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未验证 提交 8caaf85a 编写于 作者: C Chen Weihang 提交者： GitHub
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操作

[Cherry-pick] Normalize yaml name and label (#46052) 

* normalize yaml file name (#45894)

* Clear extra attributes of activation op in OpMaker (#45772)

* clear extra attr of activation op in opmaker

* fix syntax bug

* fix mkldnn kernel

* fix merge conflict

* fix bug

* [PHI] Normalize yaml op label (#45976)

* normalize yaml op label

* revert op_compat yaml change

* fix prelu and rnn compat problem

* replace api by op

* support assign op backward refuse forward (#45879)

* normize yaml backward op label (#46028)
Co-authored-by: Nzyfncg <zhangyunfei07@baidu.com>
Co-authored-by: NCharles-hit <56987902+Charles-hit@users.noreply.github.com>
上级 00486956
隐藏空白更改
内联 并排
Showing with 1111 addition and 949 deletion
paddle/fluid/eager/auto_code_generator/generator/CMakeLists.txt
浏览文件 @ 8caaf85a
set(api_yaml_path set(api_yaml_path
"${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/api.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_api.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_api.yaml" "${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/ops.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_ops.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_ops.yaml"
) )
set(backward_yaml_path set(backward_yaml_path
"${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/backward.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_backward.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_bw_api.yaml" "${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/backward.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_backward.yaml,${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_backward.yaml"
) )
set(tmp_forwards_cc_path set(tmp_forwards_cc_path
"${PADDLE_SOURCE_DIR}/paddle/fluid/eager/api/generated/eager_generated/forwards/tmp_dygraph_functions.cc" "${PADDLE_SOURCE_DIR}/paddle/fluid/eager/api/generated/eager_generated/forwards/tmp_dygraph_functions.cc"
...@@ -30,7 +30,7 @@ set(nodes_h_path ...@@ -30,7 +30,7 @@ set(nodes_h_path
) )
# StringTensor only needs forward api # StringTensor only needs forward api
set(fwd_api_yaml_path set(fwd_api_yaml_path
"${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/strings_api.yaml") "${PADDLE_SOURCE_DIR}/paddle/phi/api/yaml/strings_ops.yaml")
message("Final State Eager CodeGen") message("Final State Eager CodeGen")
add_custom_target( add_custom_target(
......
paddle/fluid/eager/auto_code_generator/generator/codegen_utils.py
浏览文件 @ 8caaf85a
...@@ -83,10 +83,10 @@ def ReadBwdFile(filepath): ...@@ -83,10 +83,10 @@ def ReadBwdFile(filepath):
ret = {} ret = {}
if contents is not None: if contents is not None:
for content in contents: for content in contents:
assert 'backward_api' in content.keys(), AssertMessage( assert 'backward_op' in content.keys(), AssertMessage(
'backward_api', content.keys()) 'backward_op', content.keys())
if 'backward_api' in content.keys(): if 'backward_op' in content.keys():
api_name = content['backward_api'] api_name = content['backward_op']
ret[api_name] = content ret[api_name] = content
f.close() f.close()
...@@ -418,12 +418,12 @@ class FunctionGeneratorBase: ...@@ -418,12 +418,12 @@ class FunctionGeneratorBase:
def CollectOriginalForwardInfo(self): def CollectOriginalForwardInfo(self):
forward_api_contents = self.forward_api_contents forward_api_contents = self.forward_api_contents
self.forward_api_name = forward_api_contents['api'] self.forward_api_name = forward_api_contents['op']
forward_args_str = forward_api_contents['args'] forward_args_str = forward_api_contents['args']
forward_returns_str = forward_api_contents['output'] forward_returns_str = forward_api_contents['output']
assert 'api' in forward_api_contents.keys( assert 'op' in forward_api_contents.keys(
), "Unable to find \"api\" in forward_api_contents keys" ), "Unable to find \"op\" in forward_api_contents keys"
assert 'args' in forward_api_contents.keys( assert 'args' in forward_api_contents.keys(
), "Unable to find \"args\" in forward_api_contents keys" ), "Unable to find \"args\" in forward_api_contents keys"
assert 'output' in forward_api_contents.keys( assert 'output' in forward_api_contents.keys(
......
paddle/fluid/eager/auto_code_generator/generator/eager_gen.py
浏览文件 @ 8caaf85a
...@@ -569,16 +569,16 @@ class DygraphFunctionGeneratorBase(FunctionGeneratorBase): ...@@ -569,16 +569,16 @@ class DygraphFunctionGeneratorBase(FunctionGeneratorBase):
forward_api_contents = self.forward_api_contents forward_api_contents = self.forward_api_contents
grad_api_contents = self.grad_api_contents grad_api_contents = self.grad_api_contents
assert 'api' in forward_api_contents.keys( assert 'op' in forward_api_contents.keys(
), "Unable to find \"api\" in api.yaml" ), "Unable to find \"op\" in ops.yaml"
assert 'args' in forward_api_contents.keys( assert 'args' in forward_api_contents.keys(
), "Unable to find \"args\" in api.yaml" ), "Unable to find \"args\" in ops.yaml"
assert 'output' in forward_api_contents.keys( assert 'output' in forward_api_contents.keys(
), "Unable to find \"output\" in api.yaml" ), "Unable to find \"output\" in ops.yaml"
if grad_api_contents is not None: if grad_api_contents is not None:
assert 'backward' in forward_api_contents.keys( assert 'backward' in forward_api_contents.keys(
), "Unable to find \"backward\" in api.yaml" ), "Unable to find \"backward\" in ops.yaml"
assert 'args' in grad_api_contents.keys( assert 'args' in grad_api_contents.keys(
), "Unable to find \"args\" in backward.yaml" ), "Unable to find \"args\" in backward.yaml"
assert 'output' in grad_api_contents.keys( assert 'output' in grad_api_contents.keys(
...@@ -1485,7 +1485,7 @@ class DygraphNodeGenerator(DygraphFunctionGeneratorBase): ...@@ -1485,7 +1485,7 @@ class DygraphNodeGenerator(DygraphFunctionGeneratorBase):
if next_grad_api_contents: if next_grad_api_contents:
# Fake forward_api_contents and backward_api_contents # Fake forward_api_contents and backward_api_contents
forward_api_contents = grad_api_contents forward_api_contents = grad_api_contents
forward_api_contents['api'] = forward_api_contents['backward_api'] forward_api_contents['op'] = forward_api_contents['backward_op']
backward_api_contents = next_grad_api_contents backward_api_contents = next_grad_api_contents
next_node_generator = DygraphFunctionGeneratorBase( next_node_generator = DygraphFunctionGeneratorBase(
...@@ -1914,11 +1914,11 @@ class DygraphForwardAndNodesGenerator(GeneratorBase): ...@@ -1914,11 +1914,11 @@ class DygraphForwardAndNodesGenerator(GeneratorBase):
grad_api_dict = self.grad_api_dict grad_api_dict = self.grad_api_dict
forward_apis_dict = {} forward_apis_dict = {}
for api_item in forward_api_list: for api_item in forward_api_list:
forward_apis_dict[api_item['api']] = api_item forward_apis_dict[api_item['op']] = api_item
namespace = self.namespace namespace = self.namespace
for forward_api_contents in forward_api_list: for forward_api_contents in forward_api_list:
if forward_api_contents['api'] in black_ops_list: continue if forward_api_contents['op'] in black_ops_list: continue
self.CollectIsForwardOnly(forward_api_contents) self.CollectIsForwardOnly(forward_api_contents)
...@@ -1959,8 +1959,7 @@ class DygraphForwardAndNodesGenerator(GeneratorBase): ...@@ -1959,8 +1959,7 @@ class DygraphForwardAndNodesGenerator(GeneratorBase):
forward_api_contents = backward_api_contents forward_api_contents = backward_api_contents
# Fake forward_api_content # Fake forward_api_content
forward_api_contents['api'] = forward_api_contents[ forward_api_contents['op'] = forward_api_contents['backward_op']
'backward_api']
backward_api_contents = next_grad_api_contents backward_api_contents = next_grad_api_contents
if len(namespace) > 0: if len(namespace) > 0:
...@@ -2043,7 +2042,7 @@ if __name__ == "__main__": ...@@ -2043,7 +2042,7 @@ if __name__ == "__main__":
api_yaml_path = api_yaml_paths[i] api_yaml_path = api_yaml_paths[i]
# string api is forwrad only # string api is forwrad only
if not api_yaml_path.endswith('strings_api.yaml'): if not api_yaml_path.endswith('strings_ops.yaml'):
backward_yaml_path = backward_yaml_paths[i] backward_yaml_path = backward_yaml_paths[i]
else: else:
backward_yaml_path = None backward_yaml_path = None
......
paddle/fluid/framework/grad_op_desc_maker.h
浏览文件 @ 8caaf85a
...@@ -213,8 +213,8 @@ class SingleGradOpMaker<OpDesc> : public GradOpDescMakerBase { ...@@ -213,8 +213,8 @@ class SingleGradOpMaker<OpDesc> : public GradOpDescMakerBase {
std::vector<std::unique_ptr<OpDesc>> retv; std::vector<std::unique_ptr<OpDesc>> retv;
retv.emplace_back(new OpDesc()); retv.emplace_back(new OpDesc());
try { try {
this->Apply(retv.front().get());
retv.front()->SetRuntimeAttrMap(this->RuntimeAttrs()); retv.front()->SetRuntimeAttrMap(this->RuntimeAttrs());
this->Apply(retv.front().get());
} catch (platform::EnforceNotMet& exception) { } catch (platform::EnforceNotMet& exception) {
framework::AppendErrorOpHint(retv.front().get()->Type(), &exception); framework::AppendErrorOpHint(retv.front().get()->Type(), &exception);
throw std::move(exception); throw std::move(exception);
......
paddle/fluid/operators/activation_op.cc
浏览文件 @ 8caaf85a
...@@ -38,29 +38,20 @@ static constexpr bool CanInplaceAct() { ...@@ -38,29 +38,20 @@ static constexpr bool CanInplaceAct() {
GradFunctor::FwdDeps() == ActBwdOpFwdDeps::kNoDeps; GradFunctor::FwdDeps() == ActBwdOpFwdDeps::kNoDeps;
} }
#define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \ #define REGISTER_ACTIVATION_OP_MAKER(OP_NAME, OP_COMMENT) \
class OP_NAME##OpMaker \ class OP_NAME##OpMaker \
: public ::paddle::framework::OpProtoAndCheckerMaker { \ : public ::paddle::framework::OpProtoAndCheckerMaker { \
public: \ public: \
void Make() override { \ void Make() override { \
AddInput("X", \ AddInput("X", \
"Input of " #OP_NAME \ "Input of " #OP_NAME \
" operator, an N-D Tensor, with data type float32, " \ " operator, an N-D Tensor, with data type float32, " \
"float64 or float16."); \ "float64 or float16."); \
AddOutput("Out", \ AddOutput("Out", \
"Output of " #OP_NAME \ "Output of " #OP_NAME \
" operator, a Tensor with shape same as input."); \ " operator, a Tensor with shape same as input."); \
AddAttr<bool>("use_mkldnn", \ AddComment(OP_COMMENT); \
"(bool, default false) Only used in mkldnn kernel") \ } \
.SetDefault(false) \
.AsExtra(); \
AddAttr<bool>("use_cudnn", \
"(bool, default false) Only used in cudnn kernel, need " \
"install cudnn") \
.SetDefault(false) \
.AsExtra(); \
AddComment(OP_COMMENT); \
} \
} }
template <ActBwdOpFwdDeps kDepValue, typename T> template <ActBwdOpFwdDeps kDepValue, typename T>
...@@ -107,8 +98,7 @@ framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx, ...@@ -107,8 +98,7 @@ framework::OpKernelType GetKernelType(const framework::ExecutionContext& ctx,
// } // }
// #endif // #endif
#ifdef PADDLE_WITH_MKLDNN #ifdef PADDLE_WITH_MKLDNN
auto it = oper.Attrs().find("use_mkldnn"); if (library == framework::LibraryType::kPlain &&
if (library == framework::LibraryType::kPlain && it != oper.Attrs().end() &&
oper.CanMKLDNNBeUsed(ctx, data_type)) { oper.CanMKLDNNBeUsed(ctx, data_type)) {
library = framework::LibraryType::kMKLDNN; library = framework::LibraryType::kMKLDNN;
layout = framework::DataLayout::kMKLDNN; layout = framework::DataLayout::kMKLDNN;
...@@ -458,10 +448,6 @@ class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -458,10 +448,6 @@ class LeakyReluOpMaker : public framework::OpProtoAndCheckerMaker {
"A LoDTensor or Tensor with the same type and size as that of x."); "A LoDTensor or Tensor with the same type and size as that of x.");
AddAttr<float>("alpha", "Slope of the activation function at x < 0.") AddAttr<float>("alpha", "Slope of the activation function at x < 0.")
.SetDefault(0.02f); .SetDefault(0.02f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
LeakyRelu Activation Operator. LeakyRelu Activation Operator.
...@@ -483,35 +469,6 @@ class SoftplusOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -483,35 +469,6 @@ class SoftplusOpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr<float>("beta", "The value of beta for Softplus.").SetDefault(1.0f); AddAttr<float>("beta", "The value of beta for Softplus.").SetDefault(1.0f);
AddAttr<float>("threshold", "The value of threshold for Softplus.") AddAttr<float>("threshold", "The value of threshold for Softplus.")
.SetDefault(20.0f); .SetDefault(20.0f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel.")
.SetDefault(false)
.AsExtra();
AddAttr<bool>(
"use_cudnn",
"(bool, default false) Only used in cudnn kernel, need install cudnn.")
.SetDefault(false)
.AsExtra();
AddAttr<std::string>(
"fuse_activation_type",
"Fused activation type used in softplus OneDNN kernel.")
.SetDefault("")
.AsExtra();
AddAttr<float>(
"fuse_activation_alpha",
"Fused activation alpha parameter type used in softplus OneDNN kernel.")
.SetDefault(0.0f)
.AsExtra();
AddAttr<float>(
"fuse_activation_beta",
"Fused activation beta parameter type used in softplus OneDNN kernel.")
.SetDefault(0.0f)
.AsExtra();
AddAttr<float>(
"fuse_activation_scale",
"Fused activation scale parameter type used in softplus OneDNN kernel.")
.SetDefault(1.0f)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
:strong:`Softplus Activation Operator` :strong:`Softplus Activation Operator`
...@@ -613,10 +570,6 @@ class ELUOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -613,10 +570,6 @@ class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
"The output is a multi-dimensional Tensor which has same " "The output is a multi-dimensional Tensor which has same "
"dimension and data type as the ``x``."); "dimension and data type as the ``x``.");
AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f); AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
ELU Activation Operator. ELU Activation Operator.
...@@ -712,10 +665,6 @@ class Relu6OpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -712,10 +665,6 @@ class Relu6OpMaker : public framework::OpProtoAndCheckerMaker {
AddAttr<float>("threshold", AddAttr<float>("threshold",
"The threshold value of Relu6. Default is 6.0. ") "The threshold value of Relu6. Default is 6.0. ")
.SetDefault(6.0f); .SetDefault(6.0f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
Relu6 Activation Operator. Relu6 Activation Operator.
...@@ -817,10 +766,6 @@ class SwishOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -817,10 +766,6 @@ class SwishOpMaker : public framework::OpProtoAndCheckerMaker {
AddInput("X", "Input of Swish operator"); AddInput("X", "Input of Swish operator");
AddOutput("Out", "Output of Swish operator"); AddOutput("Out", "Output of Swish operator");
AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f); AddAttr<float>("beta", "Constant beta of swish operator").SetDefault(1.0f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
Swish Activation Operator. Swish Activation Operator.
...@@ -841,10 +786,6 @@ class MishOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -841,10 +786,6 @@ class MishOpMaker : public framework::OpProtoAndCheckerMaker {
"of softplus will be used if absolute value of input is greater than " "of softplus will be used if absolute value of input is greater than "
":attr:`threshold`") ":attr:`threshold`")
.SetDefault(20.f); .SetDefault(20.f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
Mish Activation Operator. Mish Activation Operator.
...@@ -871,10 +812,6 @@ class HardSwishOpMaker : public framework::OpProtoAndCheckerMaker { ...@@ -871,10 +812,6 @@ class HardSwishOpMaker : public framework::OpProtoAndCheckerMaker {
.SetDefault(6.0f); .SetDefault(6.0f);
AddAttr<float>("offset", "The offset parameter of HardSwish operator") AddAttr<float>("offset", "The offset parameter of HardSwish operator")
.SetDefault(3.0f); .SetDefault(3.0f);
AddAttr<bool>("use_mkldnn",
"(bool, default false) Only used in mkldnn kernel")
.SetDefault(false)
.AsExtra();
AddComment(R"DOC( AddComment(R"DOC(
HardSwish Activation Operator. HardSwish Activation Operator.
......
paddle/phi/api/lib/CMakeLists.txt
浏览文件 @ 8caaf85a
...@@ -21,9 +21,9 @@ set(api_gen_base ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/api_base.py) ...@@ -21,9 +21,9 @@ set(api_gen_base ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/api_base.py)
# forward api file # forward api file
set(api_gen_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/api_gen.py) set(api_gen_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/api_gen.py)
set(api_yaml_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/api.yaml) set(api_yaml_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/ops.yaml)
set(legacy_api_yaml_file set(legacy_api_yaml_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_api.yaml) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/legacy_ops.yaml)
set(api_header_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/include/api.h) set(api_header_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/include/api.h)
set(api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/api.cc) set(api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/api.cc)
set(api_header_file_tmp ${api_header_file}.tmp) set(api_header_file_tmp ${api_header_file}.tmp)
...@@ -55,7 +55,7 @@ set(dygraph_api_source_file_tmp ${dygraph_api_source_file}.tmp) ...@@ -55,7 +55,7 @@ set(dygraph_api_source_file_tmp ${dygraph_api_source_file}.tmp)
set(sparse_api_gen_file set(sparse_api_gen_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/sparse_api_gen.py) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/sparse_api_gen.py)
set(sparse_api_yaml_file set(sparse_api_yaml_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_api.yaml) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_ops.yaml)
set(sparse_api_header_file set(sparse_api_header_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/include/sparse_api.h) ${CMAKE_SOURCE_DIR}/paddle/phi/api/include/sparse_api.h)
set(sparse_api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/sparse_api.cc) set(sparse_api_source_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/lib/sparse_api.cc)
...@@ -66,7 +66,7 @@ set(sparse_api_source_file_tmp ${sparse_api_source_file}.tmp) ...@@ -66,7 +66,7 @@ set(sparse_api_source_file_tmp ${sparse_api_source_file}.tmp)
set(sparse_bw_api_gen_file set(sparse_bw_api_gen_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/sparse_bw_api_gen.py) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/sparse_bw_api_gen.py)
set(sparse_bw_api_yaml_file set(sparse_bw_api_yaml_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_bw_api.yaml) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/sparse_backward.yaml)
set(sparse_bw_api_header_file set(sparse_bw_api_header_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/backward/sparse_bw_api.h) ${CMAKE_SOURCE_DIR}/paddle/phi/api/backward/sparse_bw_api.h)
set(sparse_bw_api_source_file set(sparse_bw_api_source_file
...@@ -78,7 +78,7 @@ set(sparse_bw_api_source_file_tmp ${sparse_bw_api_source_file}.tmp) ...@@ -78,7 +78,7 @@ set(sparse_bw_api_source_file_tmp ${sparse_bw_api_source_file}.tmp)
set(strings_api_gen_file set(strings_api_gen_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/strings_api_gen.py) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/strings_api_gen.py)
set(strings_api_yaml_file set(strings_api_yaml_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/strings_api.yaml) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/strings_ops.yaml)
set(strings_api_header_file set(strings_api_header_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/include/strings_api.h) ${CMAKE_SOURCE_DIR}/paddle/phi/api/include/strings_api.h)
set(strings_api_source_file set(strings_api_source_file
...@@ -97,8 +97,7 @@ set(wrapped_infermeta_source_file ...@@ -97,8 +97,7 @@ set(wrapped_infermeta_source_file
# op extra info file # op extra info file
set(ops_extra_info_gen_file set(ops_extra_info_gen_file
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/ops_extra_info_gen.py) ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/generator/ops_extra_info_gen.py)
set(api_compat_yaml_file set(op_compat_yaml_file ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/op_compat.yaml)
${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/api_compat.yaml)
set(ops_extra_info_file set(ops_extra_info_file
${CMAKE_SOURCE_DIR}/paddle/fluid/operators/ops_extra_info.cc) ${CMAKE_SOURCE_DIR}/paddle/fluid/operators/ops_extra_info.cc)
...@@ -130,10 +129,10 @@ message( ...@@ -130,10 +129,10 @@ message(
execute_process( execute_process(
WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml
COMMAND ${CMAKE_COMMAND} -E make_directory ${parsed_api_dir} COMMAND ${CMAKE_COMMAND} -E make_directory ${parsed_api_dir}
COMMAND ${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path ./api.yaml COMMAND ${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path ./ops.yaml
--output_path ./parsed_apis/api.parsed.yaml --output_path ./parsed_apis/api.parsed.yaml
COMMAND ${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path COMMAND ${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path
./legacy_api.yaml --output_path ./parsed_apis/legacy_api.parsed.yaml ./legacy_ops.yaml --output_path ./parsed_apis/legacy_api.parsed.yaml
COMMAND COMMAND
${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path ./backward.yaml ${PYTHON_EXECUTABLE} generator/parse_api.py --api_yaml_path ./backward.yaml
--output_path ./parsed_apis/backward_api.parsed.yaml --backward --output_path ./parsed_apis/backward_api.parsed.yaml --backward
...@@ -175,7 +174,7 @@ execute_process( ...@@ -175,7 +174,7 @@ execute_process(
${PYTHON_EXECUTABLE} generator/generate_op.py --api_yaml_path ${PYTHON_EXECUTABLE} generator/generate_op.py --api_yaml_path
./parsed_apis/api.parsed.yaml --backward_api_yaml_path ./parsed_apis/api.parsed.yaml --backward_api_yaml_path
./parsed_apis/backward_api.parsed.yaml --api_version_yaml_path ./parsed_apis/backward_api.parsed.yaml --api_version_yaml_path
api_version.yaml --api_compat_yaml_path api_compat.yaml --output_op_path op_version.yaml --op_compat_yaml_path op_compat.yaml --output_op_path
"${generated_op_path}.tmp" --output_arg_map_path "${generated_op_path}.tmp" --output_arg_map_path
"${generated_argument_mapping_path}.tmp" "${generated_argument_mapping_path}.tmp"
RESULT_VARIABLE _result) RESULT_VARIABLE _result)
...@@ -221,9 +220,8 @@ endif() ...@@ -221,9 +220,8 @@ endif()
# generate ops extra info # generate ops extra info
execute_process( execute_process(
COMMAND COMMAND ${PYTHON_EXECUTABLE} ${ops_extra_info_gen_file} --op_compat_yaml_path
${PYTHON_EXECUTABLE} ${ops_extra_info_gen_file} --api_compat_yaml_path ${op_compat_yaml_file} --ops_extra_info_path ${ops_extra_info_file})
${api_compat_yaml_file} --ops_extra_info_path ${ops_extra_info_file})
message("generate ${ops_extra_info_file}") message("generate ${ops_extra_info_file}")
# generate forward api # generate forward api
......
paddle/phi/api/lib/data_transform.cc
浏览文件 @ 8caaf85a
...@@ -40,7 +40,7 @@ inline bool NeedTransformPlace(const paddle::platform::Place& input, ...@@ -40,7 +40,7 @@ inline bool NeedTransformPlace(const paddle::platform::Place& input,
const TransformFlag& transform_flag) { const TransformFlag& transform_flag) {
// NOTE(dev): The default value of TransformFlag is True, if it is set with // NOTE(dev): The default value of TransformFlag is True, if it is set with
// False // False
// somewhere such as api.yaml or backward.yaml that means we should skip data // somewhere such as ops.yaml or backward.yaml that means we should skip data
// transform. Because "stop_transform_" has highest priority. // transform. Because "stop_transform_" has highest priority.
if (!transform_flag.need_trans_backend()) { if (!transform_flag.need_trans_backend()) {
return false; return false;
......
paddle/phi/api/yaml/backward.yaml
浏览文件 @ 8caaf85a
- backward_api : atan2_grad - backward_op : atan2_grad
forward : atan2 (Tensor x, Tensor y) -> Tensor(out) forward : atan2 (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -8,7 +8,7 @@ ...@@ -8,7 +8,7 @@
kernel : kernel :
func : atan2_grad func : atan2_grad
- backward_api : cholesky_grad - backward_op : cholesky_grad
forward : cholesky (Tensor x, bool upper) -> Tensor(out) forward : cholesky (Tensor x, bool upper) -> Tensor(out)
args : (Tensor out, Tensor out_grad, bool upper) args : (Tensor out, Tensor out_grad, bool upper)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -18,7 +18,7 @@ ...@@ -18,7 +18,7 @@
kernel : kernel :
func : cholesky_grad func : cholesky_grad
- backward_api : cholesky_solve_grad - backward_op : cholesky_solve_grad
forward : cholesky_solve (Tensor x, Tensor y, bool upper) -> Tensor(out) forward : cholesky_solve (Tensor x, Tensor y, bool upper) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -28,7 +28,7 @@ ...@@ -28,7 +28,7 @@
kernel : kernel :
func : cholesky_solve_grad func : cholesky_solve_grad
- backward_api : cross_grad - backward_op : cross_grad
forward : cross (Tensor x, Tensor y, int axis = 9) -> Tensor(out) forward : cross (Tensor x, Tensor y, int axis = 9) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis) args : (Tensor x, Tensor y, Tensor out_grad, int axis)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -39,7 +39,7 @@ ...@@ -39,7 +39,7 @@
func : cross_grad func : cross_grad
data_type : out_grad data_type : out_grad
- backward_api : diag_grad - backward_op : diag_grad
forward : diag (Tensor x, int offset, float padding_value) -> Tensor(out) forward : diag (Tensor x, int offset, float padding_value) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int offset) args : (Tensor x, Tensor out_grad, int offset)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -51,7 +51,7 @@ ...@@ -51,7 +51,7 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : diagonal_grad - backward_op : diagonal_grad
forward : diagonal (Tensor x, int offset, int axis1, int axis2) -> Tensor(out) forward : diagonal (Tensor x, int offset, int axis1, int axis2) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int offset = 0, int axis1 = 0, int axis2 = 1) args : (Tensor x, Tensor out_grad, int offset = 0, int axis1 = 0, int axis2 = 1)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -63,7 +63,7 @@ ...@@ -63,7 +63,7 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : digamma_grad - backward_op : digamma_grad
forward : digamma (Tensor x) -> Tensor(out) forward : digamma (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -73,7 +73,7 @@ ...@@ -73,7 +73,7 @@
kernel : kernel :
func : digamma_grad func : digamma_grad
- backward_api : dist_grad - backward_op : dist_grad
forward : dist (Tensor x, Tensor y, float p) -> Tensor(out) forward : dist (Tensor x, Tensor y, float p) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, float p) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, float p)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -83,7 +83,7 @@ ...@@ -83,7 +83,7 @@
kernel : kernel :
func : dist_grad func : dist_grad
- backward_api : dot_grad - backward_op : dot_grad
forward : dot (Tensor x, Tensor y) -> Tensor(out) forward : dot (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -94,7 +94,7 @@ ...@@ -94,7 +94,7 @@
func : dot_grad func : dot_grad
data_type : out_grad data_type : out_grad
- backward_api : erf_grad - backward_op : erf_grad
forward : erf (Tensor x) -> Tensor(out) forward : erf (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -105,7 +105,7 @@ ...@@ -105,7 +105,7 @@
func : erf_grad func : erf_grad
data_type : out_grad data_type : out_grad
- backward_api : erfinv_grad - backward_op : erfinv_grad
forward : erfinv (Tensor x) -> Tensor(out) forward : erfinv (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -115,7 +115,7 @@ ...@@ -115,7 +115,7 @@
kernel : kernel :
func : erfinv_grad func : erfinv_grad
- backward_api : fft_c2c_grad - backward_op : fft_c2c_grad
forward: fft_c2c(Tensor x, int64_t[] axes, str normalization, bool forward) -> Tensor(out) forward: fft_c2c(Tensor x, int64_t[] axes, str normalization, bool forward) -> Tensor(out)
args : (Tensor out_grad, int64_t[] axes, str normalization, bool forward) args : (Tensor out_grad, int64_t[] axes, str normalization, bool forward)
output: Tensor(x_grad) output: Tensor(x_grad)
...@@ -125,7 +125,7 @@ ...@@ -125,7 +125,7 @@
kernel : kernel :
func : fft_c2c_grad func : fft_c2c_grad
- backward_api : fft_c2r_grad - backward_op : fft_c2r_grad
forward: fft_c2r(Tensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size) -> Tensor(out) forward: fft_c2r(Tensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size) -> Tensor(out)
args : (Tensor out_grad, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size) args : (Tensor out_grad, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size)
output: Tensor(x_grad) output: Tensor(x_grad)
...@@ -135,7 +135,7 @@ ...@@ -135,7 +135,7 @@
func : fft_c2r_grad func : fft_c2r_grad
data_type: out_grad data_type: out_grad
- backward_api : fft_r2c_grad - backward_op : fft_r2c_grad
forward: fft_r2c(Tensor x, int64_t[] axes, str normalization, bool forward, bool onesided) -> Tensor(out) forward: fft_r2c(Tensor x, int64_t[] axes, str normalization, bool forward, bool onesided) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int64_t[] axes, str normalization, bool forward, bool onesided) args : (Tensor x, Tensor out_grad, int64_t[] axes, str normalization, bool forward, bool onesided)
output: Tensor(x_grad) output: Tensor(x_grad)
...@@ -147,7 +147,7 @@ ...@@ -147,7 +147,7 @@
data_type: out_grad data_type: out_grad
no_need_buffer: x no_need_buffer: x
- backward_api : graph_send_uv_grad - backward_op : graph_send_uv_grad
forward : graph_send_uv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") -> Tensor(out) forward : graph_send_uv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") -> Tensor(out)
args: (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out_grad, str message_op = "ADD") args: (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out_grad, str message_op = "ADD")
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -158,7 +158,7 @@ ...@@ -158,7 +158,7 @@
func : graph_send_uv_grad func : graph_send_uv_grad
data_type : x data_type : x
- backward_api : lgamma_grad - backward_op : lgamma_grad
forward : lgamma(Tensor x) -> Tensor(out) forward : lgamma(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -168,7 +168,7 @@ ...@@ -168,7 +168,7 @@
kernel : kernel :
func : lgamma_grad func : lgamma_grad
- backward_api : mv_grad - backward_op : mv_grad
forward : mv (Tensor x, Tensor vec) -> Tensor(out) forward : mv (Tensor x, Tensor vec) -> Tensor(out)
args : (Tensor x, Tensor vec, Tensor out_grad) args : (Tensor x, Tensor vec, Tensor out_grad)
output : Tensor(x_grad), Tensor(vec_grad) output : Tensor(x_grad), Tensor(vec_grad)
...@@ -178,7 +178,7 @@ ...@@ -178,7 +178,7 @@
kernel : kernel :
func : mv_grad func : mv_grad
- backward_api : poisson_grad - backward_op : poisson_grad
forward : poisson (Tensor x) -> Tensor(out) forward : poisson (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -188,7 +188,7 @@ ...@@ -188,7 +188,7 @@
kernel : kernel :
func : poisson_grad func : poisson_grad
- backward_api : solve_grad - backward_op : solve_grad
forward : solve (Tensor x, Tensor y) -> Tensor(out) forward : solve (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -198,7 +198,7 @@ ...@@ -198,7 +198,7 @@
kernel : kernel :
func : solve_grad func : solve_grad
- backward_api : trace_grad - backward_op : trace_grad
forward : trace (Tensor x, int offset, int axis1, int axis2) -> Tensor(out) forward : trace (Tensor x, int offset, int axis1, int axis2) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int offset, int axis1, int axis2) args : (Tensor x, Tensor out_grad, int offset, int axis1, int axis2)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -210,7 +210,7 @@ ...@@ -210,7 +210,7 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : trunc_grad - backward_op : trunc_grad
forward : trunc (Tensor x) -> Tensor(out) forward : trunc (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
......
paddle/phi/api/yaml/generator/api_base.py
浏览文件 @ 8caaf85a
...@@ -50,7 +50,7 @@ class BaseAPI(object): ...@@ -50,7 +50,7 @@ class BaseAPI(object):
self.inplace_map, self.view_map = {}, {} self.inplace_map, self.view_map = {}, {}
def get_api_name(self, api_item_yaml): def get_api_name(self, api_item_yaml):
return api_item_yaml['api'] return api_item_yaml['op']
def get_api_func_name(self): def get_api_func_name(self):
return self.api return self.api
...@@ -881,7 +881,7 @@ PADDLE_API {self.get_return_type(inplace_flag=True)} {api_func_name}({self.get_d ...@@ -881,7 +881,7 @@ PADDLE_API {self.get_return_type(inplace_flag=True)} {api_func_name}({self.get_d
def get_condition_code(self, kernel_name): def get_condition_code(self, kernel_name):
assert self.kernel['dispatch'][kernel_name], \ assert self.kernel['dispatch'][kernel_name], \
f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'scale' in api.yaml." f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'scale' in ops.yaml."
input_types = self.kernel['dispatch'][kernel_name][0] input_types = self.kernel['dispatch'][kernel_name][0]
condition_list = [] condition_list = []
for i, in_type in enumerate(input_types): for i, in_type in enumerate(input_types):
......
paddle/phi/api/yaml/generator/api_gen.py
浏览文件 @ 8caaf85a
...@@ -319,7 +319,7 @@ def main(): ...@@ -319,7 +319,7 @@ def main():
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
help='path to api yaml file', help='path to api yaml file',
nargs='+', nargs='+',
default='paddle/phi/api/yaml/api.yaml') default='paddle/phi/api/yaml/ops.yaml')
parser.add_argument('--api_header_path', parser.add_argument('--api_header_path',
help='output of generated api header code file', help='output of generated api header code file',
......
paddle/phi/api/yaml/generator/backward_api_gen.py
浏览文件 @ 8caaf85a
...@@ -28,14 +28,14 @@ class BackwardAPI(BaseAPI): ...@@ -28,14 +28,14 @@ class BackwardAPI(BaseAPI):
self.no_need_buffer = self.parse_no_need_buffer(backward_item_yaml) self.no_need_buffer = self.parse_no_need_buffer(backward_item_yaml)
def get_api_name(self, api_item_yaml): def get_api_name(self, api_item_yaml):
return api_item_yaml['backward_api'] return api_item_yaml['backward_op']
def parse_forward_config(self, forward_config): def parse_forward_config(self, forward_config):
# api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out) # api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out)
result = re.search( result = re.search(
r"(?P<api>[a-z][a-z0-9_]+)\s*(?P<args>\([^\)]+\))\s*->\s*(?P<outputs>.+)", r"(?P<op>[a-z][a-z0-9_]+)\s*(?P<args>\([^\)]+\))\s*->\s*(?P<outputs>.+)",
forward_config) forward_config)
api = result.group('api') api = result.group('op')
_, outputs, _, = self.parse_output(self.api, result.group('outputs')) _, outputs, _, = self.parse_output(self.api, result.group('outputs'))
outputs = [item.split('@')[0] for item in outputs] outputs = [item.split('@')[0] for item in outputs]
fw_inputs, fw_attrs = self.parse_input_and_attr(api, fw_inputs, fw_attrs = self.parse_input_and_attr(api,
......
paddle/phi/api/yaml/generator/generate_op.py
浏览文件 @ 8caaf85a
...@@ -65,7 +65,7 @@ def replace_compat_name(api_op_map, forward_api_dict, backward_api_dict): ...@@ -65,7 +65,7 @@ def replace_compat_name(api_op_map, forward_api_dict, backward_api_dict):
return names[0].strip(), names[1].split(')')[0].strip() return names[0].strip(), names[1].split(')')[0].strip()
for api_args in api_op_map: for api_args in api_op_map:
api_name, op_name = get_api_and_op_name(api_args['api']) api_name, op_name = get_api_and_op_name(api_args['op'])
if api_name not in forward_api_dict: if api_name not in forward_api_dict:
continue continue
forward_api_item = forward_api_dict[api_name] forward_api_item = forward_api_dict[api_name]
...@@ -175,7 +175,7 @@ def replace_compat_name(api_op_map, forward_api_dict, backward_api_dict): ...@@ -175,7 +175,7 @@ def replace_compat_name(api_op_map, forward_api_dict, backward_api_dict):
] ]
def main(api_yaml_path, backward_yaml_path, api_compat_yaml_path, def main(api_yaml_path, backward_yaml_path, op_compat_yaml_path,
api_version_yaml_path, output_op_path, output_arg_map_path): api_version_yaml_path, output_op_path, output_arg_map_path):
with open(api_yaml_path, "rt") as f: with open(api_yaml_path, "rt") as f:
apis = yaml.safe_load(f) apis = yaml.safe_load(f)
...@@ -191,9 +191,9 @@ def main(api_yaml_path, backward_yaml_path, api_compat_yaml_path, ...@@ -191,9 +191,9 @@ def main(api_yaml_path, backward_yaml_path, api_compat_yaml_path,
api_versions = yaml.safe_load(f) api_versions = yaml.safe_load(f)
# add api version info into api # add api version info into api
for api_version in api_versions: for api_version in api_versions:
forward_api_dict[api_version['api']]['version'] = api_version['version'] forward_api_dict[api_version['op']]['version'] = api_version['version']
with open(api_compat_yaml_path, "rt") as f: with open(op_compat_yaml_path, "rt") as f:
api_op_map = yaml.safe_load(f) api_op_map = yaml.safe_load(f)
for api in apis: for api in apis:
...@@ -244,7 +244,7 @@ if __name__ == "__main__": ...@@ -244,7 +244,7 @@ if __name__ == "__main__":
parser.add_argument('--backward_api_yaml_path', parser.add_argument('--backward_api_yaml_path',
type=str, type=str,
help="parsed backward api yaml file.") help="parsed backward api yaml file.")
parser.add_argument('--api_compat_yaml_path', parser.add_argument('--op_compat_yaml_path',
type=str, type=str,
help="api args compat yaml file.") help="api args compat yaml file.")
parser.add_argument('--api_version_yaml_path', parser.add_argument('--api_version_yaml_path',
...@@ -260,5 +260,5 @@ if __name__ == "__main__": ...@@ -260,5 +260,5 @@ if __name__ == "__main__":
args = parser.parse_args() args = parser.parse_args()
main(args.api_yaml_path, args.backward_api_yaml_path, main(args.api_yaml_path, args.backward_api_yaml_path,
args.api_compat_yaml_path, args.api_version_yaml_path, args.op_compat_yaml_path, args.api_version_yaml_path,
args.output_op_path, args.output_arg_map_path) args.output_op_path, args.output_arg_map_path)
paddle/phi/api/yaml/generator/intermediate_api_gen.py
浏览文件 @ 8caaf85a
...@@ -135,11 +135,11 @@ def main(): ...@@ -135,11 +135,11 @@ def main():
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
nargs='+', nargs='+',
help='path to api yaml file', help='path to api yaml file',
default='paddle/phi/api/yaml/api.yaml') default='paddle/phi/api/yaml/ops.yaml')
parser.add_argument('--sparse_api_yaml_path', parser.add_argument('--sparse_api_yaml_path',
help='path to sparse api yaml file', help='path to sparse api yaml file',
default='paddle/phi/api/yaml/sparse_api.yaml') default='paddle/phi/api/yaml/sparse_ops.yaml')
parser.add_argument('--dygraph_api_header_path', parser.add_argument('--dygraph_api_header_path',
help='output of generated dygraph api header code file', help='output of generated dygraph api header code file',
......
paddle/phi/api/yaml/generator/ops_extra_info_gen.py
浏览文件 @ 8caaf85a
...@@ -65,9 +65,9 @@ def parse_attr(attr_str): ...@@ -65,9 +65,9 @@ def parse_attr(attr_str):
'name'), result.group('default_val') 'name'), result.group('default_val')
def generate_extra_info(api_compat_yaml_path, ops_extra_info_path): def generate_extra_info(op_compat_yaml_path, ops_extra_info_path):
compat_apis = [] compat_apis = []
with open(api_compat_yaml_path, 'rt') as f: with open(op_compat_yaml_path, 'rt') as f:
compat_apis = yaml.safe_load(f) compat_apis = yaml.safe_load(f)
def get_op_name(api_item): def get_op_name(api_item):
...@@ -80,9 +80,9 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path): ...@@ -80,9 +80,9 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path):
extra_map_str_list = [] extra_map_str_list = []
extra_checker_str_list = [] extra_checker_str_list = []
for api_compat_args in compat_apis: for op_compat_args in compat_apis:
if 'extra' in api_compat_args: if 'extra' in op_compat_args:
extra_args_map = api_compat_args['extra'] extra_args_map = op_compat_args['extra']
# TODO(chenweihang): add inputs and outputs # TODO(chenweihang): add inputs and outputs
if 'attrs' in extra_args_map: if 'attrs' in extra_args_map:
attr_map_list = [] attr_map_list = []
...@@ -103,13 +103,13 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path): ...@@ -103,13 +103,13 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path):
api_extra_attr_checkers = ",\n ".join( api_extra_attr_checkers = ",\n ".join(
attr_checker_func_list) attr_checker_func_list)
extra_map_str_list.append( extra_map_str_list.append(
f"{{\"{get_op_name(api_compat_args['api'])}\", {{ {api_extra_attr_map} }}}}" f"{{\"{get_op_name(op_compat_args['op'])}\", {{ {api_extra_attr_map} }}}}"
) )
extra_checker_str_list.append( extra_checker_str_list.append(
f"{{\"{get_op_name(api_compat_args['api'])}\", {{ {api_extra_attr_checkers} }}}}" f"{{\"{get_op_name(op_compat_args['op'])}\", {{ {api_extra_attr_checkers} }}}}"
) )
if 'backward' in api_compat_args: if 'backward' in op_compat_args:
for bw_item in api_compat_args['backward'].split(','): for bw_item in op_compat_args['backward'].split(','):
bw_op_name = get_op_name(bw_item) bw_op_name = get_op_name(bw_item)
extra_map_str_list.append( extra_map_str_list.append(
f"{{\"{bw_op_name}\", {{ {api_extra_attr_map} }}}}") f"{{\"{bw_op_name}\", {{ {api_extra_attr_map} }}}}")
...@@ -127,9 +127,9 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path): ...@@ -127,9 +127,9 @@ def generate_extra_info(api_compat_yaml_path, ops_extra_info_path):
def main(): def main():
parser = argparse.ArgumentParser( parser = argparse.ArgumentParser(
description='Generate PaddlePaddle Extra Param Info for Op') description='Generate PaddlePaddle Extra Param Info for Op')
parser.add_argument('--api_compat_yaml_path', parser.add_argument('--op_compat_yaml_path',
help='path to api compat yaml file', help='path to api compat yaml file',
default='paddle/phi/api/yaml/api_compat.yaml') default='paddle/phi/api/yaml/op_compat.yaml')
parser.add_argument('--ops_extra_info_path', parser.add_argument('--ops_extra_info_path',
help='output of generated extra_prama_info code file', help='output of generated extra_prama_info code file',
...@@ -137,10 +137,10 @@ def main(): ...@@ -137,10 +137,10 @@ def main():
options = parser.parse_args() options = parser.parse_args()
api_compat_yaml_path = options.api_compat_yaml_path op_compat_yaml_path = options.op_compat_yaml_path
ops_extra_info_path = options.ops_extra_info_path ops_extra_info_path = options.ops_extra_info_path
generate_extra_info(api_compat_yaml_path, ops_extra_info_path) generate_extra_info(op_compat_yaml_path, ops_extra_info_path)
if __name__ == '__main__': if __name__ == '__main__':
......
paddle/phi/api/yaml/generator/parse_api.py
浏览文件 @ 8caaf85a
...@@ -27,7 +27,7 @@ def main(api_yaml_path, output_path, backward): ...@@ -27,7 +27,7 @@ def main(api_yaml_path, output_path, backward):
apis = [] apis = []
else: else:
apis = [ apis = [
parse_api_entry(api, "backward_api" if backward else "api") parse_api_entry(api, "backward_op" if backward else "op")
for api in apis for api in apis
] ]
......
paddle/phi/api/yaml/generator/parse_utils.py
浏览文件 @ 8caaf85a
...@@ -210,9 +210,9 @@ def extract_type_and_name(records: List[Dict]) -> List[Dict]: ...@@ -210,9 +210,9 @@ def extract_type_and_name(records: List[Dict]) -> List[Dict]:
def parse_forward(api_name: str, forward_config: str) -> Dict[str, Any]: def parse_forward(api_name: str, forward_config: str) -> Dict[str, Any]:
# api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out) # api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out)
result = re.search( result = re.search(
r"(?P<api>[a-z][a-z0-9_]+)\s*(?P<args>\([^\)]+\))\s*->\s*(?P<outputs>.+)", r"(?P<op>[a-z][a-z0-9_]+)\s*(?P<args>\([^\)]+\))\s*->\s*(?P<outputs>.+)",
forward_config) forward_config)
api = result.group("api") api = result.group("op")
outputs = parse_outputs(api_name, result.group("outputs")) outputs = parse_outputs(api_name, result.group("outputs"))
outputs = extract_type_and_name(outputs) outputs = extract_type_and_name(outputs)
...@@ -228,7 +228,7 @@ def parse_forward(api_name: str, forward_config: str) -> Dict[str, Any]: ...@@ -228,7 +228,7 @@ def parse_forward(api_name: str, forward_config: str) -> Dict[str, Any]:
return forward_cfg return forward_cfg
def parse_api_entry(api_entry: Dict[str, Any], name_field="api"): def parse_api_entry(api_entry: Dict[str, Any], name_field="op"):
api_name = api_entry[name_field] api_name = api_entry[name_field]
inputs, attrs = parse_input_and_attr(api_name, api_entry["args"]) inputs, attrs = parse_input_and_attr(api_name, api_entry["args"])
outputs = parse_outputs(api_name, api_entry["output"]) outputs = parse_outputs(api_name, api_entry["output"])
...@@ -334,7 +334,7 @@ def parse_api_entry(api_entry: Dict[str, Any], name_field="api"): ...@@ -334,7 +334,7 @@ def parse_api_entry(api_entry: Dict[str, Any], name_field="api"):
api["backward"] = backward api["backward"] = backward
# forward for backward_apis # forward for backward_apis
is_backward_api = name_field == "backward_api" is_backward_api = name_field == "backward_op"
if is_backward_api: if is_backward_api:
if "forward" in api_entry: if "forward" in api_entry:
forward = parse_forward(api_name, api_entry["forward"]) forward = parse_forward(api_name, api_entry["forward"])
......
paddle/phi/api/yaml/generator/sparse_api_gen.py
浏览文件 @ 8caaf85a
...@@ -160,7 +160,7 @@ class SparseAPI(ForwardAPI): ...@@ -160,7 +160,7 @@ class SparseAPI(ForwardAPI):
def get_condition_code(self, kernel_name): def get_condition_code(self, kernel_name):
assert self.kernel['dispatch'][kernel_name], \ assert self.kernel['dispatch'][kernel_name], \
f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'conv3d' in sparse_api.yaml." f"{self.api} api: the tensor type of inputs and outputs for kernel isn't set, see also 'kernel:func' of 'conv3d' in sparse_ops.yaml."
input_types = self.kernel['dispatch'][kernel_name][0] input_types = self.kernel['dispatch'][kernel_name][0]
sparse_type_map = { sparse_type_map = {
'sparse_coo': 'DataLayout::SPARSE_COO', 'sparse_coo': 'DataLayout::SPARSE_COO',
...@@ -284,7 +284,7 @@ def main(): ...@@ -284,7 +284,7 @@ def main():
description='Generate PaddlePaddle C++ Sparse API files') description='Generate PaddlePaddle C++ Sparse API files')
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
help='path to sparse api yaml file', help='path to sparse api yaml file',
default='paddle/phi/api/yaml/sparse_api.yaml') default='paddle/phi/api/yaml/sparse_ops.yaml')
parser.add_argument('--api_header_path', parser.add_argument('--api_header_path',
help='output of generated api header code file', help='output of generated api header code file',
......
paddle/phi/api/yaml/generator/sparse_bw_api_gen.py
浏览文件 @ 8caaf85a
...@@ -164,7 +164,7 @@ def main(): ...@@ -164,7 +164,7 @@ def main():
description='Generate PaddlePaddle C++ Sparse API files') description='Generate PaddlePaddle C++ Sparse API files')
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
help='path to sparse api yaml file', help='path to sparse api yaml file',
default='paddle/phi/api/yaml/sparse_bw_api.yaml') default='paddle/phi/api/yaml/sparse_backward.yaml')
parser.add_argument('--api_header_path', parser.add_argument('--api_header_path',
help='output of generated api header code file', help='output of generated api header code file',
......
paddle/phi/api/yaml/generator/strings_api_gen.py
浏览文件 @ 8caaf85a
...@@ -351,7 +351,7 @@ def main(): ...@@ -351,7 +351,7 @@ def main():
description='Generate PaddlePaddle C++ Strings API files') description='Generate PaddlePaddle C++ Strings API files')
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
help='path to sparse api yaml file', help='path to sparse api yaml file',
default='paddle/phi/api/yaml/strings_api.yaml') default='paddle/phi/api/yaml/strings_ops.yaml')
parser.add_argument('--api_header_path', parser.add_argument('--api_header_path',
help='output of generated api header code file', help='output of generated api header code file',
......
paddle/phi/api/yaml/generator/wrapped_infermeta_gen.py
浏览文件 @ 8caaf85a
...@@ -167,7 +167,7 @@ def main(): ...@@ -167,7 +167,7 @@ def main():
parser.add_argument('--api_yaml_path', parser.add_argument('--api_yaml_path',
help='path to api yaml file', help='path to api yaml file',
nargs='+', nargs='+',
default='paddle/phi/api/yaml/api.yaml') default='paddle/phi/api/yaml/ops.yaml')
parser.add_argument( parser.add_argument(
'--wrapped_infermeta_header_path', '--wrapped_infermeta_header_path',
help='output of generated wrapped_infermeta header code file', help='output of generated wrapped_infermeta header code file',
......
paddle/phi/api/yaml/legacy_backward.yaml
浏览文件 @ 8caaf85a
- backward_api : abs_double_grad - backward_op : abs_double_grad
forward : abs_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x) forward : abs_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_x_grad) args : (Tensor x, Tensor grad_x_grad)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -10,7 +10,7 @@ ...@@ -10,7 +10,7 @@
data_transform: data_transform:
skip_transform : grad_x_grad skip_transform : grad_x_grad
- backward_api : abs_grad - backward_op : abs_grad
forward : abs (Tensor x) -> Tensor(out) forward : abs (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -23,7 +23,7 @@ ...@@ -23,7 +23,7 @@
skip_transform : out_grad skip_transform : out_grad
backward : abs_double_grad backward : abs_double_grad
- backward_api : acos_grad - backward_op : acos_grad
forward : acos (Tensor x) -> Tensor(out) forward : acos (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -34,7 +34,7 @@ ...@@ -34,7 +34,7 @@
func : acos_grad func : acos_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : acosh_grad - backward_op : acosh_grad
forward : acosh (Tensor x) -> Tensor(out) forward : acosh (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -45,7 +45,7 @@ ...@@ -45,7 +45,7 @@
func : acosh_grad func : acosh_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : add_double_grad - backward_op : add_double_grad
forward : add_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y) forward : add_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
args : (Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1) args : (Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -58,7 +58,7 @@ ...@@ -58,7 +58,7 @@
backward : add_triple_grad backward : add_triple_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : add_grad - backward_op : add_grad
forward : add (Tensor x, Tensor y) -> Tensor(out) forward : add (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -71,7 +71,7 @@ ...@@ -71,7 +71,7 @@
backward : add_double_grad backward : add_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : add_triple_grad - backward_op : add_triple_grad
forward : add_double_grad (Tensor y, Tensor grad_out, Tensor grad_grad_x, Tensor grad_grad_y, int axis = -1) -> Tensor(grad_grad_out) forward : add_double_grad (Tensor y, Tensor grad_out, Tensor grad_grad_x, Tensor grad_grad_y, int axis = -1) -> Tensor(grad_grad_out)
args : (Tensor grad_grad_x, Tensor grad_grad_y, Tensor grad_grad_out_grad, int axis = -1) args : (Tensor grad_grad_x, Tensor grad_grad_y, Tensor grad_grad_out_grad, int axis = -1)
output : Tensor(grad_grad_x_grad), Tensor(grad_grad_y_grad) output : Tensor(grad_grad_x_grad), Tensor(grad_grad_y_grad)
...@@ -82,7 +82,7 @@ ...@@ -82,7 +82,7 @@
func : add_triple_grad func : add_triple_grad
inplace : (grad_grad_out_grad -> grad_grad_x_grad) inplace : (grad_grad_out_grad -> grad_grad_x_grad)
- backward_api : addmm_grad - backward_op : addmm_grad
forward : addmm (Tensor input, Tensor x, Tensor y, float alpha, float beta) -> Tensor(out) forward : addmm (Tensor input, Tensor x, Tensor y, float alpha, float beta) -> Tensor(out)
args : (Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha, float beta) args : (Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha, float beta)
output : Tensor(input_grad), Tensor(x_grad), Tensor(y_grad) output : Tensor(input_grad), Tensor(x_grad), Tensor(y_grad)
...@@ -92,7 +92,7 @@ ...@@ -92,7 +92,7 @@
kernel : kernel :
func : addmm_grad func : addmm_grad
- backward_api : affine_grid_grad - backward_op : affine_grid_grad
forward : affine_grid (Tensor input, IntArray outputShape, bool use_cudnn=true, bool align_corners=true) -> Tensor(output) forward : affine_grid (Tensor input, IntArray outputShape, bool use_cudnn=true, bool align_corners=true) -> Tensor(output)
args : (Tensor output_grad, IntArray outputShape, bool use_cudnn=true, bool align_corners=true) args : (Tensor output_grad, IntArray outputShape, bool use_cudnn=true, bool align_corners=true)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -104,7 +104,7 @@ ...@@ -104,7 +104,7 @@
param : [output_grad, outputShape, align_corners] param : [output_grad, outputShape, align_corners]
use_gpudnn: use_cudnn use_gpudnn: use_cudnn
- backward_api : amax_grad - backward_op : amax_grad
forward: amax (Tensor x, int64_t[] dims={}, bool keep_dim=false) -> Tensor(out) forward: amax (Tensor x, int64_t[] dims={}, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] dims={}, bool keep_dim=false, bool reduce_all=false) args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] dims={}, bool keep_dim=false, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -114,7 +114,7 @@ ...@@ -114,7 +114,7 @@
kernel : kernel :
func : amax_grad func : amax_grad
- backward_api : amin_grad - backward_op : amin_grad
forward: amin (Tensor x, int64_t[] dims={}, bool keep_dim=false) -> Tensor(out) forward: amin (Tensor x, int64_t[] dims={}, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] dims={}, bool keep_dim=false, bool reduce_all=false) args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] dims={}, bool keep_dim=false, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -124,7 +124,7 @@ ...@@ -124,7 +124,7 @@
kernel : kernel :
func : amin_grad func : amin_grad
- backward_api : angle_grad - backward_op : angle_grad
forward : angle (Tensor x) -> Tensor(out) forward : angle (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -136,7 +136,7 @@ ...@@ -136,7 +136,7 @@
data_transform: data_transform:
skip_transform : out_grad skip_transform : out_grad
- backward_api : argsort_grad - backward_op : argsort_grad
forward : argsort (Tensor x, int axis, bool descending) -> Tensor(out), Tensor(indices) forward : argsort (Tensor x, int axis, bool descending) -> Tensor(out), Tensor(indices)
args : (Tensor indices, Tensor x, Tensor out_grad, int axis, bool descending) args : (Tensor indices, Tensor x, Tensor out_grad, int axis, bool descending)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -148,19 +148,19 @@ ...@@ -148,19 +148,19 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : as_complex_grad - backward_op : as_complex_grad
forward : as_complex (Tensor x) -> Tensor(out) forward : as_complex (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : as_real(out_grad) invoke : as_real(out_grad)
- backward_api : as_real_grad - backward_op : as_real_grad
forward : as_real (Tensor x) -> Tensor(out) forward : as_real (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : as_complex(out_grad) invoke : as_complex(out_grad)
- backward_api : asin_grad - backward_op : asin_grad
forward : asin (Tensor x) -> Tensor(out) forward : asin (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -171,7 +171,7 @@ ...@@ -171,7 +171,7 @@
func : asin_grad func : asin_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : asinh_grad - backward_op : asinh_grad
forward : asinh (Tensor x) -> Tensor(out) forward : asinh (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -182,29 +182,13 @@ ...@@ -182,29 +182,13 @@
func : asinh_grad func : asinh_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : assign_double_grad - backward_op : assign_grad
forward : assign_grad (Tensor grad_out) -> Tensor(grad_x)
args : (Tensor grad_x_grad)
output : Tensor(grad_out_grad)
infer_meta :
func : UnchangedInferMeta
kernel :
func : assign
backward: assign_triple_grad
inplace : (grad_x_grad -> grad_out_grad)
- backward_api : assign_grad
forward : assign (Tensor x) -> Tensor(out) forward : assign (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
infer_meta : invoke : assign(out_grad)
func : UnchangedInferMeta
kernel :
func : assign
backward: assign_double_grad
inplace : (out_grad -> x_grad)
- backward_api : assign_out__grad - backward_op : assign_out__grad
forward : assign_out_ (Tensor x, Tensor output) -> Tensor(out) forward : assign_out_ (Tensor x, Tensor output) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -214,17 +198,7 @@ ...@@ -214,17 +198,7 @@
func : assign func : assign
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : assign_triple_grad - backward_op : atan_grad
forward : assign_double_grad (Tensor grad_out) -> Tensor(grad_x)
args : (Tensor grad_x_grad)
output : Tensor(grad_out_grad)
infer_meta :
func : UnchangedInferMeta
kernel :
func : assign
inplace : (grad_x_grad -> grad_out_grad)
- backward_api : atan_grad
forward : atan (Tensor x) -> Tensor(out) forward : atan (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -235,7 +209,7 @@ ...@@ -235,7 +209,7 @@
func : atan_grad func : atan_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : atanh_grad - backward_op : atanh_grad
forward : atanh (Tensor x) -> Tensor(out) forward : atanh (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -246,7 +220,7 @@ ...@@ -246,7 +220,7 @@
func : atanh_grad func : atanh_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : batch_norm_double_grad - backward_op : batch_norm_double_grad
forward : batch_norm_grad (Tensor x, Tensor scale, Tensor bias, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor grad_out, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias) forward : batch_norm_grad (Tensor x, Tensor scale, Tensor bias, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor grad_out, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias)
args : (Tensor x, Tensor scale, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor grad_out, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) args : (Tensor x, Tensor scale, Tensor out_mean, Tensor out_variance, Tensor saved_mean, Tensor saved_variance, Tensor grad_out, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(grad_out_grad)
...@@ -259,7 +233,7 @@ ...@@ -259,7 +233,7 @@
optional : out_mean, out_variance optional : out_mean, out_variance
inplace : (grad_out -> grad_out_grad) inplace : (grad_out -> grad_out_grad)
- backward_api : batch_norm_grad - backward_op : batch_norm_grad
forward : batch_norm (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space) forward : batch_norm (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean_out, Tensor variance_out, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) args : (Tensor x, Tensor scale, Tensor bias, Tensor mean_out, Tensor variance_out, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
...@@ -272,7 +246,7 @@ ...@@ -272,7 +246,7 @@
optional : mean_out, variance_out, reserve_space optional : mean_out, variance_out, reserve_space
backward : batch_norm_double_grad backward : batch_norm_double_grad
- backward_api : bce_loss_grad - backward_op : bce_loss_grad
forward : bce_loss (Tensor input, Tensor label) -> Tensor(out) forward : bce_loss (Tensor input, Tensor label) -> Tensor(out)
args : (Tensor input, Tensor label, Tensor out_grad) args : (Tensor input, Tensor label, Tensor out_grad)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -283,7 +257,7 @@ ...@@ -283,7 +257,7 @@
func : bce_loss_grad func : bce_loss_grad
inplace : (out_grad -> input_grad) inplace : (out_grad -> input_grad)
- backward_api : bicubic_interp_grad - backward_op : bicubic_interp_grad
forward : bicubic_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output) forward : bicubic_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -295,7 +269,7 @@ ...@@ -295,7 +269,7 @@
func : bicubic_interp_grad func : bicubic_interp_grad
data_type : output_grad data_type : output_grad
- backward_api : bilinear_interp_grad - backward_op : bilinear_interp_grad
forward : bilinear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output) forward : bilinear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -307,7 +281,7 @@ ...@@ -307,7 +281,7 @@
func : bilinear_interp_grad func : bilinear_interp_grad
data_type : output_grad data_type : output_grad
- backward_api : bilinear_tensor_product_grad - backward_op : bilinear_tensor_product_grad
forward : bilinear_tensor_product (Tensor x, Tensor y, Tensor weight, Tensor bias) -> Tensor(out) forward : bilinear_tensor_product (Tensor x, Tensor y, Tensor weight, Tensor bias) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor weight, Tensor out_grad) args : (Tensor x, Tensor y, Tensor weight, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad), Tensor(weight_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(y_grad), Tensor(weight_grad), Tensor(bias_grad)
...@@ -316,7 +290,7 @@ ...@@ -316,7 +290,7 @@
kernel : kernel :
func : bilinear_tensor_product_grad func : bilinear_tensor_product_grad
- backward_api : bmm_grad - backward_op : bmm_grad
forward : bmm (Tensor x, Tensor y) -> Tensor(out) forward : bmm (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -325,7 +299,7 @@ ...@@ -325,7 +299,7 @@
kernel : kernel :
func : bmm_grad func : bmm_grad
- backward_api : brelu_grad - backward_op : brelu_grad
forward : brelu (Tensor x, float t_min, float t_max) -> Tensor(out) forward : brelu (Tensor x, float t_min, float t_max) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float t_min, float t_max) args : (Tensor x, Tensor out_grad, float t_min, float t_max)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -336,7 +310,7 @@ ...@@ -336,7 +310,7 @@
func : brelu_grad func : brelu_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : broadcast_tensors_grad - backward_op : broadcast_tensors_grad
forward : broadcast_tensors (Tensor[] x) -> Tensor[](out) forward : broadcast_tensors (Tensor[] x) -> Tensor[](out)
args : (Tensor[] x, Tensor[] out_grad) args : (Tensor[] x, Tensor[] out_grad)
output : Tensor[](x_grad) output : Tensor[](x_grad)
...@@ -348,7 +322,7 @@ ...@@ -348,7 +322,7 @@
param : [out_grad] param : [out_grad]
no_need_buffer : x no_need_buffer : x
- backward_api : cast_grad - backward_op : cast_grad
forward : cast (Tensor x, DataType out_dtype) -> Tensor(out) forward : cast (Tensor x, DataType out_dtype) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -360,7 +334,7 @@ ...@@ -360,7 +334,7 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : ceil_grad - backward_op : ceil_grad
forward : ceil(Tensor x) -> Tensor(out) forward : ceil(Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -371,7 +345,7 @@ ...@@ -371,7 +345,7 @@
func : ceil_grad func : ceil_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : celu_double_grad - backward_op : celu_double_grad
forward : celu_grad(Tensor x, Tensor grad_out, float alpha) -> Tensor(grad_x) forward : celu_grad(Tensor x, Tensor grad_out, float alpha) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_out, Tensor grad_x_grad, float alpha) args : (Tensor x, Tensor grad_out, Tensor grad_x_grad, float alpha)
output : Tensor(x_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(grad_out_grad)
...@@ -382,7 +356,7 @@ ...@@ -382,7 +356,7 @@
func : celu_double_grad func : celu_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : celu_grad - backward_op : celu_grad
forward : celu(Tensor x, float alpha) -> Tensor(out) forward : celu(Tensor x, float alpha) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float alpha) args : (Tensor x, Tensor out_grad, float alpha)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -394,7 +368,7 @@ ...@@ -394,7 +368,7 @@
backward : celu_double_grad backward : celu_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : clip_double_grad - backward_op : clip_double_grad
forward : clip_grad (Tensor x, Tensor grad_out, Scalar min = 0., Scalar max = 0.) -> Tensor(grad_x) forward : clip_grad (Tensor x, Tensor grad_out, Scalar min = 0., Scalar max = 0.) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_x_grad, Scalar min = 0., Scalar max = 0.) args : (Tensor x, Tensor grad_x_grad, Scalar min = 0., Scalar max = 0.)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -404,7 +378,7 @@ ...@@ -404,7 +378,7 @@
kernel : kernel :
func : clip_grad func : clip_grad
- backward_api : clip_grad - backward_op : clip_grad
forward : clip (Tensor x, Scalar min, Scalar max) -> Tensor(out) forward : clip (Tensor x, Scalar min, Scalar max) -> Tensor(out)
args : (Tensor x, Tensor out_grad, Scalar min = 0., Scalar max = 0.) args : (Tensor x, Tensor out_grad, Scalar min = 0., Scalar max = 0.)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -416,7 +390,7 @@ ...@@ -416,7 +390,7 @@
backward : clip_double_grad backward : clip_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : complex_grad - backward_op : complex_grad
forward : complex (Tensor x, Tensor y) -> Tensor(out) forward : complex (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -426,7 +400,7 @@ ...@@ -426,7 +400,7 @@
func : complex_grad func : complex_grad
data_type : x data_type : x
- backward_api : concat_double_grad - backward_op : concat_double_grad
forward : concat_grad (Tensor[] x, Tensor grad_out, Scalar axis) -> Tensor[](grad_x) forward : concat_grad (Tensor[] x, Tensor grad_out, Scalar axis) -> Tensor[](grad_x)
args : (Tensor[] grad_x_grad, Scalar axis = 0) args : (Tensor[] grad_x_grad, Scalar axis = 0)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -436,7 +410,7 @@ ...@@ -436,7 +410,7 @@
kernel : kernel :
func : concat func : concat
- backward_api : concat_grad - backward_op : concat_grad
forward : concat (Tensor[] x, Scalar axis) -> Tensor(out) forward : concat (Tensor[] x, Scalar axis) -> Tensor(out)
args : (Tensor[] x, Tensor out_grad, Scalar axis = 0) args : (Tensor[] x, Tensor out_grad, Scalar axis = 0)
output : Tensor[](x_grad){x.size()} output : Tensor[](x_grad){x.size()}
...@@ -448,7 +422,7 @@ ...@@ -448,7 +422,7 @@
no_need_buffer : x no_need_buffer : x
backward : concat_double_grad backward : concat_double_grad
- backward_api : conj_grad - backward_op : conj_grad
forward : conj (Tensor x) -> Tensor(out) forward : conj (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -458,7 +432,7 @@ ...@@ -458,7 +432,7 @@
kernel : kernel :
func : conj func : conj
- backward_api : conv2d_grad - backward_op : conv2d_grad
forward : conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(out) forward : conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor(input_grad), Tensor(filter_grad) output : Tensor(input_grad), Tensor(filter_grad)
...@@ -470,7 +444,7 @@ ...@@ -470,7 +444,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv2d_grad_grad backward : conv2d_grad_grad
- backward_api : conv2d_grad_grad - backward_op : conv2d_grad_grad
forward : conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(grad_input), Tensor(grad_filter) forward : conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad) output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
...@@ -482,7 +456,7 @@ ...@@ -482,7 +456,7 @@
use_gpudnn : true use_gpudnn : true
optional : grad_input_grad, grad_filter_grad optional : grad_input_grad, grad_filter_grad
- backward_api : conv2d_transpose_double_grad - backward_op : conv2d_transpose_double_grad
forward : conv2d_transpose_grad(Tensor x, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(grad_x), Tensor(grad_filter) forward : conv2d_transpose_grad(Tensor x, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(grad_x), Tensor(grad_filter)
args : (Tensor x, Tensor filter, Tensor grad_out, Tensor grad_x_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, Tensor grad_out, Tensor grad_x_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(x_grad), Tensor(filter_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(filter_grad), Tensor(grad_out_grad)
...@@ -492,7 +466,7 @@ ...@@ -492,7 +466,7 @@
func : conv2d_transpose_grad_grad func : conv2d_transpose_grad_grad
use_gpudnn : true use_gpudnn : true
- backward_api : conv2d_transpose_grad - backward_op : conv2d_transpose_grad
forward : conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out) forward : conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(x_grad), Tensor(filter_grad) output : Tensor(x_grad), Tensor(filter_grad)
...@@ -503,7 +477,7 @@ ...@@ -503,7 +477,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv2d_transpose_double_grad backward : conv2d_transpose_double_grad
- backward_api : conv3d_grad - backward_op : conv3d_grad
forward : conv3d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(out) forward : conv3d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor(input_grad), Tensor(filter_grad) output : Tensor(input_grad), Tensor(filter_grad)
...@@ -515,7 +489,7 @@ ...@@ -515,7 +489,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv3d_grad_grad backward : conv3d_grad_grad
- backward_api : conv3d_grad_grad - backward_op : conv3d_grad_grad
forward : conv3d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(grad_input), Tensor(grad_filter) forward : conv3d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad) output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
...@@ -527,7 +501,7 @@ ...@@ -527,7 +501,7 @@
use_gpudnn : true use_gpudnn : true
optional : grad_input_grad, grad_filter_grad optional : grad_input_grad, grad_filter_grad
- backward_api : conv3d_transpose_grad - backward_op : conv3d_transpose_grad
forward : conv3d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out) forward : conv3d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(x_grad), Tensor(filter_grad) output : Tensor(x_grad), Tensor(filter_grad)
...@@ -537,7 +511,7 @@ ...@@ -537,7 +511,7 @@
func : conv3d_transpose_grad func : conv3d_transpose_grad
use_gpudnn : true use_gpudnn : true
- backward_api : cos_grad - backward_op : cos_grad
forward : cos (Tensor x) -> Tensor(out) forward : cos (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -548,7 +522,7 @@ ...@@ -548,7 +522,7 @@
func : cos_grad func : cos_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : cosh_grad - backward_op : cosh_grad
forward : cosh (Tensor x) -> Tensor(out) forward : cosh (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -559,7 +533,7 @@ ...@@ -559,7 +533,7 @@
func : cosh_grad func : cosh_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : crop_tensor_grad - backward_op : crop_tensor_grad
forward : crop_tensor (Tensor x, IntArray shape, IntArray offsets) -> Tensor(out) forward : crop_tensor (Tensor x, IntArray shape, IntArray offsets) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray offsets) args : (Tensor x, Tensor out_grad, IntArray offsets)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -569,7 +543,7 @@ ...@@ -569,7 +543,7 @@
func : crop_tensor_grad func : crop_tensor_grad
data_type : x data_type : x
- backward_api : cross_entropy_with_softmax_grad - backward_op : cross_entropy_with_softmax_grad
forward : cross_entropy_with_softmax (Tensor input, Tensor label, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis) -> Tensor(softmax), Tensor(loss) forward : cross_entropy_with_softmax (Tensor input, Tensor label, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis) -> Tensor(softmax), Tensor(loss)
args : (Tensor label, Tensor softmax, Tensor loss_grad, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis) args : (Tensor label, Tensor softmax, Tensor loss_grad, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -580,7 +554,7 @@ ...@@ -580,7 +554,7 @@
data_type : softmax data_type : softmax
inplace : (softmax -> input_grad) inplace : (softmax -> input_grad)
- backward_api : cumprod_grad - backward_op : cumprod_grad
forward : cumprod (Tensor x, int dim) -> Tensor(out) forward : cumprod (Tensor x, int dim) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int dim) args : (Tensor x, Tensor out, Tensor out_grad, int dim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -590,13 +564,13 @@ ...@@ -590,13 +564,13 @@
kernel : kernel :
func : cumprod_grad func : cumprod_grad
- backward_api : cumsum_grad - backward_op : cumsum_grad
forward : cumsum(Tensor x, Scalar axis, bool flatten, bool exclusive, bool reverse) -> Tensor(out) forward : cumsum(Tensor x, Scalar axis, bool flatten, bool exclusive, bool reverse) -> Tensor(out)
args : (Tensor out_grad, Scalar axis, bool flatten, bool exclusive, bool reverse) args : (Tensor out_grad, Scalar axis, bool flatten, bool exclusive, bool reverse)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : cumsum(out_grad, axis, flatten, exclusive, !reverse) invoke : cumsum(out_grad, axis, flatten, exclusive, !reverse)
- backward_api : deformable_conv_grad - backward_op : deformable_conv_grad
forward : deformable_conv(Tensor x, Tensor offset, Tensor filter, Tensor mask, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step) -> Tensor(out) forward : deformable_conv(Tensor x, Tensor offset, Tensor filter, Tensor mask, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step) -> Tensor(out)
args : (Tensor x, Tensor offset, Tensor filter, Tensor mask, Tensor out_grad, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step) args : (Tensor x, Tensor offset, Tensor filter, Tensor mask, Tensor out_grad, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step)
output : Tensor(x_grad), Tensor(offset_grad), Tensor(filter_grad), Tensor(mask_grad) output : Tensor(x_grad), Tensor(offset_grad), Tensor(filter_grad), Tensor(mask_grad)
...@@ -607,7 +581,7 @@ ...@@ -607,7 +581,7 @@
data_type : x data_type : x
optional : mask optional : mask
- backward_api : depthwise_conv2d_grad - backward_op : depthwise_conv2d_grad
forward : depthwise_conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(out) forward : depthwise_conv2d (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(out)
args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) args : (Tensor input, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn)
output : Tensor(input_grad), Tensor(filter_grad) output : Tensor(input_grad), Tensor(filter_grad)
...@@ -620,7 +594,7 @@ ...@@ -620,7 +594,7 @@
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
backward : depthwise_conv2d_grad_grad backward : depthwise_conv2d_grad_grad
- backward_api : depthwise_conv2d_grad_grad - backward_op : depthwise_conv2d_grad_grad
forward : depthwise_conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(grad_input), Tensor(grad_filter) forward : depthwise_conv2d_grad (Tensor input, Tensor filter, Tensor grad_out, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) -> Tensor(grad_input), Tensor(grad_filter)
args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu) args : (Tensor input, Tensor filter, Tensor grad_out, Tensor grad_input_grad, Tensor grad_filter_grad, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu)
output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad) output : Tensor(input_grad), Tensor(filter_grad), Tensor(grad_out_grad)
...@@ -631,7 +605,7 @@ ...@@ -631,7 +605,7 @@
func : depthwise_conv2d_grad_grad func : depthwise_conv2d_grad_grad
optional : grad_input_grad, grad_filter_grad optional : grad_input_grad, grad_filter_grad
- backward_api : depthwise_conv2d_transpose_grad - backward_op : depthwise_conv2d_transpose_grad
forward : depthwise_conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out) forward : depthwise_conv2d_transpose(Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) -> Tensor(out)
args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, Tensor out_grad, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(x_grad), Tensor(filter_grad) output : Tensor(x_grad), Tensor(filter_grad)
...@@ -640,7 +614,7 @@ ...@@ -640,7 +614,7 @@
kernel : kernel :
func : depthwise_conv2d_transpose_grad func : depthwise_conv2d_transpose_grad
- backward_api : det_grad - backward_op : det_grad
forward : det (Tensor x) -> Tensor(out) forward : det (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad) args : (Tensor x, Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -650,7 +624,7 @@ ...@@ -650,7 +624,7 @@
kernel : kernel :
func : determinant_grad func : determinant_grad
- backward_api : divide_double_grad - backward_op : divide_double_grad
forward : divide_grad (Tensor x, Tensor y, Tensor out, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y) forward : divide_grad (Tensor x, Tensor y, Tensor out, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
args : (Tensor y, Tensor out, Tensor grad_x, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1) args : (Tensor y, Tensor out, Tensor grad_x, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)
output : Tensor(y_grad), Tensor(out_grad), Tensor(grad_out_grad) output : Tensor(y_grad), Tensor(out_grad), Tensor(grad_out_grad)
...@@ -663,7 +637,7 @@ ...@@ -663,7 +637,7 @@
optional : grad_x_grad, grad_y_grad optional : grad_x_grad, grad_y_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : divide_grad - backward_op : divide_grad
forward : divide (Tensor x, Tensor y) -> Tensor(out) forward : divide (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -674,7 +648,7 @@ ...@@ -674,7 +648,7 @@
func : divide_grad func : divide_grad
backward : divide_double_grad backward : divide_double_grad
- backward_api : dropout_grad - backward_op : dropout_grad
forward : dropout (Tensor x, Tensor seed_tensor, Scalar p, bool is_test, str mode, int seed, bool fix_seed) -> Tensor(out), Tensor(mask) forward : dropout (Tensor x, Tensor seed_tensor, Scalar p, bool is_test, str mode, int seed, bool fix_seed) -> Tensor(out), Tensor(mask)
args : (Tensor mask, Tensor out_grad, Scalar p, bool is_test, str mode) args : (Tensor mask, Tensor out_grad, Scalar p, bool is_test, str mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -684,7 +658,7 @@ ...@@ -684,7 +658,7 @@
kernel : kernel :
func : dropout_grad func : dropout_grad
- backward_api : eig_grad - backward_op : eig_grad
forward : eig (Tensor x) -> Tensor(out_w), Tensor(out_v) forward : eig (Tensor x) -> Tensor(out_w), Tensor(out_v)
args : (Tensor out_w, Tensor out_v, Tensor out_w_grad, Tensor out_v_grad) args : (Tensor out_w, Tensor out_v, Tensor out_w_grad, Tensor out_v_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -697,7 +671,7 @@ ...@@ -697,7 +671,7 @@
data_transform: data_transform:
skip_transform : out_w, out_w_grad skip_transform : out_w, out_w_grad
- backward_api : eigh_grad - backward_op : eigh_grad
forward : eigh (Tensor x, str uplo) -> Tensor(out_w), Tensor(out_v) forward : eigh (Tensor x, str uplo) -> Tensor(out_w), Tensor(out_v)
args : (Tensor out_w, Tensor out_v, Tensor out_w_grad, Tensor out_v_grad) args : (Tensor out_w, Tensor out_v, Tensor out_w_grad, Tensor out_v_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -710,7 +684,7 @@ ...@@ -710,7 +684,7 @@
data_transform: data_transform:
skip_transform : out_w, out_w_grad skip_transform : out_w, out_w_grad
- backward_api : eigvalsh_grad - backward_op : eigvalsh_grad
forward : eigvalsh (Tensor x, str uplo, bool is_test) -> Tensor(eigenvalues), Tensor(eigenvectors) forward : eigvalsh (Tensor x, str uplo, bool is_test) -> Tensor(eigenvalues), Tensor(eigenvectors)
args : (Tensor eigenvectors, Tensor eigenvalues_grad, str uplo, bool is_test) args : (Tensor eigenvectors, Tensor eigenvalues_grad, str uplo, bool is_test)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -722,7 +696,7 @@ ...@@ -722,7 +696,7 @@
data_transform : data_transform :
skip_transform : eigenvalues_grad skip_transform : eigenvalues_grad
- backward_api : einsum_grad - backward_op : einsum_grad
forward : einsum (Tensor[] x, str equation) -> Tensor(out), Tensor[](inner_cache), Tensor[](x_shape) forward : einsum (Tensor[] x, str equation) -> Tensor(out), Tensor[](inner_cache), Tensor[](x_shape)
args : (Tensor[] x_shape, Tensor[] inner_cache, Tensor out_grad, str equation) args : (Tensor[] x_shape, Tensor[] inner_cache, Tensor out_grad, str equation)
output : Tensor[](x_grad){x.size()} output : Tensor[](x_grad){x.size()}
...@@ -732,7 +706,7 @@ ...@@ -732,7 +706,7 @@
kernel : kernel :
func : einsum_grad func : einsum_grad
- backward_api : elementwise_pow_grad - backward_op : elementwise_pow_grad
forward : elementwise_pow(Tensor x, Tensor y) -> Tensor(out) forward : elementwise_pow(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1) args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -742,7 +716,7 @@ ...@@ -742,7 +716,7 @@
kernel : kernel :
func : elementwise_pow_grad func : elementwise_pow_grad
- backward_api : elu_double_grad - backward_op : elu_double_grad
forward : elu_grad (Tensor x, Tensor out, Tensor grad_out, float alpha)-> Tensor(grad_x) forward : elu_grad (Tensor x, Tensor out, Tensor grad_out, float alpha)-> Tensor(grad_x)
args : (Tensor x, Tensor grad_out, Tensor grad_x_grad, float alpha) args : (Tensor x, Tensor grad_out, Tensor grad_x_grad, float alpha)
output : Tensor(x_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(grad_out_grad)
...@@ -753,7 +727,7 @@ ...@@ -753,7 +727,7 @@
func : elu_double_grad func : elu_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : elu_grad - backward_op : elu_grad
forward : elu (Tensor x, float alpha) -> Tensor(out) forward : elu (Tensor x, float alpha) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, float alpha) args : (Tensor x, Tensor out, Tensor out_grad, float alpha)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -765,13 +739,13 @@ ...@@ -765,13 +739,13 @@
backward : elu_double_grad backward : elu_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : embedding_grad - backward_op : embedding_grad
forward : embedding (Tensor x, Tensor weight, int64_t padding_idx=-1, bool sparse=false) -> Tensor(out) forward : embedding (Tensor x, Tensor weight, int64_t padding_idx=-1, bool sparse=false) -> Tensor(out)
args : (Tensor x, Tensor weight, Tensor out_grad, int64_t padding_idx=-1, bool sparse=false) args : (Tensor x, Tensor weight, Tensor out_grad, int64_t padding_idx=-1, bool sparse=false)
output : Tensor(weight_grad) output : Tensor(weight_grad)
invoke : embedding_grad_impl(x, weight, out_grad, padding_idx, sparse, weight_grad) invoke : embedding_grad_impl(x, weight, out_grad, padding_idx, sparse, weight_grad)
- backward_api : exp_grad - backward_op : exp_grad
forward : exp (Tensor x) -> Tensor(out) forward : exp (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -782,7 +756,7 @@ ...@@ -782,7 +756,7 @@
func : exp_grad func : exp_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : expand_as_grad - backward_op : expand_as_grad
forward : expand_as (Tensor x, Tensor y, int[] target_shape) -> Tensor(out) forward : expand_as (Tensor x, Tensor y, int[] target_shape) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int[] target_shape) args : (Tensor x, Tensor out_grad, int[] target_shape)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -793,7 +767,7 @@ ...@@ -793,7 +767,7 @@
func : expand_as_grad func : expand_as_grad
no_need_buffer : x no_need_buffer : x
- backward_api : expand_double_grad - backward_op : expand_double_grad
forward : expand_grad (Tensor x, Tensor grad_out, IntArray shape) -> Tensor(grad_x) forward : expand_grad (Tensor x, Tensor grad_out, IntArray shape) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray shape) args : (Tensor grad_x_grad, IntArray shape)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -802,7 +776,7 @@ ...@@ -802,7 +776,7 @@
kernel : kernel :
func : expand func : expand
- backward_api : expand_grad - backward_op : expand_grad
forward : expand (Tensor x, IntArray shape) -> Tensor(out) forward : expand (Tensor x, IntArray shape) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray shape) args : (Tensor x, Tensor out_grad, IntArray shape)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -814,7 +788,7 @@ ...@@ -814,7 +788,7 @@
no_need_buffer : x no_need_buffer : x
backward : expand_double_grad backward : expand_double_grad
- backward_api : expm1_grad - backward_op : expm1_grad
forward : expm1 (Tensor x) -> Tensor(out) forward : expm1 (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -825,7 +799,7 @@ ...@@ -825,7 +799,7 @@
func : expm1_grad func : expm1_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : exponential__grad - backward_op : exponential__grad
forward : exponential_ (Tensor x, float lambda) -> Tensor(out) forward : exponential_ (Tensor x, float lambda) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -833,7 +807,7 @@ ...@@ -833,7 +807,7 @@
func : UnchangedInferMeta func : UnchangedInferMeta
invoke : zeros_like(out_grad) invoke : zeros_like(out_grad)
- backward_api : fill_diagonal_grad - backward_op : fill_diagonal_grad
forward : fill_diagonal (Tensor x, float value, int offset, bool wrap) -> Tensor(out) forward : fill_diagonal (Tensor x, float value, int offset, bool wrap) -> Tensor(out)
args : (Tensor out_grad, float value, int offset, bool wrap) args : (Tensor out_grad, float value, int offset, bool wrap)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -842,7 +816,7 @@ ...@@ -842,7 +816,7 @@
kernel : kernel :
func : fill_diagonal_grad func : fill_diagonal_grad
- backward_api : fill_diagonal_tensor_grad - backward_op : fill_diagonal_tensor_grad
forward : fill_diagonal_tensor (Tensor x, Tensor y, int64_t offset, int dim1, int dim2) -> Tensor(out) forward : fill_diagonal_tensor (Tensor x, Tensor y, int64_t offset, int dim1, int dim2) -> Tensor(out)
args : (Tensor out_grad, int64_t offset, int dim1, int dim2) args : (Tensor out_grad, int64_t offset, int dim1, int dim2)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -852,7 +826,7 @@ ...@@ -852,7 +826,7 @@
func : fill_diagonal_tensor_grad func : fill_diagonal_tensor_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : fill_grad - backward_op : fill_grad
forward : fill (Tensor x, Scalar value) -> Tensor(out) forward : fill (Tensor x, Scalar value) -> Tensor(out)
args : (Tensor out_grad, Scalar value) args : (Tensor out_grad, Scalar value)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -863,7 +837,7 @@ ...@@ -863,7 +837,7 @@
func : fill_grad func : fill_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : flatten_grad - backward_op : flatten_grad
forward : flatten(Tensor x, int start_axis, int stop_axis) -> Tensor(out), Tensor(xshape) forward : flatten(Tensor x, int start_axis, int stop_axis) -> Tensor(out), Tensor(xshape)
args : (Tensor xshape, Tensor out_grad) args : (Tensor xshape, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -877,13 +851,13 @@ ...@@ -877,13 +851,13 @@
layout: out_grad layout: out_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : flip_grad - backward_op : flip_grad
forward : flip (Tensor x, int[] axis) -> Tensor(out) forward : flip (Tensor x, int[] axis) -> Tensor(out)
args : (Tensor out_grad, int[] axis) args : (Tensor out_grad, int[] axis)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : flip(out_grad, axis) invoke : flip(out_grad, axis)
- backward_api : floor_grad - backward_op : floor_grad
forward : floor(Tensor x) -> Tensor(out) forward : floor(Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -894,7 +868,7 @@ ...@@ -894,7 +868,7 @@
func : floor_grad func : floor_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : fmax_grad - backward_op : fmax_grad
forward : fmax(Tensor x, Tensor y, int axis) -> Tensor(out) forward : fmax(Tensor x, Tensor y, int axis) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis) args : (Tensor x, Tensor y, Tensor out_grad, int axis)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -904,7 +878,7 @@ ...@@ -904,7 +878,7 @@
kernel : kernel :
func : fmax_grad func : fmax_grad
- backward_api : fmin_grad - backward_op : fmin_grad
forward : fmin(Tensor x, Tensor y, int axis) -> Tensor(out) forward : fmin(Tensor x, Tensor y, int axis) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis) args : (Tensor x, Tensor y, Tensor out_grad, int axis)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -914,7 +888,7 @@ ...@@ -914,7 +888,7 @@
kernel : kernel :
func : fmin_grad func : fmin_grad
- backward_api : frame_grad - backward_op : frame_grad
forward : frame(Tensor x, int frame_length, int hop_length, int axis) -> Tensor(out) forward : frame(Tensor x, int frame_length, int hop_length, int axis) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int frame_length, int hop_length, int axis) args : (Tensor x, Tensor out_grad, int frame_length, int hop_length, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -924,7 +898,7 @@ ...@@ -924,7 +898,7 @@
kernel : kernel :
func : frame_grad func : frame_grad
- backward_api : frobenius_norm_grad - backward_op : frobenius_norm_grad
forward : frobenius_norm(Tensor x, int64_t[] axis, bool keep_dim, bool reduce_all) -> Tensor(out) forward : frobenius_norm(Tensor x, int64_t[] axis, bool keep_dim, bool reduce_all) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] axis, bool keep_dim, bool reduce_all) args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] axis, bool keep_dim, bool reduce_all)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -934,7 +908,7 @@ ...@@ -934,7 +908,7 @@
kernel : kernel :
func : frobenius_norm_grad func : frobenius_norm_grad
- backward_api : gather_grad - backward_op : gather_grad
forward : gather(Tensor x, Tensor index, Scalar axis=0) -> Tensor(out) forward : gather(Tensor x, Tensor index, Scalar axis=0) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad, Scalar axis=0, bool overwrite=false) args : (Tensor x, Tensor index, Tensor out_grad, Scalar axis=0, bool overwrite=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -946,7 +920,7 @@ ...@@ -946,7 +920,7 @@
func : gather_grad func : gather_grad
no_need_buffer : x no_need_buffer : x
- backward_api : gather_nd_grad - backward_op : gather_nd_grad
forward : gather_nd (Tensor x, Tensor index) -> Tensor(out) forward : gather_nd (Tensor x, Tensor index) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad) args : (Tensor x, Tensor index, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -957,7 +931,7 @@ ...@@ -957,7 +931,7 @@
func : gather_nd_grad func : gather_nd_grad
no_need_buffer : x no_need_buffer : x
- backward_api : gelu_grad - backward_op : gelu_grad
forward : gelu(Tensor x, bool approximate) -> Tensor(out) forward : gelu(Tensor x, bool approximate) -> Tensor(out)
args : (Tensor x, Tensor out_grad, bool approximate) args : (Tensor x, Tensor out_grad, bool approximate)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -967,7 +941,7 @@ ...@@ -967,7 +941,7 @@
kernel : kernel :
func : gelu_grad func : gelu_grad
- backward_api : graph_send_recv_grad - backward_op : graph_send_recv_grad
forward : graph_send_recv (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0}) -> Tensor(out), Tensor(dst_count) forward : graph_send_recv (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0}) -> Tensor(out), Tensor(dst_count)
args : (Tensor x, Tensor src_index, Tensor dst_index, Tensor out, Tensor dst_count, Tensor out_grad, str reduce_op = "SUM") args : (Tensor x, Tensor src_index, Tensor dst_index, Tensor out, Tensor dst_count, Tensor out_grad, str reduce_op = "SUM")
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -979,7 +953,7 @@ ...@@ -979,7 +953,7 @@
data_type : out_grad data_type : out_grad
optional: out, dst_count optional: out, dst_count
- backward_api : graph_send_ue_recv_grad - backward_op : graph_send_ue_recv_grad
forward : graph_send_ue_recv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op, str reduce_op, IntArray out_size) -> Tensor(out), Tensor(dst_count) forward : graph_send_ue_recv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op, str reduce_op, IntArray out_size) -> Tensor(out), Tensor(dst_count)
args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out, Tensor dst_count, Tensor out_grad, str message_op, str reduce_op) args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out, Tensor dst_count, Tensor out_grad, str message_op, str reduce_op)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -991,7 +965,7 @@ ...@@ -991,7 +965,7 @@
data_type : out_grad data_type : out_grad
optional: out, dst_count optional: out, dst_count
- backward_api : grid_sample_grad - backward_op : grid_sample_grad
forward : grid_sample (Tensor x, Tensor grid, str mode, str padding_mode, bool align_corners) -> Tensor(out) forward : grid_sample (Tensor x, Tensor grid, str mode, str padding_mode, bool align_corners) -> Tensor(out)
args : (Tensor x, Tensor grid, Tensor out_grad, str mode, str padding_mode, bool align_corners) args : (Tensor x, Tensor grid, Tensor out_grad, str mode, str padding_mode, bool align_corners)
output : Tensor(x_grad), Tensor(grid_grad) output : Tensor(x_grad), Tensor(grid_grad)
...@@ -1002,7 +976,7 @@ ...@@ -1002,7 +976,7 @@
func : grid_sample_grad func : grid_sample_grad
data_type : x data_type : x
- backward_api : group_norm_grad - backward_op : group_norm_grad
forward : group_norm (Tensor x, Tensor scale, Tensor bias, float epsilon, int groups, str data_layout) -> Tensor(y), Tensor(mean), Tensor(variance) forward : group_norm (Tensor x, Tensor scale, Tensor bias, float epsilon, int groups, str data_layout) -> Tensor(y), Tensor(mean), Tensor(variance)
args : (Tensor x, Tensor scale, Tensor bias, Tensor y, Tensor mean, Tensor variance, Tensor y_grad, float epsilon, int groups, str data_layout) args : (Tensor x, Tensor scale, Tensor bias, Tensor y, Tensor mean, Tensor variance, Tensor y_grad, float epsilon, int groups, str data_layout)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
...@@ -1015,7 +989,7 @@ ...@@ -1015,7 +989,7 @@
optional: scale, bias optional: scale, bias
inplace : (y_grad -> x_grad) inplace : (y_grad -> x_grad)
- backward_api : gumbel_softmax_grad - backward_op : gumbel_softmax_grad
forward : gumbel_softmax (Tensor x, float temperature, bool hard, int axis) -> Tensor(out) forward : gumbel_softmax (Tensor x, float temperature, bool hard, int axis) -> Tensor(out)
args : (Tensor out, Tensor out_grad, int axis) args : (Tensor out, Tensor out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1025,7 +999,7 @@ ...@@ -1025,7 +999,7 @@
kernel : kernel :
func : gumbel_softmax_grad func : gumbel_softmax_grad
- backward_api : hard_shrink_grad - backward_op : hard_shrink_grad
forward : hard_shrink (Tensor x, float threshold) -> Tensor(out) forward : hard_shrink (Tensor x, float threshold) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float threshold) args : (Tensor x, Tensor out_grad, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1036,7 +1010,7 @@ ...@@ -1036,7 +1010,7 @@
func : hard_shrink_grad func : hard_shrink_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : hard_sigmoid_grad - backward_op : hard_sigmoid_grad
forward : hard_sigmoid (Tensor x, float slope, float offset) -> Tensor(out) forward : hard_sigmoid (Tensor x, float slope, float offset) -> Tensor(out)
args : (Tensor out, Tensor out_grad, float slope, float offset) args : (Tensor out, Tensor out_grad, float slope, float offset)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1047,7 +1021,7 @@ ...@@ -1047,7 +1021,7 @@
func : hard_sigmoid_grad func : hard_sigmoid_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : hard_swish_grad - backward_op : hard_swish_grad
forward : hard_swish (Tensor x, float threshold = 6.0, float scale = 6.0, float offset = 3.0) -> Tensor(out) forward : hard_swish (Tensor x, float threshold = 6.0, float scale = 6.0, float offset = 3.0) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float threshold, float scale, float offset) args : (Tensor x, Tensor out_grad, float threshold, float scale, float offset)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1058,7 +1032,7 @@ ...@@ -1058,7 +1032,7 @@
func : hard_swish_grad func : hard_swish_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : hierarchical_sigmoid_grad - backward_op : hierarchical_sigmoid_grad
forward : hierarchical_sigmoid (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse) -> Tensor(out), Tensor(pre_out), Tensor(w_out) forward : hierarchical_sigmoid (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse) -> Tensor(out), Tensor(pre_out), Tensor(w_out)
args : (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, Tensor pre_out, Tensor out_grad, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse) args : (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, Tensor pre_out, Tensor out_grad, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse)
output : Tensor(x_grad), Tensor(w_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(w_grad), Tensor(bias_grad)
...@@ -1069,7 +1043,7 @@ ...@@ -1069,7 +1043,7 @@
kernel : kernel :
func : hierarchical_sigmoid_grad func : hierarchical_sigmoid_grad
- backward_api : huber_loss_grad - backward_op : huber_loss_grad
forward : huber_loss (Tensor input, Tensor label, float delta) -> Tensor(out), Tensor(residual) forward : huber_loss (Tensor input, Tensor label, float delta) -> Tensor(out), Tensor(residual)
args : (Tensor residual, Tensor out_grad, float delta) args : (Tensor residual, Tensor out_grad, float delta)
output : Tensor(input_grad), Tensor(label_grad) output : Tensor(input_grad), Tensor(label_grad)
...@@ -1079,13 +1053,13 @@ ...@@ -1079,13 +1053,13 @@
kernel : kernel :
func : huber_loss_grad func : huber_loss_grad
- backward_api : imag_grad - backward_op : imag_grad
forward : imag (Tensor x) -> Tensor(out) forward : imag (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : imag_grad_impl(out_grad, x_grad) invoke : imag_grad_impl(out_grad, x_grad)
- backward_api : index_add_grad - backward_op : index_add_grad
forward : index_add(Tensor x, Tensor index, Tensor add_value, int axis) -> Tensor(out) forward : index_add(Tensor x, Tensor index, Tensor add_value, int axis) -> Tensor(out)
args : (Tensor index, Tensor add_value, Tensor out_grad, int axis) args : (Tensor index, Tensor add_value, Tensor out_grad, int axis)
output : Tensor(x_grad), Tensor(add_value_grad) output : Tensor(x_grad), Tensor(add_value_grad)
...@@ -1096,7 +1070,7 @@ ...@@ -1096,7 +1070,7 @@
data_type : out_grad data_type : out_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : index_sample_grad - backward_op : index_sample_grad
forward : index_sample (Tensor x, Tensor index) -> Tensor(out) forward : index_sample (Tensor x, Tensor index) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad) args : (Tensor x, Tensor index, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1108,7 +1082,7 @@ ...@@ -1108,7 +1082,7 @@
data_type : out_grad data_type : out_grad
no_need_buffer : x no_need_buffer : x
- backward_api : index_select_grad - backward_op : index_select_grad
forward : index_select(Tensor x, Tensor index, int dim) -> Tensor(out) forward : index_select(Tensor x, Tensor index, int dim) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad, int dim) args : (Tensor x, Tensor index, Tensor out_grad, int dim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1120,7 +1094,7 @@ ...@@ -1120,7 +1094,7 @@
data_type : x data_type : x
no_need_buffer : x no_need_buffer : x
- backward_api : instance_norm_double_grad - backward_op : instance_norm_double_grad
forward : instance_norm_grad(Tensor x, Tensor fwd_scale, Tensor saved_mean, Tensor saved_variance, Tensor grad_y, float epsilon) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias) forward : instance_norm_grad(Tensor x, Tensor fwd_scale, Tensor saved_mean, Tensor saved_variance, Tensor grad_y, float epsilon) -> Tensor(grad_x), Tensor(grad_scale), Tensor(grad_bias)
args : (Tensor x, Tensor fwd_scale, Tensor saved_mean, Tensor saved_variance, Tensor grad_y, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float epsilon) args : (Tensor x, Tensor fwd_scale, Tensor saved_mean, Tensor saved_variance, Tensor grad_y, Tensor grad_x_grad, Tensor grad_scale_grad, Tensor grad_bias_grad, float epsilon)
output : Tensor(x_grad), Tensor(fwd_scale_grad), Tensor(grad_y_grad) output : Tensor(x_grad), Tensor(fwd_scale_grad), Tensor(grad_y_grad)
...@@ -1131,7 +1105,7 @@ ...@@ -1131,7 +1105,7 @@
data_type : x data_type : x
optional : fwd_scale, grad_x_grad, grad_scale_grad, grad_bias_grad optional : fwd_scale, grad_x_grad, grad_scale_grad, grad_bias_grad
- backward_api : instance_norm_grad - backward_op : instance_norm_grad
forward : instance_norm(Tensor x, Tensor scale, Tensor bias, float epsilon) -> Tensor(y), Tensor(saved_mean), Tensor(saved_variance) forward : instance_norm(Tensor x, Tensor scale, Tensor bias, float epsilon) -> Tensor(y), Tensor(saved_mean), Tensor(saved_variance)
args : (Tensor x, Tensor scale, Tensor saved_mean, Tensor saved_variance, Tensor y_grad, float epsilon) args : (Tensor x, Tensor scale, Tensor saved_mean, Tensor saved_variance, Tensor y_grad, float epsilon)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
...@@ -1143,7 +1117,7 @@ ...@@ -1143,7 +1117,7 @@
optional : scale optional : scale
backward : instance_norm_double_grad backward : instance_norm_double_grad
- backward_api : inverse_grad - backward_op : inverse_grad
forward : inverse(Tensor x) -> Tensor(out) forward : inverse(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1152,7 +1126,7 @@ ...@@ -1152,7 +1126,7 @@
kernel : kernel :
func : inverse_grad func : inverse_grad
- backward_api : kldiv_loss_grad - backward_op : kldiv_loss_grad
forward : kldiv_loss(Tensor x, Tensor label, str reduction) -> Tensor(out) forward : kldiv_loss(Tensor x, Tensor label, str reduction) -> Tensor(out)
args : (Tensor x, Tensor label, Tensor out_grad, str reduction) args : (Tensor x, Tensor label, Tensor out_grad, str reduction)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1163,7 +1137,7 @@ ...@@ -1163,7 +1137,7 @@
func : kldiv_loss_grad func : kldiv_loss_grad
no_need_buffer : x no_need_buffer : x
- backward_api : kron_grad - backward_op : kron_grad
forward : kron (Tensor x, Tensor y) -> Tensor(out) forward : kron (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1174,7 +1148,7 @@ ...@@ -1174,7 +1148,7 @@
func : kron_grad func : kron_grad
data_type : out_grad data_type : out_grad
- backward_api : kthvalue_grad - backward_op : kthvalue_grad
forward : kthvalue(Tensor x, int k, int axis, bool keepdim) -> Tensor(out), Tensor(indices) forward : kthvalue(Tensor x, int k, int axis, bool keepdim) -> Tensor(out), Tensor(indices)
args : (Tensor x, Tensor indices, Tensor out_grad, int k, int axis, bool keepdim) args : (Tensor x, Tensor indices, Tensor out_grad, int k, int axis, bool keepdim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1184,7 +1158,7 @@ ...@@ -1184,7 +1158,7 @@
kernel : kernel :
func : kthvalue_grad func : kthvalue_grad
- backward_api : label_smooth_grad - backward_op : label_smooth_grad
forward : label_smooth (Tensor label, Tensor prior_dist, float epsilon) -> Tensor(out) forward : label_smooth (Tensor label, Tensor prior_dist, float epsilon) -> Tensor(out)
args : (Tensor out_grad, float epsilon) args : (Tensor out_grad, float epsilon)
output : Tensor(label_grad) output : Tensor(label_grad)
...@@ -1194,7 +1168,7 @@ ...@@ -1194,7 +1168,7 @@
kernel : kernel :
func : label_smooth_grad func : label_smooth_grad
- backward_api : layer_norm_grad - backward_op : layer_norm_grad
forward : layer_norm (Tensor x, Tensor scale, Tensor bias, float epsilon, int begin_norm_axis, bool is_test) -> Tensor(out), Tensor(mean), Tensor(variance) forward : layer_norm (Tensor x, Tensor scale, Tensor bias, float epsilon, int begin_norm_axis, bool is_test) -> Tensor(out), Tensor(mean), Tensor(variance)
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, Tensor out_grad, float epsilon, int begin_norm_axis, bool is_test) args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, Tensor out_grad, float epsilon, int begin_norm_axis, bool is_test)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
...@@ -1207,7 +1181,7 @@ ...@@ -1207,7 +1181,7 @@
no_need_buffer : bias no_need_buffer : bias
optional : scale, bias optional : scale, bias
- backward_api : leaky_relu_double_grad - backward_op : leaky_relu_double_grad
forward : leaky_relu_grad (Tensor x, Tensor grad_out, float alpha) -> Tensor(grad_x) forward : leaky_relu_grad (Tensor x, Tensor grad_out, float alpha) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_x_grad, float alpha) args : (Tensor x, Tensor grad_x_grad, float alpha)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1218,7 +1192,7 @@ ...@@ -1218,7 +1192,7 @@
func : leaky_relu_double_grad func : leaky_relu_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : leaky_relu_grad - backward_op : leaky_relu_grad
forward : leaky_relu (Tensor x, float alpha) -> Tensor(out) forward : leaky_relu (Tensor x, float alpha) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float alpha) args : (Tensor x, Tensor out_grad, float alpha)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1230,7 +1204,7 @@ ...@@ -1230,7 +1204,7 @@
backward : leaky_relu_double_grad backward : leaky_relu_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : lerp_grad - backward_op : lerp_grad
forward : lerp (Tensor x, Tensor y, Tensor weight) -> Tensor(out) forward : lerp (Tensor x, Tensor y, Tensor weight) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor weight, Tensor out, Tensor out_grad) args : (Tensor x, Tensor y, Tensor weight, Tensor out, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1240,7 +1214,7 @@ ...@@ -1240,7 +1214,7 @@
kernel : kernel :
func : lerp_grad func : lerp_grad
- backward_api : linear_interp_grad - backward_op : linear_interp_grad
forward : linear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output) forward : linear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1252,7 +1226,7 @@ ...@@ -1252,7 +1226,7 @@
func : linear_interp_grad func : linear_interp_grad
data_type : output_grad data_type : output_grad
- backward_api : log10_grad - backward_op : log10_grad
forward : log10 (Tensor x) -> Tensor(out) forward : log10 (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1263,7 +1237,7 @@ ...@@ -1263,7 +1237,7 @@
func : log10_grad func : log10_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : log1p_grad - backward_op : log1p_grad
forward : log1p (Tensor x) -> Tensor(out) forward : log1p (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1274,7 +1248,7 @@ ...@@ -1274,7 +1248,7 @@
func : log1p_grad func : log1p_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : log2_grad - backward_op : log2_grad
forward : log2 (Tensor x) -> Tensor(out) forward : log2 (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1285,7 +1259,7 @@ ...@@ -1285,7 +1259,7 @@
func : log2_grad func : log2_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : log_double_grad - backward_op : log_double_grad
forward : log_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x) forward : log_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_out, Tensor grad_x_grad) args : (Tensor x, Tensor grad_out, Tensor grad_x_grad)
output : Tensor(x_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(grad_out_grad)
...@@ -1296,7 +1270,7 @@ ...@@ -1296,7 +1270,7 @@
func : log_double_grad func : log_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : log_grad - backward_op : log_grad
forward : log (Tensor x) -> Tensor(out) forward : log (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1308,7 +1282,7 @@ ...@@ -1308,7 +1282,7 @@
backward : log_double_grad backward : log_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : log_loss_grad - backward_op : log_loss_grad
forward : log_loss (Tensor input, Tensor label, float epsilon) -> Tensor(out) forward : log_loss (Tensor input, Tensor label, float epsilon) -> Tensor(out)
args : (Tensor input, Tensor label, Tensor out_grad, float epsilon) args : (Tensor input, Tensor label, Tensor out_grad, float epsilon)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -1318,7 +1292,7 @@ ...@@ -1318,7 +1292,7 @@
kernel : kernel :
func : log_loss_grad func : log_loss_grad
- backward_api : log_softmax_grad - backward_op : log_softmax_grad
forward : log_softmax(Tensor x, int axis) -> Tensor(out) forward : log_softmax(Tensor x, int axis) -> Tensor(out)
args : (Tensor out, Tensor out_grad, int axis) args : (Tensor out, Tensor out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1328,7 +1302,7 @@ ...@@ -1328,7 +1302,7 @@
kernel : kernel :
func : log_softmax_grad func : log_softmax_grad
- backward_api : logcumsumexp_grad - backward_op : logcumsumexp_grad
forward : logcumsumexp(Tensor x, int axis, bool flatten, bool exclusive, bool reverse) -> Tensor(out) forward : logcumsumexp(Tensor x, int axis, bool flatten, bool exclusive, bool reverse) -> Tensor(out)
infer_meta : infer_meta :
func : UnchangedInferMeta func : UnchangedInferMeta
...@@ -1338,7 +1312,7 @@ ...@@ -1338,7 +1312,7 @@
kernel : kernel :
func : logcumsumexp_grad func : logcumsumexp_grad
- backward_api : logit_grad - backward_op : logit_grad
forward : logit (Tensor x, float eps = 1e-6f) -> Tensor(out) forward : logit (Tensor x, float eps = 1e-6f) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float eps) args : (Tensor x, Tensor out_grad, float eps)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1348,7 +1322,7 @@ ...@@ -1348,7 +1322,7 @@
kernel : kernel :
func : logit_grad func : logit_grad
- backward_api : logsigmoid_grad - backward_op : logsigmoid_grad
forward : logsigmoid (Tensor x) -> Tensor(out) forward : logsigmoid (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1359,7 +1333,7 @@ ...@@ -1359,7 +1333,7 @@
func : logsigmoid_grad func : logsigmoid_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : logsumexp_grad - backward_op : logsumexp_grad
forward : logsumexp(Tensor x, int64_t[] axis, bool keepdim, bool reduce_all) -> Tensor(out) forward : logsumexp(Tensor x, int64_t[] axis, bool keepdim, bool reduce_all) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] axis, bool keepdim, bool reduce_all) args : (Tensor x, Tensor out, Tensor out_grad, int64_t[] axis, bool keepdim, bool reduce_all)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1369,7 +1343,7 @@ ...@@ -1369,7 +1343,7 @@
kernel : kernel :
func : logsumexp_grad func : logsumexp_grad
- backward_api : lu_grad - backward_op : lu_grad
forward : lu (Tensor x, bool pivot) -> Tensor(out), Tensor(pivots), Tensor(infos) forward : lu (Tensor x, bool pivot) -> Tensor(out), Tensor(pivots), Tensor(infos)
args : (Tensor x, Tensor out, Tensor pivots, Tensor out_grad, bool pivot) args : (Tensor x, Tensor out, Tensor pivots, Tensor out_grad, bool pivot)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1378,7 +1352,7 @@ ...@@ -1378,7 +1352,7 @@
kernel : kernel :
func : lu_grad func : lu_grad
- backward_api : lu_unpack_grad - backward_op : lu_unpack_grad
forward : lu_unpack (Tensor x, Tensor pivots, bool unpack_ludata, bool unpack_pivots) -> Tensor(pmat), Tensor(l), Tensor(u) forward : lu_unpack (Tensor x, Tensor pivots, bool unpack_ludata, bool unpack_pivots) -> Tensor(pmat), Tensor(l), Tensor(u)
args : (Tensor x, Tensor pivots, Tensor l, Tensor u, Tensor pmat, Tensor l_grad, Tensor u_grad, bool unpack_ludata, bool unpack_pivots) args : (Tensor x, Tensor pivots, Tensor l, Tensor u, Tensor pmat, Tensor l_grad, Tensor u_grad, bool unpack_ludata, bool unpack_pivots)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1387,7 +1361,7 @@ ...@@ -1387,7 +1361,7 @@
kernel : kernel :
func : lu_unpack_grad func : lu_unpack_grad
- backward_api : margin_cross_entropy_grad - backward_op : margin_cross_entropy_grad
forward : margin_cross_entropy (Tensor logits, Tensor label, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale) -> Tensor(softmax), Tensor(loss) forward : margin_cross_entropy (Tensor logits, Tensor label, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale) -> Tensor(softmax), Tensor(loss)
args : (Tensor logits, Tensor label, Tensor softmax, Tensor loss_grad, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale) args : (Tensor logits, Tensor label, Tensor softmax, Tensor loss_grad, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale)
output : Tensor(logits_grad) output : Tensor(logits_grad)
...@@ -1398,7 +1372,7 @@ ...@@ -1398,7 +1372,7 @@
data_type : softmax data_type : softmax
inplace : (softmax -> logits_grad) inplace : (softmax -> logits_grad)
- backward_api : masked_select_grad - backward_op : masked_select_grad
forward : masked_select (Tensor x, Tensor mask) -> Tensor(out) forward : masked_select (Tensor x, Tensor mask) -> Tensor(out)
args : (Tensor x, Tensor mask, Tensor out_grad) args : (Tensor x, Tensor mask, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1410,7 +1384,7 @@ ...@@ -1410,7 +1384,7 @@
data_type : x data_type : x
no_need_buffer : x no_need_buffer : x
- backward_api : matmul_double_grad - backward_op : matmul_double_grad
forward : matmul_grad (Tensor x, Tensor y, Tensor grad_out, bool transpose_x=false, bool transpose_y=false) -> Tensor(grad_x), Tensor(grad_y) forward : matmul_grad (Tensor x, Tensor y, Tensor grad_out, bool transpose_x=false, bool transpose_y=false) -> Tensor(grad_x), Tensor(grad_y)
args : (Tensor x, Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, bool transpose_x=false, bool transpose_y=false) args : (Tensor x, Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, bool transpose_x=false, bool transpose_y=false)
output : Tensor(x_grad), Tensor(y_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(y_grad), Tensor(grad_out_grad)
...@@ -1422,7 +1396,7 @@ ...@@ -1422,7 +1396,7 @@
backward : matmul_triple_grad backward : matmul_triple_grad
optional : grad_x_grad, grad_y_grad optional : grad_x_grad, grad_y_grad
- backward_api : matmul_grad - backward_op : matmul_grad
forward : matmul (Tensor x, Tensor y, bool transpose_x=false, bool transpose_y=false) -> Tensor(out) forward : matmul (Tensor x, Tensor y, bool transpose_x=false, bool transpose_y=false) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, bool transpose_x=false, bool transpose_y=false) args : (Tensor x, Tensor y, Tensor out_grad, bool transpose_x=false, bool transpose_y=false)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1433,7 +1407,7 @@ ...@@ -1433,7 +1407,7 @@
func : matmul_grad func : matmul_grad
backward : matmul_double_grad backward : matmul_double_grad
- backward_api : matmul_triple_grad - backward_op : matmul_triple_grad
forward : matmul_double_grad (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, bool transpose_x=false, bool transpose_y=false) -> Tensor(grad_x), Tensor(grad_y), Tensor(grad_grad_out) forward : matmul_double_grad (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, bool transpose_x=false, bool transpose_y=false) -> Tensor(grad_x), Tensor(grad_y), Tensor(grad_grad_out)
args : (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, Tensor grad_x_grad, Tensor grad_y_grad, Tensor grad_grad_out_grad, bool transpose_x=false, bool transpose_y=false) args : (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, Tensor grad_x_grad, Tensor grad_y_grad, Tensor grad_grad_out_grad, bool transpose_x=false, bool transpose_y=false)
output : Tensor(x_grad), Tensor(y_grad), Tensor(fwd_grad_out_grad), Tensor(fwd_grad_grad_x_grad), Tensor(fwd_grad_grad_y_grad) output : Tensor(x_grad), Tensor(y_grad), Tensor(fwd_grad_out_grad), Tensor(fwd_grad_grad_x_grad), Tensor(fwd_grad_grad_y_grad)
...@@ -1444,7 +1418,7 @@ ...@@ -1444,7 +1418,7 @@
func : matmul_triple_grad func : matmul_triple_grad
optional : grad_x_grad, grad_y_grad, grad_grad_out_grad optional : grad_x_grad, grad_y_grad, grad_grad_out_grad
- backward_api : matrix_power_grad - backward_op : matrix_power_grad
forward : matrix_power (Tensor x, int n) -> Tensor(out) forward : matrix_power (Tensor x, int n) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int n) args : (Tensor x, Tensor out, Tensor out_grad, int n)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1454,7 +1428,7 @@ ...@@ -1454,7 +1428,7 @@
kernel : kernel :
func : matrix_power_grad func : matrix_power_grad
- backward_api : max_grad - backward_op : max_grad
forward: max (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out) forward: max (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false) args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1464,7 +1438,7 @@ ...@@ -1464,7 +1438,7 @@
kernel : kernel :
func : max_grad func : max_grad
- backward_api : max_pool2d_with_index_grad - backward_op : max_pool2d_with_index_grad
forward : max_pool2d_with_index(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) -> Tensor(out), Tensor(mask) forward : max_pool2d_with_index(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) -> Tensor(out), Tensor(mask)
args : (Tensor x, Tensor mask, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) args : (Tensor x, Tensor mask, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1473,7 +1447,7 @@ ...@@ -1473,7 +1447,7 @@
kernel : kernel :
func : max_pool2d_with_index_grad func : max_pool2d_with_index_grad
- backward_api : max_pool3d_with_index_grad - backward_op : max_pool3d_with_index_grad
forward : max_pool3d_with_index(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) -> Tensor(out), Tensor(mask) forward : max_pool3d_with_index(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) -> Tensor(out), Tensor(mask)
args : (Tensor x, Tensor mask, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) args : (Tensor x, Tensor mask, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1482,7 +1456,7 @@ ...@@ -1482,7 +1456,7 @@
kernel : kernel :
func : max_pool3d_with_index_grad func : max_pool3d_with_index_grad
- backward_api : maximum_grad - backward_op : maximum_grad
forward : maximum(Tensor x, Tensor y) -> Tensor(out) forward : maximum(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1) args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1492,7 +1466,7 @@ ...@@ -1492,7 +1466,7 @@
kernel : kernel :
func : maximum_grad func : maximum_grad
- backward_api : maxout_grad - backward_op : maxout_grad
forward : maxout(Tensor x, int groups, int axis) -> Tensor(out) forward : maxout(Tensor x, int groups, int axis) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int groups, int axis) args : (Tensor x, Tensor out, Tensor out_grad, int groups, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1502,7 +1476,7 @@ ...@@ -1502,7 +1476,7 @@
kernel : kernel :
func : maxout_grad func : maxout_grad
- backward_api : mean_all_grad - backward_op : mean_all_grad
forward : mean_all(Tensor x) -> Tensor(out) forward : mean_all(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1512,13 +1486,13 @@ ...@@ -1512,13 +1486,13 @@
kernel : kernel :
func : mean_all_grad func : mean_all_grad
- backward_api : mean_double_grad - backward_op : mean_double_grad
forward: mean_grad (Tensor x, Tensor grad_out, IntArray dims={}, bool keep_dim=false, bool reduce_all = false) -> Tensor(grad_x) forward: mean_grad (Tensor x, Tensor grad_out, IntArray dims={}, bool keep_dim=false, bool reduce_all = false) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray dims={}, bool keep_dim=false) args : (Tensor grad_x_grad, IntArray dims={}, bool keep_dim=false)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
invoke : mean(grad_x_grad, dims, keep_dim) invoke : mean(grad_x_grad, dims, keep_dim)
- backward_api : mean_grad - backward_op : mean_grad
forward: mean (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out) forward: mean (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false) args : (Tensor x, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1530,7 +1504,7 @@ ...@@ -1530,7 +1504,7 @@
backward : mean_double_grad backward : mean_double_grad
no_need_buffer : x no_need_buffer : x
- backward_api : meshgrid_grad - backward_op : meshgrid_grad
forward : meshgrid (Tensor[] inputs) -> Tensor[](outputs) forward : meshgrid (Tensor[] inputs) -> Tensor[](outputs)
args : (Tensor[] inputs, Tensor[] outputs_grad) args : (Tensor[] inputs, Tensor[] outputs_grad)
output : Tensor[](inputs_grad){inputs.size()} output : Tensor[](inputs_grad){inputs.size()}
...@@ -1539,7 +1513,7 @@ ...@@ -1539,7 +1513,7 @@
kernel : kernel :
func : meshgrid_grad func : meshgrid_grad
- backward_api : min_grad - backward_op : min_grad
forward: min (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out) forward: min (Tensor x, IntArray dims={}, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false) args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims={}, bool keep_dim=false, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1549,7 +1523,7 @@ ...@@ -1549,7 +1523,7 @@
kernel : kernel :
func : min_grad func : min_grad
- backward_api : minimum_grad - backward_op : minimum_grad
forward : minimum(Tensor x, Tensor y) -> Tensor(out) forward : minimum(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1) args : (Tensor x, Tensor y, Tensor out_grad, int axis=-1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1559,7 +1533,7 @@ ...@@ -1559,7 +1533,7 @@
kernel : kernel :
func : minimum_grad func : minimum_grad
- backward_api : mish_grad - backward_op : mish_grad
forward : mish (Tensor x, float threshold) -> Tensor(out) forward : mish (Tensor x, float threshold) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float threshold) args : (Tensor x, Tensor out_grad, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1570,7 +1544,7 @@ ...@@ -1570,7 +1544,7 @@
func : mish_grad func : mish_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : mode_grad - backward_op : mode_grad
forward : mode(Tensor x, int axis, bool keepdim) -> Tensor(out), Tensor(indices) forward : mode(Tensor x, int axis, bool keepdim) -> Tensor(out), Tensor(indices)
args : (Tensor x, Tensor indices, Tensor out_grad, int axis, bool keepdim) args : (Tensor x, Tensor indices, Tensor out_grad, int axis, bool keepdim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1580,7 +1554,7 @@ ...@@ -1580,7 +1554,7 @@
kernel : kernel :
func : mode_grad func : mode_grad
- backward_api : multi_dot_grad - backward_op : multi_dot_grad
forward : multi_dot (Tensor[] x) -> Tensor(out) forward : multi_dot (Tensor[] x) -> Tensor(out)
args : (Tensor[] x, Tensor out_grad) args : (Tensor[] x, Tensor out_grad)
output : Tensor[](x_grad) {x.size()} output : Tensor[](x_grad) {x.size()}
...@@ -1589,7 +1563,7 @@ ...@@ -1589,7 +1563,7 @@
kernel : kernel :
func : multi_dot_grad func : multi_dot_grad
- backward_api : multiplex_grad - backward_op : multiplex_grad
forward : multiplex (Tensor[] ins, Tensor ids) -> Tensor(out) forward : multiplex (Tensor[] ins, Tensor ids) -> Tensor(out)
args : (Tensor[] ins, Tensor ids, Tensor out_grad) args : (Tensor[] ins, Tensor ids, Tensor out_grad)
output : Tensor[](ins_grad){ins.size()} output : Tensor[](ins_grad){ins.size()}
...@@ -1600,7 +1574,7 @@ ...@@ -1600,7 +1574,7 @@
func : multiplex_grad func : multiplex_grad
param : [ids, out_grad] param : [ids, out_grad]
- backward_api : multiply_double_grad - backward_op : multiply_double_grad
forward : multiply_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y) forward : multiply_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
args : (Tensor x, Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(y_grad), Tensor(grad_out_grad)
...@@ -1613,7 +1587,7 @@ ...@@ -1613,7 +1587,7 @@
backward : multiply_triple_grad backward : multiply_triple_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : multiply_grad - backward_op : multiply_grad
forward : multiply (Tensor x, Tensor y) -> Tensor(out) forward : multiply (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -1624,7 +1598,7 @@ ...@@ -1624,7 +1598,7 @@
func : multiply_grad func : multiply_grad
backward : multiply_double_grad backward : multiply_double_grad
- backward_api : multiply_triple_grad - backward_op : multiply_triple_grad
forward : multiply_double_grad (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, int aixs = -1) -> Tensor(grad_x), Tensor(grad_y), Tensor(grad_grad_out) forward : multiply_double_grad (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, int aixs = -1) -> Tensor(grad_x), Tensor(grad_y), Tensor(grad_grad_out)
args : (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, Tensor grad_x_grad, Tensor grad_y_grad, Tensor grad_grad_out_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor fwd_grad_out, Tensor fwd_grad_grad_x, Tensor fwd_grad_grad_y, Tensor grad_x_grad, Tensor grad_y_grad, Tensor grad_grad_out_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad), Tensor(fwd_grad_out_grad), Tensor(fwd_grad_grad_x_grad), Tensor(fwd_grad_grad_y_grad) output : Tensor(x_grad), Tensor(y_grad), Tensor(fwd_grad_out_grad), Tensor(fwd_grad_grad_x_grad), Tensor(fwd_grad_grad_y_grad)
...@@ -1635,7 +1609,7 @@ ...@@ -1635,7 +1609,7 @@
func : multiply_triple_grad func : multiply_triple_grad
optional : fwd_grad_grad_x, fwd_grad_grad_y, grad_grad_out_grad optional : fwd_grad_grad_x, fwd_grad_grad_y, grad_grad_out_grad
- backward_api : nearest_interp_grad - backward_op : nearest_interp_grad
forward : nearest_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output) forward : nearest_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1647,7 +1621,7 @@ ...@@ -1647,7 +1621,7 @@
func : nearest_interp_grad func : nearest_interp_grad
data_type : output_grad data_type : output_grad
- backward_api : nll_loss_grad - backward_op : nll_loss_grad
forward : nll_loss (Tensor input, Tensor label, Tensor weight, int64_t ignore_index, str reduction) -> Tensor(out), Tensor(total_weight) forward : nll_loss (Tensor input, Tensor label, Tensor weight, int64_t ignore_index, str reduction) -> Tensor(out), Tensor(total_weight)
args : (Tensor input, Tensor label, Tensor weight, Tensor total_weight, Tensor out_grad, int64_t ignore_index, str reduction) args : (Tensor input, Tensor label, Tensor weight, Tensor total_weight, Tensor out_grad, int64_t ignore_index, str reduction)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -1658,7 +1632,7 @@ ...@@ -1658,7 +1632,7 @@
data_type : input data_type : input
optional : weight optional : weight
- backward_api : norm_grad - backward_op : norm_grad
forward : norm (Tensor x, int axis, float epsilon, bool is_test) -> Tensor(out), Tensor(norm) forward : norm (Tensor x, int axis, float epsilon, bool is_test) -> Tensor(out), Tensor(norm)
args : (Tensor x, Tensor norm, Tensor out_grad, int axis, float epsilon, bool is_test) args : (Tensor x, Tensor norm, Tensor out_grad, int axis, float epsilon, bool is_test)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1668,7 +1642,7 @@ ...@@ -1668,7 +1642,7 @@
kernel : kernel :
func : norm_grad func : norm_grad
- backward_api : overlap_add_grad - backward_op : overlap_add_grad
forward : overlap_add(Tensor x, int hop_length, int axis) -> Tensor(out) forward : overlap_add(Tensor x, int hop_length, int axis) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int hop_length, int axis) args : (Tensor x, Tensor out_grad, int hop_length, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1678,7 +1652,7 @@ ...@@ -1678,7 +1652,7 @@
func : overlap_add_grad func : overlap_add_grad
data_type : x data_type : x
- backward_api : p_norm_grad - backward_op : p_norm_grad
forward : p_norm(Tensor x, float porder, int axis, float epsilon, bool keepdim, bool asvector=false) -> Tensor(out) forward : p_norm(Tensor x, float porder, int axis, float epsilon, bool keepdim, bool asvector=false) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, float porder, int axis, float epsilon, bool keepdim, bool asvector) args : (Tensor x, Tensor out, Tensor out_grad, float porder, int axis, float epsilon, bool keepdim, bool asvector)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1688,7 +1662,7 @@ ...@@ -1688,7 +1662,7 @@
kernel : kernel :
func : p_norm_grad func : p_norm_grad
- backward_api : pad3d_double_grad - backward_op : pad3d_double_grad
forward : pad3d_grad(Tensor x, Tensor grad_out, IntArray paddings, str mode, float pad_value, str data_format) -> Tensor(grad_x) forward : pad3d_grad(Tensor x, Tensor grad_out, IntArray paddings, str mode, float pad_value, str data_format) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray paddings, str mode, float pad_value, str data_format) args : (Tensor grad_x_grad, IntArray paddings, str mode, float pad_value, str data_format)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1697,7 +1671,7 @@ ...@@ -1697,7 +1671,7 @@
kernel : kernel :
func : pad3d func : pad3d
- backward_api : pad3d_grad - backward_op : pad3d_grad
forward : pad3d(Tensor x, IntArray paddings, str mode, float pad_value, str data_format) -> Tensor(out) forward : pad3d(Tensor x, IntArray paddings, str mode, float pad_value, str data_format) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray paddings, str mode, float pad_value, str data_format) args : (Tensor x, Tensor out_grad, IntArray paddings, str mode, float pad_value, str data_format)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1709,7 +1683,7 @@ ...@@ -1709,7 +1683,7 @@
no_need_buffer : x no_need_buffer : x
backward : pad3d_double_grad backward : pad3d_double_grad
- backward_api : pad_double_grad - backward_op : pad_double_grad
forward : pad_grad(Tensor x, Tensor grad_out, int[] paddings, Scalar pad_value) -> Tensor(grad_x) forward : pad_grad(Tensor x, Tensor grad_out, int[] paddings, Scalar pad_value) -> Tensor(grad_x)
args : (Tensor grad_x_grad, int[] paddings, Scalar pad_value) args : (Tensor grad_x_grad, int[] paddings, Scalar pad_value)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1718,7 +1692,7 @@ ...@@ -1718,7 +1692,7 @@
kernel : kernel :
func : pad func : pad
- backward_api : pad_grad - backward_op : pad_grad
forward : pad(Tensor x, int[] paddings, Scalar pad_value) -> Tensor(out) forward : pad(Tensor x, int[] paddings, Scalar pad_value) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int[] paddings, Scalar pad_value) args : (Tensor x, Tensor out_grad, int[] paddings, Scalar pad_value)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1731,7 +1705,7 @@ ...@@ -1731,7 +1705,7 @@
no_need_buffer : x no_need_buffer : x
backward : pad_double_grad backward : pad_double_grad
- backward_api : pixel_shuffle_grad - backward_op : pixel_shuffle_grad
forward : pixel_shuffle (Tensor x, int upscale_factor, str data_format) -> Tensor(out) forward : pixel_shuffle (Tensor x, int upscale_factor, str data_format) -> Tensor(out)
args : (Tensor out_grad, int upscale_factor, str data_format) args : (Tensor out_grad, int upscale_factor, str data_format)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1740,7 +1714,7 @@ ...@@ -1740,7 +1714,7 @@
kernel : kernel :
func : pixel_shuffle_grad func : pixel_shuffle_grad
- backward_api : pool2d_double_grad - backward_op : pool2d_double_grad
forward : pool2d_grad(Tensor x, Tensor out, Tensor grad_out, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(grad_x) forward : pool2d_grad(Tensor x, Tensor out, Tensor grad_out, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) args : (Tensor grad_x_grad, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1752,7 +1726,7 @@ ...@@ -1752,7 +1726,7 @@
param : [grad_x_grad, kernel_size, strides, paddings, ceil_mode, exclusive, data_format, pooling_type, global_pooling, adaptive, padding_algorithm] param : [grad_x_grad, kernel_size, strides, paddings, ceil_mode, exclusive, data_format, pooling_type, global_pooling, adaptive, padding_algorithm]
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
- backward_api : pool2d_grad - backward_op : pool2d_grad
forward : pool2d(Tensor x, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(out) forward : pool2d(Tensor x, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) args : (Tensor x, Tensor out, Tensor out_grad, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1765,7 +1739,7 @@ ...@@ -1765,7 +1739,7 @@
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
backward : pool2d_double_grad backward : pool2d_double_grad
- backward_api : pool3d_grad - backward_op : pool3d_grad
forward : pool3d(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(out) forward : pool3d(Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) args : (Tensor x, Tensor out, Tensor out_grad, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1777,7 +1751,7 @@ ...@@ -1777,7 +1751,7 @@
param : [x, out, out_grad, kernel_size, strides, paddings, ceil_mode, exclusive, data_format, pooling_type, global_pooling, adaptive, padding_algorithm] param : [x, out, out_grad, kernel_size, strides, paddings, ceil_mode, exclusive, data_format, pooling_type, global_pooling, adaptive, padding_algorithm]
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
- backward_api : pow_grad - backward_op : pow_grad
forward : pow(Tensor x, Scalar s) -> Tensor(out) forward : pow(Tensor x, Scalar s) -> Tensor(out)
args : (Tensor x, Tensor out_grad, Scalar s=-1) args : (Tensor x, Tensor out_grad, Scalar s=-1)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1788,7 +1762,7 @@ ...@@ -1788,7 +1762,7 @@
func : pow_grad func : pow_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : prelu_grad - backward_op : prelu_grad
forward : prelu(Tensor x, Tensor alpha, str data_format, str mode) -> Tensor(out) forward : prelu(Tensor x, Tensor alpha, str data_format, str mode) -> Tensor(out)
args : (Tensor x, Tensor alpha, Tensor out_grad, str data_format, str mode) args : (Tensor x, Tensor alpha, Tensor out_grad, str data_format, str mode)
output : Tensor(x_grad), Tensor(alpha_grad) output : Tensor(x_grad), Tensor(alpha_grad)
...@@ -1798,7 +1772,7 @@ ...@@ -1798,7 +1772,7 @@
kernel : kernel :
func : prelu_grad func : prelu_grad
- backward_api : psroi_pool_grad - backward_op : psroi_pool_grad
forward : psroi_pool (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, int output_channels, float spatial_scale) -> Tensor(out) forward : psroi_pool (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, int output_channels, float spatial_scale) -> Tensor(out)
args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor out_grad, int pooled_height, int pooled_width, int output_channels, float spatial_scale) args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor out_grad, int pooled_height, int pooled_width, int output_channels, float spatial_scale)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1811,7 +1785,7 @@ ...@@ -1811,7 +1785,7 @@
optional : boxes_num optional : boxes_num
# output is optional # output is optional
- backward_api : put_along_axis_grad - backward_op : put_along_axis_grad
forward : put_along_axis (Tensor x, Tensor index, Tensor value, int axis, str reduce) -> Tensor(out) forward : put_along_axis (Tensor x, Tensor index, Tensor value, int axis, str reduce) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad, int axis, str reduce) args : (Tensor x, Tensor index, Tensor out_grad, int axis, str reduce)
output : Tensor(x_grad), Tensor(value_grad) output : Tensor(x_grad), Tensor(value_grad)
...@@ -1821,7 +1795,7 @@ ...@@ -1821,7 +1795,7 @@
kernel : kernel :
func : put_along_axis_grad func : put_along_axis_grad
- backward_api : qr_grad - backward_op : qr_grad
forward : qr (Tensor x, str mode) -> Tensor(q), Tensor(r) forward : qr (Tensor x, str mode) -> Tensor(q), Tensor(r)
args : (Tensor x, Tensor q, Tensor r, Tensor q_grad, Tensor r_grad, str mode) args : (Tensor x, Tensor q, Tensor r, Tensor q_grad, Tensor r_grad, str mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1831,13 +1805,13 @@ ...@@ -1831,13 +1805,13 @@
kernel : kernel :
func : qr_grad func : qr_grad
- backward_api : real_grad - backward_op : real_grad
forward : real (Tensor x) -> Tensor(out) forward : real (Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : real_grad_impl(out_grad, x_grad) invoke : real_grad_impl(out_grad, x_grad)
- backward_api : reciprocal_grad - backward_op : reciprocal_grad
forward : reciprocal (Tensor x) -> Tensor(out) forward : reciprocal (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1848,7 +1822,7 @@ ...@@ -1848,7 +1822,7 @@
func : reciprocal_grad func : reciprocal_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : reduce_prod_grad - backward_op : reduce_prod_grad
forward : reduce_prod (Tensor x, IntArray dims, bool keep_dim, bool reduce_all) -> Tensor(out) forward : reduce_prod (Tensor x, IntArray dims, bool keep_dim, bool reduce_all) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims, bool keep_dim, bool reduce_all) args : (Tensor x, Tensor out, Tensor out_grad, IntArray dims, bool keep_dim, bool reduce_all)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1858,7 +1832,7 @@ ...@@ -1858,7 +1832,7 @@
kernel : kernel :
func : prod_grad func : prod_grad
- backward_api : relu6_grad - backward_op : relu6_grad
forward : relu6 (Tensor x, float threshold) -> Tensor(out) forward : relu6 (Tensor x, float threshold) -> Tensor(out)
args : (Tensor out, Tensor out_grad, float threshold) args : (Tensor out, Tensor out_grad, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1869,7 +1843,7 @@ ...@@ -1869,7 +1843,7 @@
func : relu6_grad func : relu6_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : relu_double_grad - backward_op : relu_double_grad
forward : relu_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x) forward : relu_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor out, Tensor grad_x_grad) args : (Tensor out, Tensor grad_x_grad)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1880,7 +1854,7 @@ ...@@ -1880,7 +1854,7 @@
func : relu_double_grad func : relu_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : relu_grad - backward_op : relu_grad
forward : relu (Tensor x) -> Tensor(out) forward : relu (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1892,7 +1866,7 @@ ...@@ -1892,7 +1866,7 @@
backward: relu_double_grad backward: relu_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : renorm_grad - backward_op : renorm_grad
forward : renorm (Tensor x, float p, int axis, float max_norm) -> Tensor(out) forward : renorm (Tensor x, float p, int axis, float max_norm) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float p, int axis, float max_norm) args : (Tensor x, Tensor out_grad, float p, int axis, float max_norm)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1902,7 +1876,7 @@ ...@@ -1902,7 +1876,7 @@
kernel : kernel :
func : renorm_grad func : renorm_grad
- backward_api : repeat_interleave_grad - backward_op : repeat_interleave_grad
forward : repeat_interleave(Tensor x, int repeats, int dim) -> Tensor(out) forward : repeat_interleave(Tensor x, int repeats, int dim) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int repeats, int dim) args : (Tensor x, Tensor out_grad, int repeats, int dim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1912,7 +1886,7 @@ ...@@ -1912,7 +1886,7 @@
kernel : kernel :
func : repeat_interleave_grad func : repeat_interleave_grad
- backward_api : repeat_interleave_with_tensor_index_grad - backward_op : repeat_interleave_with_tensor_index_grad
forward : repeat_interleave_with_tensor_index(Tensor x, Tensor repeats, int dim) -> Tensor(out) forward : repeat_interleave_with_tensor_index(Tensor x, Tensor repeats, int dim) -> Tensor(out)
args : (Tensor x, Tensor repeats, Tensor out_grad, int dim) args : (Tensor x, Tensor repeats, Tensor out_grad, int dim)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1923,7 +1897,7 @@ ...@@ -1923,7 +1897,7 @@
func : repeat_interleave_with_tensor_index_grad func : repeat_interleave_with_tensor_index_grad
data_type : x data_type : x
- backward_api : reshape_double_grad - backward_op : reshape_double_grad
forward : reshape_grad (Tensor xshape, Tensor grad_out) -> Tensor(grad_x) forward : reshape_grad (Tensor xshape, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor grad_out, Tensor grad_x_grad) args : (Tensor grad_out, Tensor grad_x_grad)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -1935,7 +1909,7 @@ ...@@ -1935,7 +1909,7 @@
no_need_buffer : grad_out no_need_buffer : grad_out
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : reshape_grad - backward_op : reshape_grad
forward : reshape (Tensor x, IntArray shape) -> Tensor(out), Tensor(xshape) forward : reshape (Tensor x, IntArray shape) -> Tensor(out), Tensor(xshape)
args : (Tensor xshape, Tensor out_grad) args : (Tensor xshape, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1951,7 +1925,7 @@ ...@@ -1951,7 +1925,7 @@
backward : reshape_double_grad backward : reshape_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : reverse_array_grad - backward_op : reverse_array_grad
forward : reverse_array (Tensor[] x, IntArray axis) -> Tensor[](out) forward : reverse_array (Tensor[] x, IntArray axis) -> Tensor[](out)
args : (Tensor[] out_grad, IntArray axis) args : (Tensor[] out_grad, IntArray axis)
output : Tensor[](x_grad){out_grad.size()} output : Tensor[](x_grad){out_grad.size()}
...@@ -1960,13 +1934,13 @@ ...@@ -1960,13 +1934,13 @@
kernel : kernel :
func : reverse func : reverse
- backward_api : reverse_grad - backward_op : reverse_grad
forward : reverse (Tensor x, IntArray axis) -> Tensor(out) forward : reverse (Tensor x, IntArray axis) -> Tensor(out)
args : (Tensor out_grad, IntArray axis) args : (Tensor out_grad, IntArray axis)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : reverse(out_grad, axis) invoke : reverse(out_grad, axis)
- backward_api : roi_align_grad - backward_op : roi_align_grad
forward : roi_align (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned) -> Tensor(out) forward : roi_align (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned) -> Tensor(out)
args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor out_grad, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned) args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor out_grad, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1979,7 +1953,7 @@ ...@@ -1979,7 +1953,7 @@
no_need_buffer : x no_need_buffer : x
optional : boxes_num optional : boxes_num
- backward_api : roi_pool_grad - backward_op : roi_pool_grad
forward : roi_pool (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale) -> Tensor(out), Tensor(arg_max) forward : roi_pool (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale) -> Tensor(out), Tensor(arg_max)
args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor arg_max, Tensor out_grad, int pooled_height, int pooled_width, float spatial_scale) args : (Tensor x, Tensor boxes, Tensor boxes_num, Tensor arg_max, Tensor out_grad, int pooled_height, int pooled_width, float spatial_scale)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -1991,7 +1965,7 @@ ...@@ -1991,7 +1965,7 @@
data_type : x data_type : x
optional : boxes_num optional : boxes_num
- backward_api : roll_grad - backward_op : roll_grad
forward : roll(Tensor x, IntArray shifts, int64_t[] axis) -> Tensor(out) forward : roll(Tensor x, IntArray shifts, int64_t[] axis) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray shifts, int64_t[] axis) args : (Tensor x, Tensor out_grad, IntArray shifts, int64_t[] axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2003,7 +1977,7 @@ ...@@ -2003,7 +1977,7 @@
data_type : x data_type : x
no_need_buffer : x no_need_buffer : x
- backward_api : round_grad - backward_op : round_grad
forward : round(Tensor x) -> Tensor(out) forward : round(Tensor x) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2014,7 +1988,7 @@ ...@@ -2014,7 +1988,7 @@
func : round_grad func : round_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : rsqrt_double_grad - backward_op : rsqrt_double_grad
forward : rsqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x) forward : rsqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor out, Tensor grad_x, Tensor grad_x_grad) args : (Tensor out, Tensor grad_x, Tensor grad_x_grad)
output : Tensor(out_grad), Tensor(grad_out_grad) output : Tensor(out_grad), Tensor(grad_out_grad)
...@@ -2025,7 +1999,7 @@ ...@@ -2025,7 +1999,7 @@
func : rsqrt_double_grad func : rsqrt_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : rsqrt_grad - backward_op : rsqrt_grad
forward : rsqrt (Tensor x) -> Tensor(out) forward : rsqrt (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2037,13 +2011,13 @@ ...@@ -2037,13 +2011,13 @@
backward : rsqrt_double_grad backward : rsqrt_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : scale_grad - backward_op : scale_grad
forward : scale (Tensor x, Scalar scale, float bias, bool bias_after_scale) -> Tensor(out) forward : scale (Tensor x, Scalar scale, float bias, bool bias_after_scale) -> Tensor(out)
args : (Tensor out_grad, Scalar scale=1.0, bool bias_after_scale=true) args : (Tensor out_grad, Scalar scale=1.0, bool bias_after_scale=true)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : scale(out_grad, scale, 0.0, bias_after_scale) invoke : scale(out_grad, scale, 0.0, bias_after_scale)
- backward_api : scatter_grad - backward_op : scatter_grad
forward : scatter (Tensor x, Tensor index, Tensor updates, bool overwrite) -> Tensor(out) forward : scatter (Tensor x, Tensor index, Tensor updates, bool overwrite) -> Tensor(out)
args : (Tensor index, Tensor updates, Tensor out_grad, bool overwrite) args : (Tensor index, Tensor updates, Tensor out_grad, bool overwrite)
output : Tensor(x_grad), Tensor(updates_grad) output : Tensor(x_grad), Tensor(updates_grad)
...@@ -2054,7 +2028,7 @@ ...@@ -2054,7 +2028,7 @@
func : scatter_grad func : scatter_grad
no_need_buffer : updates no_need_buffer : updates
- backward_api : scatter_nd_add_grad - backward_op : scatter_nd_add_grad
forward : scatter_nd_add (Tensor x, Tensor index, Tensor updates) -> Tensor(out) forward : scatter_nd_add (Tensor x, Tensor index, Tensor updates) -> Tensor(out)
args : (Tensor index, Tensor updates, Tensor out_grad) args : (Tensor index, Tensor updates, Tensor out_grad)
output : Tensor(x_grad), Tensor(updates_grad) output : Tensor(x_grad), Tensor(updates_grad)
...@@ -2065,7 +2039,7 @@ ...@@ -2065,7 +2039,7 @@
func : scatter_nd_add_grad func : scatter_nd_add_grad
no_need_buffer : updates no_need_buffer : updates
- backward_api : segment_pool_grad - backward_op : segment_pool_grad
forward : segment_pool (Tensor x, Tensor segment_ids, str pooltype) -> Tensor(out), Tensor(summed_ids) forward : segment_pool (Tensor x, Tensor segment_ids, str pooltype) -> Tensor(out), Tensor(summed_ids)
args : (Tensor x, Tensor segment_ids, Tensor out, Tensor summed_ids, Tensor out_grad, str pooltype) args : (Tensor x, Tensor segment_ids, Tensor out, Tensor summed_ids, Tensor out_grad, str pooltype)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2077,7 +2051,7 @@ ...@@ -2077,7 +2051,7 @@
data_type : x data_type : x
optional : summed_ids optional : summed_ids
- backward_api : selu_grad - backward_op : selu_grad
forward : selu (Tensor x, float scale, float alpha) -> Tensor(out) forward : selu (Tensor x, float scale, float alpha) -> Tensor(out)
args : (Tensor out, Tensor out_grad, float scale, float alpha) args : (Tensor out, Tensor out_grad, float scale, float alpha)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2087,7 +2061,7 @@ ...@@ -2087,7 +2061,7 @@
kernel : kernel :
func : selu_grad func : selu_grad
- backward_api : sigmoid_cross_entropy_with_logits_grad - backward_op : sigmoid_cross_entropy_with_logits_grad
forward : sigmoid_cross_entropy_with_logits (Tensor x, Tensor label, bool normalize, int ignore_index) -> Tensor(out) forward : sigmoid_cross_entropy_with_logits (Tensor x, Tensor label, bool normalize, int ignore_index) -> Tensor(out)
args : (Tensor x, Tensor label, Tensor out_grad, bool normalize, int ignore_index) args : (Tensor x, Tensor label, Tensor out_grad, bool normalize, int ignore_index)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2098,7 +2072,7 @@ ...@@ -2098,7 +2072,7 @@
func : sigmoid_cross_entropy_with_logits_grad func : sigmoid_cross_entropy_with_logits_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sigmoid_double_grad - backward_op : sigmoid_double_grad
forward : sigmoid_grad (Tensor out, Tensor fwd_grad_out) -> Tensor(grad_x) forward : sigmoid_grad (Tensor out, Tensor fwd_grad_out) -> Tensor(grad_x)
args : (Tensor out, Tensor fwd_grad_out, Tensor grad_x_grad) args : (Tensor out, Tensor fwd_grad_out, Tensor grad_x_grad)
output : Tensor(out_grad), Tensor(fwd_grad_out_grad) output : Tensor(out_grad), Tensor(fwd_grad_out_grad)
...@@ -2110,7 +2084,7 @@ ...@@ -2110,7 +2084,7 @@
backward : sigmoid_triple_grad backward : sigmoid_triple_grad
inplace : (grad_x_grad -> fwd_grad_out_grad) inplace : (grad_x_grad -> fwd_grad_out_grad)
- backward_api : sigmoid_grad - backward_op : sigmoid_grad
forward : sigmoid (Tensor x) -> Tensor(out) forward : sigmoid (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2122,7 +2096,7 @@ ...@@ -2122,7 +2096,7 @@
backward : sigmoid_double_grad backward : sigmoid_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sigmoid_triple_grad - backward_op : sigmoid_triple_grad
forward : sigmoid_double_grad (Tensor out, Tensor fwd_grad_out, Tensor grad_grad_x) -> Tensor(grad_out), Tensor(grad_grad_out) forward : sigmoid_double_grad (Tensor out, Tensor fwd_grad_out, Tensor grad_grad_x) -> Tensor(grad_out), Tensor(grad_grad_out)
args : (Tensor out, Tensor fwd_grad_out, Tensor grad_grad_x, Tensor grad_out_grad, Tensor grad_grad_out_grad) args : (Tensor out, Tensor fwd_grad_out, Tensor grad_grad_x, Tensor grad_out_grad, Tensor grad_grad_out_grad)
output : Tensor(out_grad), Tensor(fwd_grad_out_grad), Tensor(grad_grad_x_grad) output : Tensor(out_grad), Tensor(fwd_grad_out_grad), Tensor(grad_grad_x_grad)
...@@ -2134,7 +2108,7 @@ ...@@ -2134,7 +2108,7 @@
optional : grad_grad_out_grad optional : grad_grad_out_grad
inplace : (grad_grad_x -> fwd_grad_out_grad) inplace : (grad_grad_x -> fwd_grad_out_grad)
- backward_api : silu_grad - backward_op : silu_grad
forward : silu (Tensor x) -> Tensor(out) forward : silu (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2145,7 +2119,7 @@ ...@@ -2145,7 +2119,7 @@
func : silu_grad func : silu_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sin_grad - backward_op : sin_grad
forward : sin (Tensor x) -> Tensor(out) forward : sin (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2156,7 +2130,7 @@ ...@@ -2156,7 +2130,7 @@
func : sin_grad func : sin_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sinh_grad - backward_op : sinh_grad
forward : sinh (Tensor x) -> Tensor(out) forward : sinh (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2167,7 +2141,7 @@ ...@@ -2167,7 +2141,7 @@
func : sinh_grad func : sinh_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : slice_double_grad - backward_op : slice_double_grad
forward : slice_grad (Tensor input, Tensor grad_out, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(grad_input) forward : slice_grad (Tensor input, Tensor grad_out, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(grad_input)
args : (Tensor grad_input_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) args : (Tensor grad_input_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -2177,7 +2151,7 @@ ...@@ -2177,7 +2151,7 @@
kernel : kernel :
func : slice func : slice
- backward_api : slice_grad - backward_op : slice_grad
forward : slice (Tensor input, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(out) forward : slice (Tensor input, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) -> Tensor(out)
args : (Tensor input, Tensor out_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) args : (Tensor input, Tensor out_grad, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis)
output : Tensor(input_grad) output : Tensor(input_grad)
...@@ -2189,7 +2163,7 @@ ...@@ -2189,7 +2163,7 @@
backward : slice_double_grad backward : slice_double_grad
no_need_buffer : input no_need_buffer : input
- backward_api : slogdet_grad - backward_op : slogdet_grad
forward : slogdet (Tensor x) -> Tensor(out) forward : slogdet (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out, Tensor out_grad) args : (Tensor x, Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2199,7 +2173,7 @@ ...@@ -2199,7 +2173,7 @@
kernel : kernel :
func : slogdeterminant_grad func : slogdeterminant_grad
- backward_api : soft_shrink_grad - backward_op : soft_shrink_grad
forward : soft_shrink (Tensor x, float lambda) -> Tensor(out) forward : soft_shrink (Tensor x, float lambda) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float lambda) args : (Tensor x, Tensor out_grad, float lambda)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2210,7 +2184,7 @@ ...@@ -2210,7 +2184,7 @@
func : soft_shrink_grad func : soft_shrink_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : softmax_grad - backward_op : softmax_grad
forward : softmax (Tensor x, int axis) -> Tensor(out) forward : softmax (Tensor x, int axis) -> Tensor(out)
args : (Tensor out, Tensor out_grad, int axis) args : (Tensor out, Tensor out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2221,7 +2195,7 @@ ...@@ -2221,7 +2195,7 @@
func : softmax_grad func : softmax_grad
use_gpudnn : true use_gpudnn : true
- backward_api : softplus_grad - backward_op : softplus_grad
forward : softplus (Tensor x, float beta, float threshold) -> Tensor(out) forward : softplus (Tensor x, float beta, float threshold) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float beta, float threshold) args : (Tensor x, Tensor out_grad, float beta, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2232,7 +2206,7 @@ ...@@ -2232,7 +2206,7 @@
func : softplus_grad func : softplus_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : softsign_grad - backward_op : softsign_grad
forward : softsign (Tensor x) -> Tensor(out) forward : softsign (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2243,7 +2217,7 @@ ...@@ -2243,7 +2217,7 @@
func : softsign_grad func : softsign_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : spectral_norm_grad - backward_op : spectral_norm_grad
forward : spectral_norm (Tensor weight, Tensor u, Tensor v, int dim, int power_iters, float eps) -> Tensor(out) forward : spectral_norm (Tensor weight, Tensor u, Tensor v, int dim, int power_iters, float eps) -> Tensor(out)
args : (Tensor weight, Tensor u, Tensor v, Tensor out_grad, int dim, int power_iters, float eps) args : (Tensor weight, Tensor u, Tensor v, Tensor out_grad, int dim, int power_iters, float eps)
output : Tensor(weight_grad) output : Tensor(weight_grad)
...@@ -2253,20 +2227,20 @@ ...@@ -2253,20 +2227,20 @@
func : spectral_norm_grad func : spectral_norm_grad
data_type : out_grad data_type : out_grad
- backward_api : split_grad - backward_op : split_grad
forward : split (Tensor x, IntArray num_or_sections, Scalar axis) -> Tensor[](out) forward : split (Tensor x, IntArray num_or_sections, Scalar axis) -> Tensor[](out)
args : (Tensor[] out_grad, Scalar axis = -1) args : (Tensor[] out_grad, Scalar axis = -1)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : concat( out_grad, axis) invoke : concat( out_grad, axis)
- backward_api : split_with_num_grad - backward_op : split_with_num_grad
forward : split_with_num (Tensor x, int num, Scalar axis) -> Tensor[](out) forward : split_with_num (Tensor x, int num, Scalar axis) -> Tensor[](out)
args : (Tensor[] out_grad, Scalar axis = -1) args : (Tensor[] out_grad, Scalar axis = -1)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : concat( out_grad, axis) invoke : concat( out_grad, axis)
# TODO(zhangyunfei) The config of double grad and triple grad will be supported in the future. # TODO(zhangyunfei) The config of double grad and triple grad will be supported in the future.
- backward_api : sqrt_double_grad - backward_op : sqrt_double_grad
forward : sqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x) forward : sqrt_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor out, Tensor grad_x, Tensor grad_x_grad) args : (Tensor out, Tensor grad_x, Tensor grad_x_grad)
output : Tensor(out_grad), Tensor(grad_out_grad) output : Tensor(out_grad), Tensor(grad_out_grad)
...@@ -2277,7 +2251,7 @@ ...@@ -2277,7 +2251,7 @@
func : sqrt_double_grad func : sqrt_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : sqrt_grad - backward_op : sqrt_grad
forward : sqrt (Tensor x) -> Tensor(out) forward : sqrt (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2289,7 +2263,7 @@ ...@@ -2289,7 +2263,7 @@
backward : sqrt_double_grad backward : sqrt_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : square_double_grad - backward_op : square_double_grad
forward : square_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x) forward : square_grad (Tensor x, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor x, Tensor grad_out, Tensor grad_x_grad) args : (Tensor x, Tensor grad_out, Tensor grad_x_grad)
output : Tensor(x_grad), Tensor(grad_out_grad) output : Tensor(x_grad), Tensor(grad_out_grad)
...@@ -2300,7 +2274,7 @@ ...@@ -2300,7 +2274,7 @@
func : square_double_grad func : square_double_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : square_grad - backward_op : square_grad
forward : square (Tensor x) -> Tensor(out) forward : square (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2312,7 +2286,7 @@ ...@@ -2312,7 +2286,7 @@
backward : square_double_grad backward : square_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : squared_l2_norm_grad - backward_op : squared_l2_norm_grad
forward : squared_l2_norm(Tensor x) -> Tensor(out) forward : squared_l2_norm(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2322,13 +2296,13 @@ ...@@ -2322,13 +2296,13 @@
kernel : kernel :
func : squared_l2_norm_grad func : squared_l2_norm_grad
- backward_api : squeeze_double_grad - backward_op : squeeze_double_grad
forward : squeeze_grad(Tensor xshape, Tensor grad_out, IntArray axes) -> Tensor(grad_x) forward : squeeze_grad(Tensor xshape, Tensor grad_out, IntArray axes) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray axes) args : (Tensor grad_x_grad, IntArray axes)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
invoke: squeeze(grad_x_grad, axes) invoke: squeeze(grad_x_grad, axes)
- backward_api : squeeze_grad - backward_op : squeeze_grad
forward : squeeze(Tensor x, IntArray axes) -> Tensor(out), Tensor(xshape) forward : squeeze(Tensor x, IntArray axes) -> Tensor(out), Tensor(xshape)
args : (Tensor xshape, Tensor out_grad, IntArray axes) args : (Tensor xshape, Tensor out_grad, IntArray axes)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2340,7 +2314,7 @@ ...@@ -2340,7 +2314,7 @@
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
backward: squeeze_double_grad backward: squeeze_double_grad
- backward_api : stack_grad - backward_op : stack_grad
forward : stack (Tensor[] x, int axis) -> Tensor(out) forward : stack (Tensor[] x, int axis) -> Tensor(out)
args : (Tensor[] x, Tensor out_grad, int axis) args : (Tensor[] x, Tensor out_grad, int axis)
output : Tensor[](x_grad){x.size()} output : Tensor[](x_grad){x.size()}
...@@ -2352,7 +2326,7 @@ ...@@ -2352,7 +2326,7 @@
param : [out_grad, axis] param : [out_grad, axis]
no_need_buffer : x no_need_buffer : x
- backward_api : strided_slice_grad - backward_op : strided_slice_grad
forward : strided_slice (Tensor x, int[] axes, IntArray starts, IntArray ends, IntArray strides) -> Tensor(out) forward : strided_slice (Tensor x, int[] axes, IntArray starts, IntArray ends, IntArray strides) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int[] axes, IntArray starts, IntArray ends, IntArray strides) args : (Tensor x, Tensor out_grad, int[] axes, IntArray starts, IntArray ends, IntArray strides)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2363,7 +2337,7 @@ ...@@ -2363,7 +2337,7 @@
func : strided_slice_grad func : strided_slice_grad
no_need_buffer : x no_need_buffer : x
- backward_api : subtract_double_grad - backward_op : subtract_double_grad
forward : subtract_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y) forward : subtract_grad (Tensor x, Tensor y, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
args : (Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1) args : (Tensor y, Tensor grad_out, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -2376,7 +2350,7 @@ ...@@ -2376,7 +2350,7 @@
no_need_buffer : y, grad_out no_need_buffer : y, grad_out
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : subtract_grad - backward_op : subtract_grad
forward : subtract (Tensor x, Tensor y) -> Tensor(out) forward : subtract (Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1) args : (Tensor x, Tensor y, Tensor out_grad, int axis = -1)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -2389,13 +2363,13 @@ ...@@ -2389,13 +2363,13 @@
backward : subtract_double_grad backward : subtract_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sum_double_grad - backward_op : sum_double_grad
forward : sum_grad (Tensor x, Tensor grad_out, IntArray dims, bool keep_dim, bool reduce_all=false) -> Tensor(grad_x) forward : sum_grad (Tensor x, Tensor grad_out, IntArray dims, bool keep_dim, bool reduce_all=false) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray dims={}, bool keep_dim=false) args : (Tensor grad_x_grad, IntArray dims={}, bool keep_dim=false)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
invoke : sum(grad_x_grad, dims, grad_x_grad.dtype(), keep_dim) invoke : sum(grad_x_grad, dims, grad_x_grad.dtype(), keep_dim)
- backward_api : sum_grad - backward_op : sum_grad
forward : sum (Tensor x, IntArray dims={}, DataType out_dtype=DataType::UNDEFINED, bool keep_dim=false) -> Tensor(out) forward : sum (Tensor x, IntArray dims={}, DataType out_dtype=DataType::UNDEFINED, bool keep_dim=false) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray dims, bool keep_dim, bool reduce_all=false) args : (Tensor x, Tensor out_grad, IntArray dims, bool keep_dim, bool reduce_all=false)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2407,7 +2381,7 @@ ...@@ -2407,7 +2381,7 @@
no_need_buffer : x no_need_buffer : x
backward : sum_double_grad backward : sum_double_grad
- backward_api : svd_grad - backward_op : svd_grad
forward : svd (Tensor x, bool full) -> Tensor(u), Tensor(s), Tensor(vh) forward : svd (Tensor x, bool full) -> Tensor(u), Tensor(s), Tensor(vh)
args : (Tensor x, Tensor u, Tensor vh, Tensor s, Tensor u_grad, Tensor vh_grad, Tensor s_grad, bool full) args : (Tensor x, Tensor u, Tensor vh, Tensor s, Tensor u_grad, Tensor vh_grad, Tensor s_grad, bool full)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2418,7 +2392,7 @@ ...@@ -2418,7 +2392,7 @@
func : svd_grad func : svd_grad
optional: u_grad, vh_grad, s_grad optional: u_grad, vh_grad, s_grad
- backward_api : swish_grad - backward_op : swish_grad
forward : swish (Tensor x, float beta=1.0) -> Tensor(out) forward : swish (Tensor x, float beta=1.0) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float bete=1.0) args : (Tensor x, Tensor out_grad, float bete=1.0)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2429,7 +2403,7 @@ ...@@ -2429,7 +2403,7 @@
func : swish_grad func : swish_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : sync_batch_norm_grad - backward_op : sync_batch_norm_grad
forward : sync_batch_norm_ (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space) forward : sync_batch_norm_ (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) -> Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
args : (Tensor x, Tensor scale, Tensor bias, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) args : (Tensor x, Tensor scale, Tensor bias, Tensor saved_mean, Tensor saved_variance, Tensor reserve_space, Tensor out_grad, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad) output : Tensor(x_grad), Tensor(scale_grad), Tensor(bias_grad)
...@@ -2441,7 +2415,7 @@ ...@@ -2441,7 +2415,7 @@
data_type : out_grad data_type : out_grad
optional : reserve_space optional : reserve_space
- backward_api : take_along_axis_grad - backward_op : take_along_axis_grad
forward : take_along_axis (Tensor x, Tensor index, int axis) -> Tensor(out) forward : take_along_axis (Tensor x, Tensor index, int axis) -> Tensor(out)
args : (Tensor x, Tensor index, Tensor out_grad, int axis) args : (Tensor x, Tensor index, Tensor out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2451,7 +2425,7 @@ ...@@ -2451,7 +2425,7 @@
kernel : kernel :
func : take_along_axis_grad func : take_along_axis_grad
- backward_api : tan_grad - backward_op : tan_grad
forward : tan (Tensor x) -> Tensor(out) forward : tan (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2462,7 +2436,7 @@ ...@@ -2462,7 +2436,7 @@
func : tan_grad func : tan_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : tanh_double_grad - backward_op : tanh_double_grad
forward : tanh_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x) forward : tanh_grad (Tensor out, Tensor grad_out) -> Tensor(grad_x)
args : (Tensor out, Tensor grad_out, Tensor grad_x_grad) args : (Tensor out, Tensor grad_out, Tensor grad_x_grad)
output : Tensor(out_grad), Tensor(grad_out_grad) output : Tensor(out_grad), Tensor(grad_out_grad)
...@@ -2474,7 +2448,7 @@ ...@@ -2474,7 +2448,7 @@
backward : tanh_triple_grad backward : tanh_triple_grad
inplace : (grad_x_grad -> grad_out_grad) inplace : (grad_x_grad -> grad_out_grad)
- backward_api : tanh_grad - backward_op : tanh_grad
forward : tanh (Tensor x) -> Tensor(out) forward : tanh (Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2486,7 +2460,7 @@ ...@@ -2486,7 +2460,7 @@
backward : tanh_double_grad backward : tanh_double_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : tanh_shrink_grad - backward_op : tanh_shrink_grad
forward : tanh_shrink (Tensor x) -> Tensor(out) forward : tanh_shrink (Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2497,7 +2471,7 @@ ...@@ -2497,7 +2471,7 @@
func : tanh_shrink_grad func : tanh_shrink_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : tanh_triple_grad - backward_op : tanh_triple_grad
forward : tanh_double_grad (Tensor out, Tensor grad_out_forward, Tensor grad_x_grad_forward) -> Tensor(grad_out_new), Tensor(grad_out_grad) forward : tanh_double_grad (Tensor out, Tensor grad_out_forward, Tensor grad_x_grad_forward) -> Tensor(grad_out_new), Tensor(grad_out_grad)
args : (Tensor out, Tensor grad_out_forward, Tensor grad_x_grad_forward, Tensor grad_out_new_grad, Tensor grad_out_grad_grad) args : (Tensor out, Tensor grad_out_forward, Tensor grad_x_grad_forward, Tensor grad_out_new_grad, Tensor grad_out_grad_grad)
output : Tensor(out_grad), Tensor(grad_out_forward_grad), Tensor(grad_x_grad_forward_grad) output : Tensor(out_grad), Tensor(grad_out_forward_grad), Tensor(grad_x_grad_forward_grad)
...@@ -2508,7 +2482,7 @@ ...@@ -2508,7 +2482,7 @@
func : tanh_triple_grad func : tanh_triple_grad
inplace : (grad_x_grad_forward -> grad_out_forward_grad) inplace : (grad_x_grad_forward -> grad_out_forward_grad)
- backward_api : temporal_shift_grad - backward_op : temporal_shift_grad
forward : temporal_shift(Tensor x, int seg_num, float shift_ratio, str data_format_str) -> Tensor(out) forward : temporal_shift(Tensor x, int seg_num, float shift_ratio, str data_format_str) -> Tensor(out)
args : (Tensor out_grad, int seg_num, float shift_ratio, str data_format_str) args : (Tensor out_grad, int seg_num, float shift_ratio, str data_format_str)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2518,7 +2492,7 @@ ...@@ -2518,7 +2492,7 @@
kernel : kernel :
func : temporal_shift_grad func : temporal_shift_grad
- backward_api : thresholded_relu_grad - backward_op : thresholded_relu_grad
forward : thresholded_relu (Tensor x, float threshold) -> Tensor(out) forward : thresholded_relu (Tensor x, float threshold) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float threshold) args : (Tensor x, Tensor out_grad, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2529,7 +2503,7 @@ ...@@ -2529,7 +2503,7 @@
func : thresholded_relu_grad func : thresholded_relu_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : tile_double_grad - backward_op : tile_double_grad
forward : tile_grad (Tensor x, Tensor grad_out, IntArray repeat_times) -> Tensor(grad_x) forward : tile_grad (Tensor x, Tensor grad_out, IntArray repeat_times) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray repeat_times) args : (Tensor grad_x_grad, IntArray repeat_times)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
...@@ -2538,7 +2512,7 @@ ...@@ -2538,7 +2512,7 @@
kernel : kernel :
func : tile func : tile
- backward_api : tile_grad - backward_op : tile_grad
forward : tile (Tensor x, IntArray repeat_times) -> Tensor(out) forward : tile (Tensor x, IntArray repeat_times) -> Tensor(out)
args : (Tensor x, Tensor out_grad, IntArray repeat_times) args : (Tensor x, Tensor out_grad, IntArray repeat_times)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2550,7 +2524,7 @@ ...@@ -2550,7 +2524,7 @@
no_need_buffer : x no_need_buffer : x
backward : tile_double_grad backward : tile_double_grad
- backward_api : top_k_grad - backward_op : top_k_grad
forward : top_k (Tensor x, Scalar k, int axis = -1, bool largest = true, bool sorted = true) -> Tensor(out), Tensor(indices) forward : top_k (Tensor x, Scalar k, int axis = -1, bool largest = true, bool sorted = true) -> Tensor(out), Tensor(indices)
args : (Tensor x, Tensor indices, Tensor out_grad, Scalar k = -1, int axis = -1, bool largest = true, bool sorted = true) args : (Tensor x, Tensor indices, Tensor out_grad, Scalar k = -1, int axis = -1, bool largest = true, bool sorted = true)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2560,13 +2534,13 @@ ...@@ -2560,13 +2534,13 @@
kernel : kernel :
func : top_k_grad func : top_k_grad
- backward_api : transpose_double_grad - backward_op : transpose_double_grad
forward : transpose_grad (Tensor grad_out, int[] axis) -> Tensor(grad_x) forward : transpose_grad (Tensor grad_out, int[] axis) -> Tensor(grad_x)
args : (Tensor grad_x_grad, int[] axis) args : (Tensor grad_x_grad, int[] axis)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
invoke : transpose(grad_x_grad, axis) invoke : transpose(grad_x_grad, axis)
- backward_api : transpose_grad - backward_op : transpose_grad
forward : transpose (Tensor x, int[] axis) -> Tensor(out) forward : transpose (Tensor x, int[] axis) -> Tensor(out)
args : (Tensor out_grad, int[] axis) args : (Tensor out_grad, int[] axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2577,7 +2551,7 @@ ...@@ -2577,7 +2551,7 @@
func : transpose_grad func : transpose_grad
backward : transpose_double_grad backward : transpose_double_grad
- backward_api : triangular_solve_grad - backward_op : triangular_solve_grad
forward : triangular_solve (Tensor x, Tensor y, bool upper, bool tranpose, bool unitriangular) -> Tensor(out) forward : triangular_solve (Tensor x, Tensor y, bool upper, bool tranpose, bool unitriangular) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper, bool tranpose, bool unitriangular) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper, bool tranpose, bool unitriangular)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -2587,7 +2561,7 @@ ...@@ -2587,7 +2561,7 @@
kernel : kernel :
func : triangular_solve_grad func : triangular_solve_grad
- backward_api : tril_triu_grad - backward_op : tril_triu_grad
forward : tril_triu(Tensor x, int diagonal, bool lower) -> Tensor(out) forward : tril_triu(Tensor x, int diagonal, bool lower) -> Tensor(out)
args : (Tensor out_grad, int diagonal, bool lower) args : (Tensor out_grad, int diagonal, bool lower)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2597,7 +2571,7 @@ ...@@ -2597,7 +2571,7 @@
kernel : kernel :
func : tril_triu_grad func : tril_triu_grad
- backward_api : trilinear_interp_grad - backward_op : trilinear_interp_grad
forward : trilinear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output) forward : trilinear_interp (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) -> Tensor(output)
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, Tensor output_grad, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2609,13 +2583,13 @@ ...@@ -2609,13 +2583,13 @@
func : trilinear_interp_grad func : trilinear_interp_grad
data_type : output_grad data_type : output_grad
- backward_api : unbind_grad - backward_op : unbind_grad
forward : unbind (Tensor input, int axis) -> Tensor[](out) forward : unbind (Tensor input, int axis) -> Tensor[](out)
args : (Tensor[] out_grad, int axis) args : (Tensor[] out_grad, int axis)
output : Tensor(input_grad) output : Tensor(input_grad)
invoke : stack(out_grad, axis) invoke : stack(out_grad, axis)
- backward_api : unfold_grad - backward_op : unfold_grad
forward : unfold (Tensor x, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) -> Tensor(out) forward : unfold (Tensor x, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) -> Tensor(out)
args : (Tensor x, Tensor out_grad, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) args : (Tensor x, Tensor out_grad, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2626,7 +2600,7 @@ ...@@ -2626,7 +2600,7 @@
func : unfold_grad func : unfold_grad
no_need_buffer : x no_need_buffer : x
- backward_api : uniform_random_inplace_grad - backward_op : uniform_random_inplace_grad
forward : uniform_random_inplace(Tensor x, float min, float max, int seed, int diag_num, int diag_step, float diag_val) -> Tensor(out) forward : uniform_random_inplace(Tensor x, float min, float max, int seed, int diag_num, int diag_step, float diag_val) -> Tensor(out)
args : (Tensor out_grad, float min, float max, int seed, int diag_num, int diag_step, float diag_val) args : (Tensor out_grad, float min, float max, int seed, int diag_num, int diag_step, float diag_val)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2636,13 +2610,13 @@ ...@@ -2636,13 +2610,13 @@
func : uniform_random_inplace_grad func : uniform_random_inplace_grad
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
- backward_api : unsqueeze_double_grad - backward_op : unsqueeze_double_grad
forward : unsqueeze_grad(Tensor xshape, Tensor grad_out, IntArray axes) -> Tensor(grad_x) forward : unsqueeze_grad(Tensor xshape, Tensor grad_out, IntArray axes) -> Tensor(grad_x)
args : (Tensor grad_x_grad, IntArray axes) args : (Tensor grad_x_grad, IntArray axes)
output : Tensor(grad_out_grad) output : Tensor(grad_out_grad)
invoke : unsqueeze(grad_x_grad, axes) invoke : unsqueeze(grad_x_grad, axes)
- backward_api : unsqueeze_grad - backward_op : unsqueeze_grad
forward : unsqueeze(Tensor x, IntArray axes) -> Tensor(out), Tensor(xshape) forward : unsqueeze(Tensor x, IntArray axes) -> Tensor(out), Tensor(xshape)
args : (Tensor xshape, Tensor out_grad, IntArray axes) args : (Tensor xshape, Tensor out_grad, IntArray axes)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2655,7 +2629,7 @@ ...@@ -2655,7 +2629,7 @@
inplace : (out_grad -> x_grad) inplace : (out_grad -> x_grad)
backward : unsqueeze_double_grad backward : unsqueeze_double_grad
- backward_api : unstack_grad - backward_op : unstack_grad
forward : unstack (Tensor x, int axis, int num) -> Tensor[](out) forward : unstack (Tensor x, int axis, int num) -> Tensor[](out)
args : (Tensor[] out_grad, int axis) args : (Tensor[] out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -2665,7 +2639,7 @@ ...@@ -2665,7 +2639,7 @@
kernel : kernel :
func : unstack_grad func : unstack_grad
- backward_api : warpctc_grad - backward_op : warpctc_grad
forward : warpctc (Tensor logits, Tensor label, Tensor logits_length, Tensor labels_length, int blank, bool norm_by_times) -> Tensor(loss), Tensor(warpctcgrad) forward : warpctc (Tensor logits, Tensor label, Tensor logits_length, Tensor labels_length, int blank, bool norm_by_times) -> Tensor(loss), Tensor(warpctcgrad)
args : (Tensor logits, Tensor logits_length, Tensor warpctcgrad, Tensor loss_grad, int blank, bool norm_by_times) args : (Tensor logits, Tensor logits_length, Tensor warpctcgrad, Tensor loss_grad, int blank, bool norm_by_times)
output : Tensor(logits_grad) output : Tensor(logits_grad)
...@@ -2677,7 +2651,7 @@ ...@@ -2677,7 +2651,7 @@
optional : logits_length optional : logits_length
no_need_buffer : logits no_need_buffer : logits
- backward_api : where_grad - backward_op : where_grad
forward : where (Tensor condition, Tensor x, Tensor y) -> Tensor(out) forward : where (Tensor condition, Tensor x, Tensor y) -> Tensor(out)
args : (Tensor condition, Tensor x, Tensor y, Tensor out_grad) args : (Tensor condition, Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -2688,7 +2662,7 @@ ...@@ -2688,7 +2662,7 @@
func : where_grad func : where_grad
no_need_buffer : x, y no_need_buffer : x, y
- backward_api : yolov3_loss_grad - backward_op : yolov3_loss_grad
forward : yolov3_loss(Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) -> Tensor(loss), Tensor(objectness_mask), Tensor(gt_match_mask) forward : yolov3_loss(Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) -> Tensor(loss), Tensor(objectness_mask), Tensor(gt_match_mask)
args : (Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, Tensor objectness_mask, Tensor gt_match_mask, Tensor loss_grad, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) args : (Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, Tensor objectness_mask, Tensor gt_match_mask, Tensor loss_grad, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0)
output : Tensor(x_grad), Tensor(gt_box_grad), Tensor(gt_label_grad), Tensor(gt_score_grad) output : Tensor(x_grad), Tensor(gt_box_grad), Tensor(gt_label_grad), Tensor(gt_score_grad)
...@@ -2698,7 +2672,7 @@ ...@@ -2698,7 +2672,7 @@
func : yolov3_loss_grad func : yolov3_loss_grad
optional : gt_score optional : gt_score
- backward_api: fold_grad - backward_op: fold_grad
forward: fold (Tensor x, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) -> Tensor(out) forward: fold (Tensor x, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) -> Tensor(out)
args: (Tensor x, Tensor out_grad, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) args: (Tensor x, Tensor out_grad, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations)
output: Tensor(x_grad) output: Tensor(x_grad)
...@@ -2709,7 +2683,7 @@ ...@@ -2709,7 +2683,7 @@
func: fold_grad func: fold_grad
no_need_buffer : x no_need_buffer : x
- backward_api: unpool3d_grad - backward_op: unpool3d_grad
forward: unpool3d (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format) -> Tensor(out) forward: unpool3d (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format) -> Tensor(out)
args: (Tensor x, Tensor indices, Tensor out, Tensor out_grad, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format) args: (Tensor x, Tensor indices, Tensor out, Tensor out_grad, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format)
output: Tensor(x_grad) output: Tensor(x_grad)
...@@ -2720,7 +2694,7 @@ ...@@ -2720,7 +2694,7 @@
func: unpool3d_grad func: unpool3d_grad
data_type: x data_type: x
- backward_api: unpool_grad - backward_op: unpool_grad
forward: unpool (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format) -> Tensor(out) forward: unpool (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format) -> Tensor(out)
args: (Tensor x, Tensor indices, Tensor out, Tensor out_grad, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format) args: (Tensor x, Tensor indices, Tensor out, Tensor out_grad, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format)
output: Tensor(x_grad) output: Tensor(x_grad)
......
paddle/phi/api/yaml/legacy_api.yaml → paddle/phi/api/yaml/legacy_ops.yaml
浏览文件 @ 8caaf85a
# The apis in this file are unstandardized that may caused by a variety of reasons, # The apis in this file are unstandardized that may caused by a variety of reasons,
# we are trying to fix these apis and will move standardized apis into api.yaml. # we are trying to fix these apis and will move standardized apis into ops.yaml.
- api : abs - op : abs
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -10,7 +10,7 @@ ...@@ -10,7 +10,7 @@
func : abs func : abs
backward : abs_grad backward : abs_grad
- api : accuracy - op : accuracy
args : (Tensor x, Tensor indices, Tensor label) args : (Tensor x, Tensor indices, Tensor label)
output : Tensor(accuracy), Tensor(correct), Tensor(total) output : Tensor(accuracy), Tensor(correct), Tensor(total)
infer_meta : infer_meta :
...@@ -19,7 +19,7 @@ ...@@ -19,7 +19,7 @@
func : accuracy func : accuracy
dtype : x dtype : x
- api : acos - op : acos
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -28,7 +28,7 @@ ...@@ -28,7 +28,7 @@
func : acos func : acos
backward : acos_grad backward : acos_grad
- api : acosh - op : acosh
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -37,7 +37,7 @@ ...@@ -37,7 +37,7 @@
func : acosh func : acosh
backward : acosh_grad backward : acosh_grad
- api : adadelta_ - op : adadelta_
args : (Tensor param, Tensor grad, Tensor avg_squared_grad, Tensor avg_squared_update, float rho, float epsilon) args : (Tensor param, Tensor grad, Tensor avg_squared_grad, Tensor avg_squared_update, float rho, float epsilon)
output : Tensor(param_out), Tensor(moment_out), Tensor(inf_norm_out) output : Tensor(param_out), Tensor(moment_out), Tensor(inf_norm_out)
infer_meta : infer_meta :
...@@ -46,7 +46,7 @@ ...@@ -46,7 +46,7 @@
func : adadelta func : adadelta
inplace : (param -> param_out), (avg_squared_grad -> moment_out), (avg_squared_update -> inf_norm_out) inplace : (param -> param_out), (avg_squared_grad -> moment_out), (avg_squared_update -> inf_norm_out)
- api : adagrad_ - op : adagrad_
args : (Tensor param, Tensor grad, Tensor moment, Tensor learning_rate, float epsilon) args : (Tensor param, Tensor grad, Tensor moment, Tensor learning_rate, float epsilon)
output : Tensor(param_out), Tensor(moment_out) output : Tensor(param_out), Tensor(moment_out)
infer_meta : infer_meta :
...@@ -57,7 +57,7 @@ ...@@ -57,7 +57,7 @@
data_type : param data_type : param
inplace : (param -> param_out), (moment -> moment_out) inplace : (param -> param_out), (moment -> moment_out)
- api : adam_ - op : adam_
args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1, Scalar beta2, Scalar epsilon, bool lazy_mode, int64_t min_row_size_to_use_multithread, bool multi_precision, bool use_global_beta_pow) args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1, Scalar beta2, Scalar epsilon, bool lazy_mode, int64_t min_row_size_to_use_multithread, bool multi_precision, bool use_global_beta_pow)
output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs) output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs)
infer_meta : infer_meta :
...@@ -69,7 +69,7 @@ ...@@ -69,7 +69,7 @@
optional : master_param, skip_update optional : master_param, skip_update
inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs) inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs)
- api : adamax_ - op : adamax_
args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment, Tensor inf_norm, Tensor beta1_pow, float beta1, float beta2, float epsilon) args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment, Tensor inf_norm, Tensor beta1_pow, float beta1, float beta2, float epsilon)
output : Tensor(param_out), Tensor(avg_squared_grad_out), Tensor(avg_squared_update_out) output : Tensor(param_out), Tensor(avg_squared_grad_out), Tensor(avg_squared_update_out)
infer_meta : infer_meta :
...@@ -78,7 +78,7 @@ ...@@ -78,7 +78,7 @@
func : adamax func : adamax
inplace : (param -> param_out), (moment -> avg_squared_grad_out), (inf_norm -> avg_squared_update_out) inplace : (param -> param_out), (moment -> avg_squared_grad_out), (inf_norm -> avg_squared_update_out)
- api : adamw_ - op : adamw_
args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1, Scalar beta2, Scalar epsilon, float lr_ratio, float coeff, bool with_decay, bool lazy_mode, int64_t min_row_size_to_use_multithread, bool multi_precision, bool use_global_beta_pow) args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, Scalar beta1, Scalar beta2, Scalar epsilon, float lr_ratio, float coeff, bool with_decay, bool lazy_mode, int64_t min_row_size_to_use_multithread, bool multi_precision, bool use_global_beta_pow)
output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs) output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs)
infer_meta : infer_meta :
...@@ -89,7 +89,7 @@ ...@@ -89,7 +89,7 @@
optional : master_param, skip_update optional : master_param, skip_update
inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs) inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs)
- api : add - op : add
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -99,7 +99,7 @@ ...@@ -99,7 +99,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : add_grad backward : add_grad
- api : add_n - op : add_n
args : (Tensor[] x) args : (Tensor[] x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -108,7 +108,7 @@ ...@@ -108,7 +108,7 @@
func : add_n func : add_n
backward : add_n_grad backward : add_n_grad
- api : addmm - op : addmm
args : (Tensor input, Tensor x, Tensor y, float alpha, float beta) args : (Tensor input, Tensor x, Tensor y, float alpha, float beta)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -117,7 +117,7 @@ ...@@ -117,7 +117,7 @@
func : addmm func : addmm
backward : addmm_grad backward : addmm_grad
- api : affine_grid - op : affine_grid
args : (Tensor input, IntArray outputShape, bool use_cudnn=true, bool align_corners=true) args : (Tensor input, IntArray outputShape, bool use_cudnn=true, bool align_corners=true)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -130,7 +130,7 @@ ...@@ -130,7 +130,7 @@
use_gpudnn: use_cudnn use_gpudnn: use_cudnn
backward : affine_grid_grad backward : affine_grid_grad
- api : all - op : all
args : (Tensor x, int64_t[] dims={}, bool keep_dim=false) args : (Tensor x, int64_t[] dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -138,7 +138,7 @@ ...@@ -138,7 +138,7 @@
kernel : kernel :
func : all func : all
- api : allclose - op : allclose
args : (Tensor x, Tensor y, Scalar rtol, Scalar atol, bool equal_nan) args : (Tensor x, Tensor y, Scalar rtol, Scalar atol, bool equal_nan)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -147,7 +147,7 @@ ...@@ -147,7 +147,7 @@
kernel : kernel :
func : allclose func : allclose
- api : amax - op : amax
args : (Tensor x, int64_t[] dims={}, bool keep_dim=false) args : (Tensor x, int64_t[] dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -156,7 +156,7 @@ ...@@ -156,7 +156,7 @@
func : amax func : amax
backward : amax_grad backward : amax_grad
- api : amin - op : amin
args : (Tensor x, int64_t[] dims={}, bool keep_dim=false) args : (Tensor x, int64_t[] dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -165,7 +165,7 @@ ...@@ -165,7 +165,7 @@
func : amin func : amin
backward : amin_grad backward : amin_grad
- api : angle - op : angle
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -174,7 +174,7 @@ ...@@ -174,7 +174,7 @@
func : angle func : angle
backward : angle_grad backward : angle_grad
- api : any - op : any
args : (Tensor x, int64_t[] dims={}, bool keep_dim=false) args : (Tensor x, int64_t[] dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -182,7 +182,7 @@ ...@@ -182,7 +182,7 @@
kernel : kernel :
func : any func : any
- api : arange - op : arange
args : (Tensor start, Tensor end, Tensor step, DataType dtype, Place place={}) args : (Tensor start, Tensor end, Tensor step, DataType dtype, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -196,7 +196,7 @@ ...@@ -196,7 +196,7 @@
data_transform : data_transform :
support_trans_dtype : start, end, step support_trans_dtype : start, end, step
- api : argmax - op : argmax
args : (Tensor x, Scalar axis, bool keepdims, bool flatten, int dtype) args : (Tensor x, Scalar axis, bool keepdims, bool flatten, int dtype)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -204,7 +204,7 @@ ...@@ -204,7 +204,7 @@
kernel : kernel :
func : arg_max func : arg_max
- api : argmin - op : argmin
args : (Tensor x, Scalar axis, bool keepdims, bool flatten, int dtype) args : (Tensor x, Scalar axis, bool keepdims, bool flatten, int dtype)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -212,7 +212,7 @@ ...@@ -212,7 +212,7 @@
kernel : kernel :
func : arg_min func : arg_min
- api : argsort - op : argsort
args : (Tensor x, int axis=-1, bool descending=false) args : (Tensor x, int axis=-1, bool descending=false)
output : Tensor(out), Tensor(indices) output : Tensor(out), Tensor(indices)
infer_meta : infer_meta :
...@@ -221,7 +221,7 @@ ...@@ -221,7 +221,7 @@
func : argsort func : argsort
backward : argsort_grad backward : argsort_grad
- api : as_complex - op : as_complex
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -230,7 +230,7 @@ ...@@ -230,7 +230,7 @@
func : as_complex func : as_complex
backward : as_complex_grad backward : as_complex_grad
- api : as_real - op : as_real
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -239,7 +239,7 @@ ...@@ -239,7 +239,7 @@
func : as_real func : as_real
backward : as_real_grad backward : as_real_grad
- api : asin - op : asin
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -248,7 +248,7 @@ ...@@ -248,7 +248,7 @@
func : asin func : asin
backward : asin_grad backward : asin_grad
- api : asinh - op : asinh
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -257,7 +257,7 @@ ...@@ -257,7 +257,7 @@
func : asinh func : asinh
backward : asinh_grad backward : asinh_grad
- api : assign - op : assign
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -266,7 +266,7 @@ ...@@ -266,7 +266,7 @@
func : assign func : assign
backward : assign_grad backward : assign_grad
- api : assign_out_ - op : assign_out_
args : (Tensor x, Tensor output) args : (Tensor x, Tensor output)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -278,7 +278,7 @@ ...@@ -278,7 +278,7 @@
inplace : (output -> out) inplace : (output -> out)
backward : assign_out__grad backward : assign_out__grad
- api : assign_value_ - op : assign_value_
args : (Tensor output, int[] shape, DataType dtype, Scalar[] values, Place place = {}) args : (Tensor output, int[] shape, DataType dtype, Scalar[] values, Place place = {})
output : Tensor(out) output : Tensor(out)
inplace: (output -> out) inplace: (output -> out)
...@@ -291,7 +291,7 @@ ...@@ -291,7 +291,7 @@
data_type : dtype data_type : dtype
backend : place > output backend : place > output
- api : atan - op : atan
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -300,7 +300,7 @@ ...@@ -300,7 +300,7 @@
func : atan func : atan
backward : atan_grad backward : atan_grad
- api : atanh - op : atanh
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -309,7 +309,7 @@ ...@@ -309,7 +309,7 @@
func : atanh func : atanh
backward : atanh_grad backward : atanh_grad
- api : auc - op : auc
args : (Tensor x, Tensor label, Tensor stat_pos, Tensor stat_neg, Tensor ins_tag_weight, str curve, int num_thresholds, int slide_steps) args : (Tensor x, Tensor label, Tensor stat_pos, Tensor stat_neg, Tensor ins_tag_weight, str curve, int num_thresholds, int slide_steps)
output : Tensor(auc), Tensor(stat_pos_out), Tensor(stat_neg_out) output : Tensor(auc), Tensor(stat_pos_out), Tensor(stat_neg_out)
infer_meta : infer_meta :
...@@ -318,7 +318,7 @@ ...@@ -318,7 +318,7 @@
func : auc func : auc
optional : ins_tag_weight optional : ins_tag_weight
- api : average_accumulates_ - op : average_accumulates_
args : (Tensor param, Tensor in_sum_1, Tensor in_sum_2, Tensor in_sum_3, Tensor in_num_accumulates, Tensor in_old_num_accumulates, Tensor in_num_updates, float average_window, int64_t max_average_window, int64_t min_average_window) args : (Tensor param, Tensor in_sum_1, Tensor in_sum_2, Tensor in_sum_3, Tensor in_num_accumulates, Tensor in_old_num_accumulates, Tensor in_num_updates, float average_window, int64_t max_average_window, int64_t min_average_window)
output : Tensor(out_sum_1), Tensor(out_sum_2), Tensor(out_sum_3), Tensor(out_num_accumulates), Tensor(out_old_num_accumulates), Tensor(out_num_updates) output : Tensor(out_sum_1), Tensor(out_sum_2), Tensor(out_sum_3), Tensor(out_num_accumulates), Tensor(out_old_num_accumulates), Tensor(out_num_updates)
infer_meta: infer_meta:
...@@ -328,13 +328,13 @@ ...@@ -328,13 +328,13 @@
data_type : param data_type : param
inplace : (in_sum_1 -> out_sum_1), (in_sum_2 -> out_sum_2), (in_sum_3 -> out_sum_3), (in_num_accumulates -> out_num_accumulates), (in_old_num_accumulates -> out_old_num_accumulates), (in_num_updates -> out_num_updates) inplace : (in_sum_1 -> out_sum_1), (in_sum_2 -> out_sum_2), (in_sum_3 -> out_sum_3), (in_num_accumulates -> out_num_accumulates), (in_old_num_accumulates -> out_old_num_accumulates), (in_num_updates -> out_num_updates)
- api : batch_norm - op : batch_norm
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space) output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
invoke : batch_norm_impl(x, scale, bias, mean, variance, momentum, epsilon, data_layout, is_test, use_global_stats, trainable_statistics, fuse_with_relu) invoke : batch_norm_impl(x, scale, bias, mean, variance, momentum, epsilon, data_layout, is_test, use_global_stats, trainable_statistics, fuse_with_relu)
backward : batch_norm_grad backward : batch_norm_grad
- api : bce_loss - op : bce_loss
args : (Tensor input, Tensor label) args : (Tensor input, Tensor label)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -343,7 +343,7 @@ ...@@ -343,7 +343,7 @@
func : bce_loss func : bce_loss
backward : bce_loss_grad backward : bce_loss_grad
- api : bicubic_interp - op : bicubic_interp
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(output) output : Tensor(output)
infer_meta : infer_meta :
...@@ -354,7 +354,7 @@ ...@@ -354,7 +354,7 @@
data_type : x data_type : x
backward : bicubic_interp_grad backward : bicubic_interp_grad
- api : bilinear_interp - op : bilinear_interp
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(output) output : Tensor(output)
infer_meta : infer_meta :
...@@ -365,7 +365,7 @@ ...@@ -365,7 +365,7 @@
data_type : x data_type : x
backward : bilinear_interp_grad backward : bilinear_interp_grad
- api : bilinear_tensor_product - op : bilinear_tensor_product
args : (Tensor x, Tensor y, Tensor weight, Tensor bias) args : (Tensor x, Tensor y, Tensor weight, Tensor bias)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -375,7 +375,7 @@ ...@@ -375,7 +375,7 @@
optional : bias optional : bias
backward : bilinear_tensor_product_grad backward : bilinear_tensor_product_grad
- api : bitwise_and - op : bitwise_and
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -383,7 +383,7 @@ ...@@ -383,7 +383,7 @@
kernel : kernel :
func : bitwise_and func : bitwise_and
- api : bitwise_not - op : bitwise_not
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -391,7 +391,7 @@ ...@@ -391,7 +391,7 @@
kernel : kernel :
func : bitwise_not func : bitwise_not
- api : bitwise_or - op : bitwise_or
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -399,7 +399,7 @@ ...@@ -399,7 +399,7 @@
kernel : kernel :
func : bitwise_or func : bitwise_or
- api : bitwise_xor - op : bitwise_xor
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -407,7 +407,7 @@ ...@@ -407,7 +407,7 @@
kernel : kernel :
func : bitwise_xor func : bitwise_xor
- api : bmm - op : bmm
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -416,7 +416,7 @@ ...@@ -416,7 +416,7 @@
func : bmm func : bmm
backward : bmm_grad backward : bmm_grad
- api : box_coder - op : box_coder
args : (Tensor prior_box, Tensor prior_box_var, Tensor target_box, str code_type, bool box_normalized, int axis, float[] variance) args : (Tensor prior_box, Tensor prior_box_var, Tensor target_box, str code_type, bool box_normalized, int axis, float[] variance)
output : Tensor(output_box) output : Tensor(output_box)
infer_meta : infer_meta :
...@@ -425,7 +425,7 @@ ...@@ -425,7 +425,7 @@
func : box_coder func : box_coder
optional : prior_box_var optional : prior_box_var
- api : brelu - op : brelu
args : (Tensor x, float t_min, float t_max) args : (Tensor x, float t_min, float t_max)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -435,7 +435,7 @@ ...@@ -435,7 +435,7 @@
func : brelu func : brelu
backward : brelu_grad backward : brelu_grad
- api : cast - op : cast
args : (Tensor x, DataType out_dtype) args : (Tensor x, DataType out_dtype)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -446,7 +446,7 @@ ...@@ -446,7 +446,7 @@
data_type : x data_type : x
backward : cast_grad backward : cast_grad
- api : ceil - op : ceil
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -456,7 +456,7 @@ ...@@ -456,7 +456,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : ceil_grad backward : ceil_grad
- api : celu - op : celu
args : (Tensor x, float alpha) args : (Tensor x, float alpha)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -466,7 +466,7 @@ ...@@ -466,7 +466,7 @@
func : celu func : celu
backward : celu_grad backward : celu_grad
- api : class_center_sample - op : class_center_sample
args : (Tensor label, int num_classes, int num_samples, int ring_id, int rank, int nranks, bool fix_seed, int seed) args : (Tensor label, int num_classes, int num_samples, int ring_id, int rank, int nranks, bool fix_seed, int seed)
output : Tensor(remapped_label), Tensor(sampled_local_class_center) output : Tensor(remapped_label), Tensor(sampled_local_class_center)
infer_meta : infer_meta :
...@@ -474,7 +474,7 @@ ...@@ -474,7 +474,7 @@
kernel : kernel :
func : class_center_sample func : class_center_sample
- api : clip - op : clip
args : (Tensor x, Scalar(float) min, Scalar(float) max) args : (Tensor x, Scalar(float) min, Scalar(float) max)
output : Tensor(out) output : Tensor(out)
inplace : (x -> out) inplace : (x -> out)
...@@ -485,7 +485,7 @@ ...@@ -485,7 +485,7 @@
func : clip func : clip
backward : clip_grad backward : clip_grad
- api : clip_by_norm - op : clip_by_norm
args : (Tensor x, float max_norm) args : (Tensor x, float max_norm)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -493,7 +493,7 @@ ...@@ -493,7 +493,7 @@
kernel : kernel :
func : clip_by_norm func : clip_by_norm
- api : coalesce_tensor - op : coalesce_tensor
args : (Tensor[] input, DataType dtype, bool copy_data = false, bool set_constant = false, bool persist_output = false, float constant = 0.0, bool use_align = true, int align_size = -1, int size_of_dtype = -1, int64_t[] concated_shapes = {}, int64_t[] concated_ranks = {}) args : (Tensor[] input, DataType dtype, bool copy_data = false, bool set_constant = false, bool persist_output = false, float constant = 0.0, bool use_align = true, int align_size = -1, int size_of_dtype = -1, int64_t[] concated_shapes = {}, int64_t[] concated_ranks = {})
output : Tensor[](output){input.size()}, Tensor(fused_output) output : Tensor[](output){input.size()}, Tensor(fused_output)
infer_meta : infer_meta :
...@@ -502,7 +502,7 @@ ...@@ -502,7 +502,7 @@
func : coalesce_tensor func : coalesce_tensor
data_type : dtype data_type : dtype
- api : complex - op : complex
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -511,7 +511,7 @@ ...@@ -511,7 +511,7 @@
func : complex func : complex
backward : complex_grad backward : complex_grad
- api : concat - op : concat
args : (Tensor[] x, Scalar(int64_t) axis) args : (Tensor[] x, Scalar(int64_t) axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -521,7 +521,7 @@ ...@@ -521,7 +521,7 @@
func : concat func : concat
backward : concat_grad backward : concat_grad
- api : conj - op : conj
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -530,7 +530,7 @@ ...@@ -530,7 +530,7 @@
func : conj func : conj
backward : conj_grad backward : conj_grad
- api : conv2d - op : conv2d
args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -540,7 +540,7 @@ ...@@ -540,7 +540,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv2d_grad backward : conv2d_grad
- api : conv2d_transpose - op : conv2d_transpose
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -550,7 +550,7 @@ ...@@ -550,7 +550,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv2d_transpose_grad backward : conv2d_transpose_grad
- api : conv3d - op : conv3d
args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search) args : (Tensor input, Tensor filter, int[] strides, int[] paddings, str paddding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -560,7 +560,7 @@ ...@@ -560,7 +560,7 @@
use_gpudnn : true use_gpudnn : true
backward : conv3d_grad backward : conv3d_grad
- api : conv3d_transpose - op : conv3d_transpose
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, int[] output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -570,12 +570,12 @@ ...@@ -570,12 +570,12 @@
use_gpudnn : true use_gpudnn : true
backward : conv3d_transpose_grad backward : conv3d_transpose_grad
- api : copy_to - op : copy_to
args : (Tensor x, Place place, bool blocking) args : (Tensor x, Place place, bool blocking)
output : Tensor(out) output : Tensor(out)
invoke : copy_to_impl(x, place, blocking) invoke : copy_to_impl(x, place, blocking)
- api : cos - op : cos
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -584,7 +584,7 @@ ...@@ -584,7 +584,7 @@
func : cos func : cos
backward : cos_grad backward : cos_grad
- api : cosh - op : cosh
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -593,7 +593,7 @@ ...@@ -593,7 +593,7 @@
func : cosh func : cosh
backward : cosh_grad backward : cosh_grad
- api : crop_tensor - op : crop_tensor
args : (Tensor x, IntArray shape, IntArray offsets) args : (Tensor x, IntArray shape, IntArray offsets)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -604,7 +604,7 @@ ...@@ -604,7 +604,7 @@
backward : crop_tensor_grad backward : crop_tensor_grad
# Part of python API paddle.nn.functional.cross_entropy # Part of python API paddle.nn.functional.cross_entropy
- api : cross_entropy_with_softmax - op : cross_entropy_with_softmax
args : (Tensor input, Tensor label, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis) args : (Tensor input, Tensor label, bool soft_label, bool use_softmax, bool numeric_stable_mode, int ignore_index, int axis)
output : Tensor(softmax), Tensor(loss) output : Tensor(softmax), Tensor(loss)
infer_meta : infer_meta :
...@@ -614,7 +614,7 @@ ...@@ -614,7 +614,7 @@
data_type : input data_type : input
backward : cross_entropy_with_softmax_grad backward : cross_entropy_with_softmax_grad
- api : cumprod - op : cumprod
args : (Tensor x, int dim) args : (Tensor x, int dim)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -624,7 +624,7 @@ ...@@ -624,7 +624,7 @@
func : cumprod func : cumprod
backward : cumprod_grad backward : cumprod_grad
- api : cumsum - op : cumsum
args : (Tensor x, Scalar axis, bool flatten, bool exclusive, bool reverse) args : (Tensor x, Scalar axis, bool flatten, bool exclusive, bool reverse)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -633,7 +633,7 @@ ...@@ -633,7 +633,7 @@
func : cumsum func : cumsum
backward : cumsum_grad backward : cumsum_grad
- api : decode_jpeg - op : decode_jpeg
args : (Tensor x, str mode) args : (Tensor x, str mode)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -641,7 +641,7 @@ ...@@ -641,7 +641,7 @@
kernel : kernel :
func : decode_jpeg func : decode_jpeg
- api : deformable_conv - op : deformable_conv
args : (Tensor x, Tensor offset, Tensor filter, Tensor mask, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step) args : (Tensor x, Tensor offset, Tensor filter, Tensor mask, int[] strides, int[] paddings, int[] dilations, int deformable_groups, int groups, int im2col_step)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -652,7 +652,7 @@ ...@@ -652,7 +652,7 @@
optional : mask optional : mask
backward : deformable_conv_grad backward : deformable_conv_grad
- api : depthwise_conv2d - op : depthwise_conv2d
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn) args : (Tensor x, Tensor filter, int[] strides, int[] paddings, str padding_algorithm, int groups, int[] dilations, str data_format, bool use_addto, int workspace_size_MB, bool exhaustive_search, bool fuse_relu, bool use_gpudnn)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -664,7 +664,7 @@ ...@@ -664,7 +664,7 @@
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
backward : depthwise_conv2d_grad backward : depthwise_conv2d_grad
- api : depthwise_conv2d_transpose - op : depthwise_conv2d_transpose
args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format) args : (Tensor x, Tensor filter, int[] strides, int[] paddings, int[] output_padding, IntArray output_size, str padding_algorithm, int groups, int[] dilations, str data_format)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -673,7 +673,7 @@ ...@@ -673,7 +673,7 @@
func : depthwise_conv2d_transpose func : depthwise_conv2d_transpose
backward : depthwise_conv2d_transpose_grad backward : depthwise_conv2d_transpose_grad
- api : det - op : det
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -682,7 +682,7 @@ ...@@ -682,7 +682,7 @@
func : determinant func : determinant
backward : det_grad backward : det_grad
- api : diag_embed - op : diag_embed
args : (Tensor x, int offset, int dim1, int dim2) args : (Tensor x, int offset, int dim1, int dim2)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -690,7 +690,7 @@ ...@@ -690,7 +690,7 @@
kernel : kernel :
func : diag_embed func : diag_embed
- api : distribute_fpn_proposals - op : distribute_fpn_proposals
args : (Tensor fpn_rois, Tensor rois_num, int min_level, int max_level, int refer_level, int refer_scale, bool pixel_offset) args : (Tensor fpn_rois, Tensor rois_num, int min_level, int max_level, int refer_level, int refer_scale, bool pixel_offset)
output : Tensor[](multi_fpn_rois){max_level - min_level + 1}, Tensor[](multi_level_rois_num){max_level - min_level + 1}, Tensor(restore_index) output : Tensor[](multi_fpn_rois){max_level - min_level + 1}, Tensor[](multi_level_rois_num){max_level - min_level + 1}, Tensor(restore_index)
infer_meta : infer_meta :
...@@ -700,7 +700,7 @@ ...@@ -700,7 +700,7 @@
data_type : fpn_rois data_type : fpn_rois
optional : rois_num optional : rois_num
- api : divide - op : divide
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -709,7 +709,7 @@ ...@@ -709,7 +709,7 @@
func : divide func : divide
backward : divide_grad backward : divide_grad
- api : dropout - op : dropout
args : (Tensor x, Tensor seed_tensor, Scalar p, bool is_test, str mode, int seed, bool fix_seed) args : (Tensor x, Tensor seed_tensor, Scalar p, bool is_test, str mode, int seed, bool fix_seed)
output : Tensor(out), Tensor(mask) output : Tensor(out), Tensor(mask)
infer_meta : infer_meta :
...@@ -720,7 +720,7 @@ ...@@ -720,7 +720,7 @@
optional : seed_tensor optional : seed_tensor
backward : dropout_grad backward : dropout_grad
- api : edit_distance - op : edit_distance
args : (Tensor hyps, Tensor refs, Tensor hypslength, Tensor refslength, bool normalized = false) args : (Tensor hyps, Tensor refs, Tensor hypslength, Tensor refslength, bool normalized = false)
output : Tensor(sequencenum), Tensor(out) output : Tensor(sequencenum), Tensor(out)
infer_meta : infer_meta :
...@@ -730,7 +730,7 @@ ...@@ -730,7 +730,7 @@
data_type: DataType::FLOAT32 data_type: DataType::FLOAT32
optional : hypslength, refslength optional : hypslength, refslength
- api : eigh - op : eigh
args : (Tensor x, str uplo) args : (Tensor x, str uplo)
output : Tensor(out_w), Tensor(out_v) output : Tensor(out_w), Tensor(out_v)
infer_meta : infer_meta :
...@@ -739,7 +739,7 @@ ...@@ -739,7 +739,7 @@
func : eigh func : eigh
backward : eigh_grad backward : eigh_grad
- api : eigvals - op : eigvals
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -747,7 +747,7 @@ ...@@ -747,7 +747,7 @@
kernel : kernel :
func : eigvals func : eigvals
- api : eigvalsh - op : eigvalsh
args : (Tensor x, str uplo, bool is_test) args : (Tensor x, str uplo, bool is_test)
output : Tensor(eigenvalues), Tensor(eigenvectors) output : Tensor(eigenvalues), Tensor(eigenvectors)
infer_meta : infer_meta :
...@@ -756,7 +756,7 @@ ...@@ -756,7 +756,7 @@
func : eigvalsh func : eigvalsh
backward : eigvalsh_grad backward : eigvalsh_grad
- api : einsum - op : einsum
args : (Tensor[] x, str equation) args : (Tensor[] x, str equation)
output : Tensor, Tensor[]{x.size()}, Tensor[]{x.size()} output : Tensor, Tensor[]{x.size()}, Tensor[]{x.size()}
infer_meta : infer_meta :
...@@ -766,7 +766,7 @@ ...@@ -766,7 +766,7 @@
func : einsum_raw func : einsum_raw
backward : einsum_grad backward : einsum_grad
- api : elementwise_pow - op : elementwise_pow
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -775,7 +775,7 @@ ...@@ -775,7 +775,7 @@
func : elementwise_pow func : elementwise_pow
backward : elementwise_pow_grad backward : elementwise_pow_grad
- api : elu - op : elu
args : (Tensor x, float alpha) args : (Tensor x, float alpha)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -786,13 +786,13 @@ ...@@ -786,13 +786,13 @@
inplace : (x -> out) inplace : (x -> out)
backward : elu_grad backward : elu_grad
- api : embedding - op : embedding
args : (Tensor x, Tensor weight, int64_t padding_idx=-1, bool sparse=false) args : (Tensor x, Tensor weight, int64_t padding_idx=-1, bool sparse=false)
output : Tensor output : Tensor
invoke : embedding_impl(x, weight, padding_idx, sparse) invoke : embedding_impl(x, weight, padding_idx, sparse)
backward : embedding_grad backward : embedding_grad
- api : empty - op : empty
args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()) args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace())
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -804,7 +804,7 @@ ...@@ -804,7 +804,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : empty_like - op : empty_like
args : (Tensor x, DataType dtype = DataType::UNDEFINED, Place place = {}) args : (Tensor x, DataType dtype = DataType::UNDEFINED, Place place = {})
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -816,7 +816,7 @@ ...@@ -816,7 +816,7 @@
data_type : dtype > x data_type : dtype > x
backend : place > x backend : place > x
- api : equal - op : equal
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -824,7 +824,7 @@ ...@@ -824,7 +824,7 @@
kernel : kernel :
func : equal func : equal
- api : equal_all - op : equal_all
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -832,7 +832,7 @@ ...@@ -832,7 +832,7 @@
kernel : kernel :
func : equal_all func : equal_all
- api : exp - op : exp
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -842,7 +842,7 @@ ...@@ -842,7 +842,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : exp_grad backward : exp_grad
- api : expand - op : expand
args : (Tensor x, IntArray shape) args : (Tensor x, IntArray shape)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -851,7 +851,7 @@ ...@@ -851,7 +851,7 @@
func : expand func : expand
backward : expand_grad backward : expand_grad
- api : expand_as - op : expand_as
args : (Tensor x, Tensor y, int[] target_shape) args : (Tensor x, Tensor y, int[] target_shape)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -861,7 +861,7 @@ ...@@ -861,7 +861,7 @@
optional : y optional : y
backward : expand_as_grad backward : expand_as_grad
- api : expm1 - op : expm1
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -871,7 +871,7 @@ ...@@ -871,7 +871,7 @@
func : expm1 func : expm1
backward : expm1_grad backward : expm1_grad
- api : exponential_ - op : exponential_
args : (Tensor x, float lambda) args : (Tensor x, float lambda)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -882,7 +882,7 @@ ...@@ -882,7 +882,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : exponential__grad backward : exponential__grad
- api : eye - op : eye
args : (Scalar num_rows, Scalar num_columns, DataType dtype=DataType::FLOAT32, Place place={}) args : (Scalar num_rows, Scalar num_columns, DataType dtype=DataType::FLOAT32, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -894,7 +894,7 @@ ...@@ -894,7 +894,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : fill - op : fill
args : (Tensor x, Scalar value) args : (Tensor x, Scalar value)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -905,7 +905,7 @@ ...@@ -905,7 +905,7 @@
inplace : (x -> out) inplace : (x -> out)
backward: fill_grad backward: fill_grad
- api : fill_diagonal - op : fill_diagonal
args : (Tensor x, float value, int offset, bool wrap) args : (Tensor x, float value, int offset, bool wrap)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -915,7 +915,7 @@ ...@@ -915,7 +915,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : fill_diagonal_grad backward : fill_diagonal_grad
- api : fill_diagonal_tensor - op : fill_diagonal_tensor
args : (Tensor x, Tensor y, int64_t offset, int dim1, int dim2) args : (Tensor x, Tensor y, int64_t offset, int dim1, int dim2)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -925,7 +925,7 @@ ...@@ -925,7 +925,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : fill_diagonal_tensor_grad backward : fill_diagonal_tensor_grad
- api : flatten - op : flatten
args : (Tensor x, int start_axis, int stop_axis) args : (Tensor x, int start_axis, int stop_axis)
output : Tensor(out), Tensor(xshape) output : Tensor(out), Tensor(xshape)
infer_meta : infer_meta :
...@@ -938,7 +938,7 @@ ...@@ -938,7 +938,7 @@
intermediate : xshape intermediate : xshape
backward : flatten_grad backward : flatten_grad
- api : flip - op : flip
args : (Tensor x, int[] axis) args : (Tensor x, int[] axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -947,7 +947,7 @@ ...@@ -947,7 +947,7 @@
func : flip func : flip
backward : flip_grad backward : flip_grad
- api : floor - op : floor
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -957,7 +957,7 @@ ...@@ -957,7 +957,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : floor_grad backward : floor_grad
- api : floor_divide - op : floor_divide
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -965,7 +965,7 @@ ...@@ -965,7 +965,7 @@
kernel : kernel :
func : floor_divide func : floor_divide
- api : fmax - op : fmax
args : (Tensor x, Tensor y, int axis) args : (Tensor x, Tensor y, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -975,7 +975,7 @@ ...@@ -975,7 +975,7 @@
func : fmax func : fmax
backward : fmax_grad backward : fmax_grad
- api : fmin - op : fmin
args : (Tensor x, Tensor y, int axis) args : (Tensor x, Tensor y, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -985,7 +985,7 @@ ...@@ -985,7 +985,7 @@
func : fmin func : fmin
backward : fmin_grad backward : fmin_grad
- api : frame - op : frame
args : (Tensor x, int frame_length, int hop_length, int axis) args : (Tensor x, int frame_length, int hop_length, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -994,7 +994,7 @@ ...@@ -994,7 +994,7 @@
func : frame func : frame
backward : frame_grad backward : frame_grad
- api : frobenius_norm - op : frobenius_norm
args : (Tensor x, int64_t[] axis, bool keep_dim, bool reduce_all) args : (Tensor x, int64_t[] axis, bool keep_dim, bool reduce_all)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1003,7 +1003,7 @@ ...@@ -1003,7 +1003,7 @@
func : frobenius_norm func : frobenius_norm
backward : frobenius_norm_grad backward : frobenius_norm_grad
- api : full - op : full
args : (IntArray shape, Scalar value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()) args : (IntArray shape, Scalar value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace())
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -1015,7 +1015,7 @@ ...@@ -1015,7 +1015,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : full_ - op : full_
args : (Tensor output, IntArray shape, Scalar value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()) args : (Tensor output, IntArray shape, Scalar value, DataType dtype=DataType::FLOAT32, Place place=CPUPlace())
output : Tensor(out) output : Tensor(out)
inplace : (output -> out) inplace : (output -> out)
...@@ -1028,7 +1028,7 @@ ...@@ -1028,7 +1028,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : full_batch_size_like - op : full_batch_size_like
args : (Tensor input, int[] shape, DataType dtype, Scalar value, int input_dim_idx, int output_dim_idx, Place place=CPUPlace()) args : (Tensor input, int[] shape, DataType dtype, Scalar value, int input_dim_idx, int output_dim_idx, Place place=CPUPlace())
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -1040,7 +1040,7 @@ ...@@ -1040,7 +1040,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : full_like - op : full_like
args : (Tensor x, Scalar value, DataType dtype = DataType::UNDEFINED, Place place = {}) args : (Tensor x, Scalar value, DataType dtype = DataType::UNDEFINED, Place place = {})
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -1054,7 +1054,7 @@ ...@@ -1054,7 +1054,7 @@
data_transform : data_transform :
skip_transform : x skip_transform : x
- api : gather - op : gather
args : (Tensor x, Tensor index, Scalar(int) axis=0) args : (Tensor x, Tensor index, Scalar(int) axis=0)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1064,7 +1064,7 @@ ...@@ -1064,7 +1064,7 @@
data_type: x data_type: x
backward : gather_grad backward : gather_grad
- api : gather_nd - op : gather_nd
args : (Tensor x, Tensor index) args : (Tensor x, Tensor index)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1074,7 +1074,7 @@ ...@@ -1074,7 +1074,7 @@
data_type : x data_type : x
backward : gather_nd_grad backward : gather_nd_grad
- api : gather_tree - op : gather_tree
args : (Tensor ids, Tensor parents) args : (Tensor ids, Tensor parents)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1082,7 +1082,7 @@ ...@@ -1082,7 +1082,7 @@
kernel : kernel :
func : gather_tree func : gather_tree
- api : gaussian_random - op : gaussian_random
args : (IntArray shape, float mean, float std, int seed, DataType dtype, Place place={}) args : (IntArray shape, float mean, float std, int seed, DataType dtype, Place place={})
output: Tensor(out) output: Tensor(out)
infer_meta : infer_meta :
...@@ -1094,7 +1094,7 @@ ...@@ -1094,7 +1094,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : gelu - op : gelu
args : (Tensor x, bool approximate) args : (Tensor x, bool approximate)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1104,7 +1104,7 @@ ...@@ -1104,7 +1104,7 @@
func : gelu func : gelu
backward : gelu_grad backward : gelu_grad
- api : generate_proposals_v2 - op : generate_proposals_v2
args : (Tensor scores, Tensor bbox_deltas, Tensor im_shape, Tensor anchors, Tensor variances, int pre_nms_top_n, int post_nms_top_n, float nms_thresh, float min_size, float eta, bool pixel_offset=true) args : (Tensor scores, Tensor bbox_deltas, Tensor im_shape, Tensor anchors, Tensor variances, int pre_nms_top_n, int post_nms_top_n, float nms_thresh, float min_size, float eta, bool pixel_offset=true)
output : Tensor(rpn_rois), Tensor(rpn_roi_probs), Tensor(rpn_rois_num) output : Tensor(rpn_rois), Tensor(rpn_roi_probs), Tensor(rpn_rois_num)
infer_meta : infer_meta :
...@@ -1112,7 +1112,7 @@ ...@@ -1112,7 +1112,7 @@
kernel : kernel :
func : generate_proposals_v2 func : generate_proposals_v2
- api : graph_send_recv - op : graph_send_recv
args : (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0}) args : (Tensor x, Tensor src_index, Tensor dst_index, str reduce_op = "SUM", IntArray out_size = {0})
output : Tensor(out), Tensor(dst_count) output : Tensor(out), Tensor(dst_count)
infer_meta : infer_meta :
...@@ -1123,7 +1123,7 @@ ...@@ -1123,7 +1123,7 @@
intermediate : dst_count intermediate : dst_count
backward : graph_send_recv_grad backward : graph_send_recv_grad
- api : graph_send_ue_recv - op : graph_send_ue_recv
args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op, str reduce_op, IntArray out_size) args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op, str reduce_op, IntArray out_size)
output : Tensor(out), Tensor(dst_count) output : Tensor(out), Tensor(dst_count)
infer_meta : infer_meta :
...@@ -1134,7 +1134,7 @@ ...@@ -1134,7 +1134,7 @@
intermediate : dst_count intermediate : dst_count
backward : graph_send_ue_recv_grad backward : graph_send_ue_recv_grad
- api : greater_equal - op : greater_equal
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1142,7 +1142,7 @@ ...@@ -1142,7 +1142,7 @@
kernel : kernel :
func : greater_equal func : greater_equal
- api : greater_than - op : greater_than
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1150,7 +1150,7 @@ ...@@ -1150,7 +1150,7 @@
kernel : kernel :
func : greater_than func : greater_than
- api : grid_sample - op : grid_sample
args : (Tensor x, Tensor grid, str mode, str padding_mode, bool align_corners) args : (Tensor x, Tensor grid, str mode, str padding_mode, bool align_corners)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1161,7 +1161,7 @@ ...@@ -1161,7 +1161,7 @@
data_type : x data_type : x
backward : grid_sample_grad backward : grid_sample_grad
- api : group_norm - op : group_norm
args : (Tensor x, Tensor scale, Tensor bias, float epsilon, int groups, str data_layout) args : (Tensor x, Tensor scale, Tensor bias, float epsilon, int groups, str data_layout)
output : Tensor(y), Tensor(mean), Tensor(variance) output : Tensor(y), Tensor(mean), Tensor(variance)
infer_meta : infer_meta :
...@@ -1172,7 +1172,7 @@ ...@@ -1172,7 +1172,7 @@
intermediate : mean, variance intermediate : mean, variance
backward : group_norm_grad backward : group_norm_grad
- api : gumbel_softmax - op : gumbel_softmax
args : (Tensor x, float temperature, bool hard, int axis) args : (Tensor x, float temperature, bool hard, int axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1181,7 +1181,7 @@ ...@@ -1181,7 +1181,7 @@
func : gumbel_softmax func : gumbel_softmax
backward : gumbel_softmax_grad backward : gumbel_softmax_grad
- api : hard_shrink - op : hard_shrink
args : (Tensor x, float threshold) args : (Tensor x, float threshold)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1191,7 +1191,7 @@ ...@@ -1191,7 +1191,7 @@
func : hard_shrink func : hard_shrink
backward : hard_shrink_grad backward : hard_shrink_grad
- api : hard_sigmoid - op : hard_sigmoid
args : (Tensor x, float slope, float offset) args : (Tensor x, float slope, float offset)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1201,7 +1201,7 @@ ...@@ -1201,7 +1201,7 @@
func : hard_sigmoid func : hard_sigmoid
backward : hard_sigmoid_grad backward : hard_sigmoid_grad
- api : hard_swish - op : hard_swish
args : (Tensor x, float threshold = 6.0, float scale = 6.0, float offset = 3.0) args : (Tensor x, float threshold = 6.0, float scale = 6.0, float offset = 3.0)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1211,7 +1211,7 @@ ...@@ -1211,7 +1211,7 @@
func : hard_swish func : hard_swish
backward : hard_swish_grad backward : hard_swish_grad
- api : hierarchical_sigmoid - op : hierarchical_sigmoid
args : (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse) args : (Tensor x, Tensor w, Tensor label, Tensor path, Tensor code, Tensor bias, int num_classes, bool remote_prefetch, int trainer_id, int64_t[] height_sections, str[] epmap, str[] table_names, bool is_sparse)
output : Tensor(out), Tensor(pre_out), Tensor(w_out) output : Tensor(out), Tensor(pre_out), Tensor(w_out)
infer_meta : infer_meta :
...@@ -1222,7 +1222,7 @@ ...@@ -1222,7 +1222,7 @@
data_type : x data_type : x
backward : hierarchical_sigmoid_grad backward : hierarchical_sigmoid_grad
- api : histogram - op : histogram
args : (Tensor x, int64_t bins, int min, int max) args : (Tensor x, int64_t bins, int min, int max)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1230,7 +1230,7 @@ ...@@ -1230,7 +1230,7 @@
kernel : kernel :
func : histogram func : histogram
- api : huber_loss - op : huber_loss
args : (Tensor input, Tensor label, float delta) args : (Tensor input, Tensor label, float delta)
output : Tensor(out), Tensor(residual) output : Tensor(out), Tensor(residual)
infer_meta : infer_meta :
...@@ -1239,7 +1239,7 @@ ...@@ -1239,7 +1239,7 @@
func : huber_loss func : huber_loss
backward : huber_loss_grad backward : huber_loss_grad
- api : imag - op : imag
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1248,7 +1248,7 @@ ...@@ -1248,7 +1248,7 @@
func : imag func : imag
backward : imag_grad backward : imag_grad
- api : increment - op : increment
args : (Tensor x, float value) args : (Tensor x, float value)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1257,7 +1257,7 @@ ...@@ -1257,7 +1257,7 @@
func : increment func : increment
inplace : (x -> out) inplace : (x -> out)
- api : index_add - op : index_add
args : (Tensor x, Tensor index, Tensor add_value, int axis) args : (Tensor x, Tensor index, Tensor add_value, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1268,7 +1268,7 @@ ...@@ -1268,7 +1268,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : index_add_grad backward : index_add_grad
- api : index_sample - op : index_sample
args : (Tensor x, Tensor index) args : (Tensor x, Tensor index)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1278,7 +1278,7 @@ ...@@ -1278,7 +1278,7 @@
data_type : x data_type : x
backward : index_sample_grad backward : index_sample_grad
- api : index_select - op : index_select
args : (Tensor x, Tensor index, int dim) args : (Tensor x, Tensor index, int dim)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1288,7 +1288,7 @@ ...@@ -1288,7 +1288,7 @@
data_type : x data_type : x
backward : index_select_grad backward : index_select_grad
- api : instance_norm - op : instance_norm
args : (Tensor x, Tensor scale, Tensor bias, float epsilon) args : (Tensor x, Tensor scale, Tensor bias, float epsilon)
output : Tensor(y), Tensor(saved_mean), Tensor(saved_variance) output : Tensor(y), Tensor(saved_mean), Tensor(saved_variance)
infer_meta : infer_meta :
...@@ -1300,7 +1300,7 @@ ...@@ -1300,7 +1300,7 @@
intermediate : saved_mean, saved_variance intermediate : saved_mean, saved_variance
backward : instance_norm_grad backward : instance_norm_grad
- api : inverse - op : inverse
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1309,7 +1309,7 @@ ...@@ -1309,7 +1309,7 @@
func : inverse func : inverse
backward : inverse_grad backward : inverse_grad
- api : is_empty - op : is_empty
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1317,7 +1317,7 @@ ...@@ -1317,7 +1317,7 @@
kernel : kernel :
func : is_empty func : is_empty
- api : isclose - op : isclose
args : (Tensor x, Tensor y, Scalar rtol, Scalar atol, bool equal_nan) args : (Tensor x, Tensor y, Scalar rtol, Scalar atol, bool equal_nan)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1326,7 +1326,7 @@ ...@@ -1326,7 +1326,7 @@
kernel : kernel :
func : isclose func : isclose
- api : isfinite - op : isfinite
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1335,7 +1335,7 @@ ...@@ -1335,7 +1335,7 @@
func : isfinite {dense -> dense}, func : isfinite {dense -> dense},
infinite_sr {selected_rows -> selected_rows} infinite_sr {selected_rows -> selected_rows}
- api : isinf - op : isinf
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1344,7 +1344,7 @@ ...@@ -1344,7 +1344,7 @@
func : isinf {dense -> dense}, func : isinf {dense -> dense},
isinf_sr {selected_rows -> selected_rows} isinf_sr {selected_rows -> selected_rows}
- api : isnan - op : isnan
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1353,7 +1353,7 @@ ...@@ -1353,7 +1353,7 @@
func : isnan {dense -> dense}, func : isnan {dense -> dense},
isnan_sr {selected_rows -> selected_rows} isnan_sr {selected_rows -> selected_rows}
- api : kldiv_loss - op : kldiv_loss
args : (Tensor x, Tensor label, str reduction) args : (Tensor x, Tensor label, str reduction)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1363,7 +1363,7 @@ ...@@ -1363,7 +1363,7 @@
data_type : x data_type : x
backward : kldiv_loss_grad backward : kldiv_loss_grad
- api : kron - op : kron
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1372,7 +1372,7 @@ ...@@ -1372,7 +1372,7 @@
func : kron func : kron
backward : kron_grad backward : kron_grad
- api : kthvalue - op : kthvalue
args : (Tensor x, int k, int axis, bool keepdim) args : (Tensor x, int k, int axis, bool keepdim)
output : Tensor(out), Tensor(indices) output : Tensor(out), Tensor(indices)
infer_meta : infer_meta :
...@@ -1381,7 +1381,7 @@ ...@@ -1381,7 +1381,7 @@
func : kthvalue func : kthvalue
backward : kthvalue_grad backward : kthvalue_grad
- api : label_smooth - op : label_smooth
args : (Tensor label, Tensor prior_dist, float epsilon) args : (Tensor label, Tensor prior_dist, float epsilon)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1393,7 +1393,7 @@ ...@@ -1393,7 +1393,7 @@
optional : prior_dist optional : prior_dist
backward : label_smooth_grad backward : label_smooth_grad
- api : lamb_ - op : lamb_
args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, float weight_decay, float beta1, float beta2, float epsilon, bool multi_precision) args : (Tensor param, Tensor grad, Tensor learning_rate, Tensor moment1, Tensor moment2, Tensor beta1_pow, Tensor beta2_pow, Tensor master_param, Tensor skip_update, float weight_decay, float beta1, float beta2, float epsilon, bool multi_precision)
output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs) output : Tensor(param_out), Tensor(moment1_out), Tensor(moment2_out), Tensor(beta1_pow_out), Tensor(beta2_pow_out), Tensor(master_param_outs)
infer_meta : infer_meta :
...@@ -1405,7 +1405,7 @@ ...@@ -1405,7 +1405,7 @@
optional : master_param, skip_update optional : master_param, skip_update
inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs) inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_outs)
- api : layer_norm - op : layer_norm
args : (Tensor x, Tensor scale, Tensor bias, float epsilon, int begin_norm_axis, bool is_test) args : (Tensor x, Tensor scale, Tensor bias, float epsilon, int begin_norm_axis, bool is_test)
output : Tensor(out), Tensor(mean), Tensor(variance) output : Tensor(out), Tensor(mean), Tensor(variance)
infer_meta : infer_meta :
...@@ -1416,7 +1416,7 @@ ...@@ -1416,7 +1416,7 @@
backward : layer_norm_grad backward : layer_norm_grad
optional : scale, bias optional : scale, bias
- api : leaky_relu - op : leaky_relu
args : (Tensor x, float alpha) args : (Tensor x, float alpha)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1426,7 +1426,7 @@ ...@@ -1426,7 +1426,7 @@
func : leaky_relu func : leaky_relu
backward : leaky_relu_grad backward : leaky_relu_grad
- api : lerp - op : lerp
args : (Tensor x, Tensor y, Tensor weight) args : (Tensor x, Tensor y, Tensor weight)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1436,7 +1436,7 @@ ...@@ -1436,7 +1436,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : lerp_grad backward : lerp_grad
- api : less_equal - op : less_equal
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1444,7 +1444,7 @@ ...@@ -1444,7 +1444,7 @@
kernel : kernel :
func : less_equal func : less_equal
- api : less_than - op : less_than
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1452,7 +1452,7 @@ ...@@ -1452,7 +1452,7 @@
kernel : kernel :
func : less_than func : less_than
- api : linear_interp - op : linear_interp
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(output) output : Tensor(output)
infer_meta : infer_meta :
...@@ -1463,7 +1463,7 @@ ...@@ -1463,7 +1463,7 @@
data_type : x data_type : x
backward : linear_interp_grad backward : linear_interp_grad
- api : linspace - op : linspace
args : (Tensor start, Tensor stop, Tensor number, DataType dtype) args : (Tensor start, Tensor stop, Tensor number, DataType dtype)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1472,7 +1472,7 @@ ...@@ -1472,7 +1472,7 @@
func : linspace func : linspace
data_type : dtype data_type : dtype
- api : log - op : log
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1481,7 +1481,7 @@ ...@@ -1481,7 +1481,7 @@
func : log func : log
backward: log_grad backward: log_grad
- api : log10 - op : log10
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1490,7 +1490,7 @@ ...@@ -1490,7 +1490,7 @@
func : log10 func : log10
backward: log10_grad backward: log10_grad
- api : log1p - op : log1p
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1499,7 +1499,7 @@ ...@@ -1499,7 +1499,7 @@
func : log1p func : log1p
backward: log1p_grad backward: log1p_grad
- api : log2 - op : log2
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1508,7 +1508,7 @@ ...@@ -1508,7 +1508,7 @@
func : log2 func : log2
backward: log2_grad backward: log2_grad
- api : log_loss - op : log_loss
args : (Tensor input, Tensor label, float epsilon) args : (Tensor input, Tensor label, float epsilon)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1517,7 +1517,7 @@ ...@@ -1517,7 +1517,7 @@
func : log_loss func : log_loss
backward : log_loss_grad backward : log_loss_grad
- api : log_softmax - op : log_softmax
args : (Tensor x, int axis) args : (Tensor x, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1526,7 +1526,7 @@ ...@@ -1526,7 +1526,7 @@
func : log_softmax func : log_softmax
backward : log_softmax_grad backward : log_softmax_grad
- api : logcumsumexp - op : logcumsumexp
args : (Tensor x, int axis, bool flatten, bool exclusive, bool reverse) args : (Tensor x, int axis, bool flatten, bool exclusive, bool reverse)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1535,7 +1535,7 @@ ...@@ -1535,7 +1535,7 @@
func : logcumsumexp func : logcumsumexp
backward : logcumsumexp_grad backward : logcumsumexp_grad
- api : logical_and - op : logical_and
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1543,7 +1543,7 @@ ...@@ -1543,7 +1543,7 @@
kernel : kernel :
func : logical_and func : logical_and
- api : logical_not - op : logical_not
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1551,7 +1551,7 @@ ...@@ -1551,7 +1551,7 @@
kernel : kernel :
func : logical_not func : logical_not
- api : logical_or - op : logical_or
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1559,7 +1559,7 @@ ...@@ -1559,7 +1559,7 @@
kernel : kernel :
func : logical_or func : logical_or
- api : logical_xor - op : logical_xor
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1567,7 +1567,7 @@ ...@@ -1567,7 +1567,7 @@
kernel : kernel :
func : logical_xor func : logical_xor
- api : logit - op : logit
args : (Tensor x, float eps = 1e-6f) args : (Tensor x, float eps = 1e-6f)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1577,7 +1577,7 @@ ...@@ -1577,7 +1577,7 @@
func : logit func : logit
backward : logit_grad backward : logit_grad
- api : logsigmoid - op : logsigmoid
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1586,7 +1586,7 @@ ...@@ -1586,7 +1586,7 @@
func : logsigmoid func : logsigmoid
backward : logsigmoid_grad backward : logsigmoid_grad
- api : logsumexp - op : logsumexp
args : (Tensor x, int64_t[] axis, bool keepdim, bool reduce_all) args : (Tensor x, int64_t[] axis, bool keepdim, bool reduce_all)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1595,7 +1595,7 @@ ...@@ -1595,7 +1595,7 @@
func : logsumexp func : logsumexp
backward : logsumexp_grad backward : logsumexp_grad
- api : lstsq - op : lstsq
args : (Tensor x, Tensor y, Scalar rcond, str driver) args : (Tensor x, Tensor y, Scalar rcond, str driver)
output : Tensor(solution), Tensor(residuals), Tensor(rank), Tensor(singular_values) output : Tensor(solution), Tensor(residuals), Tensor(rank), Tensor(singular_values)
infer_meta : infer_meta :
...@@ -1604,7 +1604,7 @@ ...@@ -1604,7 +1604,7 @@
kernel : kernel :
func : lstsq func : lstsq
- api : lu - op : lu
args : (Tensor x, bool pivot) args : (Tensor x, bool pivot)
output : Tensor(out), Tensor(pivots), Tensor(infos) output : Tensor(out), Tensor(pivots), Tensor(infos)
infer_meta : infer_meta :
...@@ -1613,7 +1613,7 @@ ...@@ -1613,7 +1613,7 @@
func : lu func : lu
backward : lu_grad backward : lu_grad
- api : lu_unpack - op : lu_unpack
args : (Tensor x, Tensor pivots, bool unpack_ludata, bool unpack_pivots) args : (Tensor x, Tensor pivots, bool unpack_ludata, bool unpack_pivots)
output : Tensor(pmat), Tensor(l), Tensor(u) output : Tensor(pmat), Tensor(l), Tensor(u)
infer_meta : infer_meta :
...@@ -1623,7 +1623,7 @@ ...@@ -1623,7 +1623,7 @@
data_type : x data_type : x
backward : lu_unpack_grad backward : lu_unpack_grad
- api : margin_cross_entropy - op : margin_cross_entropy
args : (Tensor logits, Tensor label, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale) args : (Tensor logits, Tensor label, bool return_softmax, int ring_id, int rank, int nranks, float margin1, float margin2, float margin3, float scale)
output : Tensor(softmax), Tensor(loss) output : Tensor(softmax), Tensor(loss)
infer_meta : infer_meta :
...@@ -1633,7 +1633,7 @@ ...@@ -1633,7 +1633,7 @@
data_type : logits data_type : logits
backward : margin_cross_entropy_grad backward : margin_cross_entropy_grad
- api : masked_select - op : masked_select
args : (Tensor x, Tensor mask) args : (Tensor x, Tensor mask)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1643,7 +1643,7 @@ ...@@ -1643,7 +1643,7 @@
data_type : x data_type : x
backward : masked_select_grad backward : masked_select_grad
- api : matmul - op : matmul
args : (Tensor x, Tensor y, bool transpose_x = false, bool transpose_y = false) args : (Tensor x, Tensor y, bool transpose_x = false, bool transpose_y = false)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1652,7 +1652,7 @@ ...@@ -1652,7 +1652,7 @@
func : matmul func : matmul
backward : matmul_grad backward : matmul_grad
- api : matrix_nms - op : matrix_nms
args : (Tensor bboxes, Tensor scores, float score_threshold, int nms_top_k, int keep_top_k, float post_threshold=0., bool use_gaussian = false, float gaussian_sigma = 2.0, int background_label = 0, bool normalized = true) args : (Tensor bboxes, Tensor scores, float score_threshold, int nms_top_k, int keep_top_k, float post_threshold=0., bool use_gaussian = false, float gaussian_sigma = 2.0, int background_label = 0, bool normalized = true)
output : Tensor(out), Tensor(index), Tensor(roisnum) output : Tensor(out), Tensor(index), Tensor(roisnum)
infer_meta : infer_meta :
...@@ -1660,7 +1660,7 @@ ...@@ -1660,7 +1660,7 @@
kernel : kernel :
func : matrix_nms func : matrix_nms
- api : matrix_power - op : matrix_power
args : (Tensor x, int n) args : (Tensor x, int n)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1670,7 +1670,7 @@ ...@@ -1670,7 +1670,7 @@
func : matrix_power func : matrix_power
backward : matrix_power_grad backward : matrix_power_grad
- api : matrix_rank - op : matrix_rank
args : (Tensor x, float tol, bool use_default_tol=true, bool hermitian=false) args : (Tensor x, float tol, bool use_default_tol=true, bool hermitian=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1679,7 +1679,7 @@ ...@@ -1679,7 +1679,7 @@
kernel : kernel :
func : matrix_rank func : matrix_rank
- api : matrix_rank_tol - op : matrix_rank_tol
args : (Tensor x, Tensor atol_tensor, bool use_default_tol=true, bool hermitian=false) args : (Tensor x, Tensor atol_tensor, bool use_default_tol=true, bool hermitian=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1687,7 +1687,7 @@ ...@@ -1687,7 +1687,7 @@
kernel : kernel :
func : matrix_rank_tol func : matrix_rank_tol
- api : max - op : max
args : (Tensor x, IntArray dims={}, bool keep_dim=false) args : (Tensor x, IntArray dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1696,7 +1696,7 @@ ...@@ -1696,7 +1696,7 @@
func : max func : max
backward : max_grad backward : max_grad
- api : max_pool2d_with_index - op : max_pool2d_with_index
args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive)
output : Tensor(out), Tensor(mask) output : Tensor(out), Tensor(mask)
infer_meta : infer_meta :
...@@ -1705,7 +1705,7 @@ ...@@ -1705,7 +1705,7 @@
func : max_pool2d_with_index func : max_pool2d_with_index
backward : max_pool2d_with_index_grad backward : max_pool2d_with_index_grad
- api : max_pool3d_with_index - op : max_pool3d_with_index
args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive) args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool global_pooling, bool adaptive)
output : Tensor(out), Tensor(mask) output : Tensor(out), Tensor(mask)
infer_meta : infer_meta :
...@@ -1714,7 +1714,7 @@ ...@@ -1714,7 +1714,7 @@
func : max_pool3d_with_index func : max_pool3d_with_index
backward : max_pool3d_with_index_grad backward : max_pool3d_with_index_grad
- api : maximum - op : maximum
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1723,7 +1723,7 @@ ...@@ -1723,7 +1723,7 @@
func : maximum func : maximum
backward : maximum_grad backward : maximum_grad
- api : maxout - op : maxout
args : (Tensor x, int groups, int axis) args : (Tensor x, int groups, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1732,7 +1732,7 @@ ...@@ -1732,7 +1732,7 @@
func : maxout func : maxout
backward : maxout_grad backward : maxout_grad
- api : mean - op : mean
args : (Tensor x, IntArray dims={}, bool keep_dim=false) args : (Tensor x, IntArray dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1741,7 +1741,7 @@ ...@@ -1741,7 +1741,7 @@
func : mean func : mean
backward : mean_grad backward : mean_grad
- api : mean_all - op : mean_all
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1750,7 +1750,7 @@ ...@@ -1750,7 +1750,7 @@
func : mean_all func : mean_all
backward : mean_all_grad backward : mean_all_grad
- api : merged_adam_ - op : merged_adam_
args : (Tensor[] param, Tensor[] grad, Tensor[] learning_rate, Tensor[] moment1, Tensor[] moment2, Tensor[] beta1_pow, Tensor[] beta2_pow, Tensor[] master_param, Scalar beta1, Scalar beta2, Scalar epsilon, bool multi_precision, bool use_global_beta_pow) args : (Tensor[] param, Tensor[] grad, Tensor[] learning_rate, Tensor[] moment1, Tensor[] moment2, Tensor[] beta1_pow, Tensor[] beta2_pow, Tensor[] master_param, Scalar beta1, Scalar beta2, Scalar epsilon, bool multi_precision, bool use_global_beta_pow)
output : Tensor[](param_out){param.size()}, Tensor[](moment1_out){param.size()}, Tensor[](moment2_out){param.size()}, Tensor[](beta1_pow_out){param.size()}, Tensor[](beta2_pow_out){param.size()}, Tensor[](master_param_out){param.size()} output : Tensor[](param_out){param.size()}, Tensor[](moment1_out){param.size()}, Tensor[](moment2_out){param.size()}, Tensor[](beta1_pow_out){param.size()}, Tensor[](beta2_pow_out){param.size()}, Tensor[](master_param_out){param.size()}
infer_meta : infer_meta :
...@@ -1761,7 +1761,7 @@ ...@@ -1761,7 +1761,7 @@
data_type : param data_type : param
inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_out) inplace : (param -> param_out), (moment1 -> moment1_out), (moment2 -> moment2_out), (beta1_pow -> beta1_pow_out), (beta2_pow -> beta2_pow_out), (master_param -> master_param_out)
- api : merged_momentum_ - op : merged_momentum_
args : (Tensor[] param, Tensor[] grad, Tensor[] velocity, Tensor[] learning_rate, Tensor[] master_param, float mu, bool use_nesterov = false, str[] regularization_method = {}, float[] regularization_coeff = {}, bool multi_precision = false, float rescale_grad = 1.0f) args : (Tensor[] param, Tensor[] grad, Tensor[] velocity, Tensor[] learning_rate, Tensor[] master_param, float mu, bool use_nesterov = false, str[] regularization_method = {}, float[] regularization_coeff = {}, bool multi_precision = false, float rescale_grad = 1.0f)
output : Tensor[](param_out){param.size()}, Tensor[](velocity_out){param.size()}, Tensor[](master_param_out){param.size()} output : Tensor[](param_out){param.size()}, Tensor[](velocity_out){param.size()}, Tensor[](master_param_out){param.size()}
infer_meta : infer_meta :
...@@ -1772,7 +1772,7 @@ ...@@ -1772,7 +1772,7 @@
data_type : param data_type : param
inplace : (param -> param_out), (velocity -> velocity_out), (master_param -> master_param_out) inplace : (param -> param_out), (velocity -> velocity_out), (master_param -> master_param_out)
- api : meshgrid - op : meshgrid
args : (Tensor[] inputs) args : (Tensor[] inputs)
output : Tensor[]{inputs.size()} output : Tensor[]{inputs.size()}
infer_meta : infer_meta :
...@@ -1781,7 +1781,7 @@ ...@@ -1781,7 +1781,7 @@
func : meshgrid func : meshgrid
backward : meshgrid_grad backward : meshgrid_grad
- api : min - op : min
args : (Tensor x, IntArray dims={}, bool keep_dim=false) args : (Tensor x, IntArray dims={}, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1790,7 +1790,7 @@ ...@@ -1790,7 +1790,7 @@
func : min func : min
backward : min_grad backward : min_grad
- api : minimum - op : minimum
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1799,7 +1799,7 @@ ...@@ -1799,7 +1799,7 @@
func : minimum func : minimum
backward : minimum_grad backward : minimum_grad
- api : mish - op : mish
args : (Tensor x, float lambda) args : (Tensor x, float lambda)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1809,7 +1809,7 @@ ...@@ -1809,7 +1809,7 @@
func : mish func : mish
backward : mish_grad backward : mish_grad
- api : mode - op : mode
args : (Tensor x, int axis, bool keepdim) args : (Tensor x, int axis, bool keepdim)
output : Tensor(out), Tensor(indices) output : Tensor(out), Tensor(indices)
infer_meta : infer_meta :
...@@ -1818,7 +1818,7 @@ ...@@ -1818,7 +1818,7 @@
func : mode func : mode
backward : mode_grad backward : mode_grad
- api : momentum_ - op : momentum_
args : (Tensor param, Tensor grad, Tensor velocity, Tensor learning_rate, Tensor master_param, float mu, bool use_nesterov = false, str regularization_method = "", float regularization_coeff = 0.0, bool multi_precision = false, float rescale_grad = 1.0f) args : (Tensor param, Tensor grad, Tensor velocity, Tensor learning_rate, Tensor master_param, float mu, bool use_nesterov = false, str regularization_method = "", float regularization_coeff = 0.0, bool multi_precision = false, float rescale_grad = 1.0f)
output : Tensor(param_out), Tensor(velocity_out), Tensor(master_param_out) output : Tensor(param_out), Tensor(velocity_out), Tensor(master_param_out)
infer_meta: infer_meta:
...@@ -1829,7 +1829,7 @@ ...@@ -1829,7 +1829,7 @@
optional : master_param optional : master_param
inplace : (param -> param_out), (velocity -> velocity_out), (master_param -> master_param_out) inplace : (param -> param_out), (velocity -> velocity_out), (master_param -> master_param_out)
- api : multi_dot - op : multi_dot
args : (Tensor[] x) args : (Tensor[] x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1838,7 +1838,7 @@ ...@@ -1838,7 +1838,7 @@
func : multi_dot func : multi_dot
backward : multi_dot_grad backward : multi_dot_grad
- api : multiclass_nms3 - op : multiclass_nms3
args : (Tensor bboxes, Tensor scores, Tensor rois_num, float score_threshold, int nms_top_k, int keep_top_k, float nms_threshold=0.3, bool normalized=true, float nms_eta=1.0, int background_label=0) args : (Tensor bboxes, Tensor scores, Tensor rois_num, float score_threshold, int nms_top_k, int keep_top_k, float nms_threshold=0.3, bool normalized=true, float nms_eta=1.0, int background_label=0)
output : Tensor(out), Tensor(index), Tensor(nms_rois_num) output : Tensor(out), Tensor(index), Tensor(nms_rois_num)
infer_meta : infer_meta :
...@@ -1847,7 +1847,7 @@ ...@@ -1847,7 +1847,7 @@
func : multiclass_nms3 func : multiclass_nms3
optional : rois_num optional : rois_num
- api : multinomial - op : multinomial
args : (Tensor x, Scalar num_samples, bool replacement) args : (Tensor x, Scalar num_samples, bool replacement)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1855,7 +1855,7 @@ ...@@ -1855,7 +1855,7 @@
kernel : kernel :
func : multinomial func : multinomial
- api : multiplex - op : multiplex
args : (Tensor[] ins, Tensor ids) args : (Tensor[] ins, Tensor ids)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1865,7 +1865,7 @@ ...@@ -1865,7 +1865,7 @@
data_type : ins data_type : ins
backward : multiplex_grad backward : multiplex_grad
- api : multiply - op : multiply
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1875,7 +1875,7 @@ ...@@ -1875,7 +1875,7 @@
multiply_sr {selected_rows, dense -> selected_rows} multiply_sr {selected_rows, dense -> selected_rows}
backward : multiply_grad backward : multiply_grad
- api : nearest_interp - op : nearest_interp
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(output) output : Tensor(output)
infer_meta : infer_meta :
...@@ -1886,7 +1886,7 @@ ...@@ -1886,7 +1886,7 @@
data_type : x data_type : x
backward : nearest_interp_grad backward : nearest_interp_grad
- api : nll_loss - op : nll_loss
args : (Tensor input, Tensor label, Tensor weight, int64_t ignore_index, str reduction) args : (Tensor input, Tensor label, Tensor weight, int64_t ignore_index, str reduction)
output : Tensor(out), Tensor(total_weight) output : Tensor(out), Tensor(total_weight)
infer_meta : infer_meta :
...@@ -1897,7 +1897,7 @@ ...@@ -1897,7 +1897,7 @@
optional : weight optional : weight
backward : nll_loss_grad backward : nll_loss_grad
- api : nms - op : nms
args : (Tensor x, float threshold) args : (Tensor x, float threshold)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1906,7 +1906,7 @@ ...@@ -1906,7 +1906,7 @@
func : nms func : nms
data_type : x data_type : x
- api : norm - op : norm
args : (Tensor x, int axis, float epsilon, bool is_test) args : (Tensor x, int axis, float epsilon, bool is_test)
output : Tensor(out), Tensor(norm) output : Tensor(out), Tensor(norm)
infer_meta : infer_meta :
...@@ -1915,7 +1915,7 @@ ...@@ -1915,7 +1915,7 @@
func : norm func : norm
backward : norm_grad backward : norm_grad
- api : not_equal - op : not_equal
args : (Tensor x, Tensor y, int axis = -1) args : (Tensor x, Tensor y, int axis = -1)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1923,7 +1923,7 @@ ...@@ -1923,7 +1923,7 @@
kernel : kernel :
func : not_equal func : not_equal
- api : one_hot - op : one_hot
args : (Tensor x, Scalar(int) num_classes) args : (Tensor x, Scalar(int) num_classes)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1931,17 +1931,17 @@ ...@@ -1931,17 +1931,17 @@
kernel : kernel :
func : one_hot func : one_hot
- api : ones - op : ones
args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()) args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace())
output : Tensor(out) output : Tensor(out)
invoke : full(shape, 1, dtype, place) invoke : full(shape, 1, dtype, place)
- api : ones_like - op : ones_like
args : (Tensor x, DataType dtype=DataType::UNDEFINED, Place place={}) args : (Tensor x, DataType dtype=DataType::UNDEFINED, Place place={})
output : Tensor(out) output : Tensor(out)
invoke : full_like(x, 1, dtype, place) invoke : full_like(x, 1, dtype, place)
- api : p_norm - op : p_norm
args : (Tensor x, float porder, int axis, float epsilon, bool keepdim, bool asvector=false) args : (Tensor x, float porder, int axis, float epsilon, bool keepdim, bool asvector=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1950,7 +1950,7 @@ ...@@ -1950,7 +1950,7 @@
func : p_norm func : p_norm
backward : p_norm_grad backward : p_norm_grad
- api : pad - op : pad
args : (Tensor x, int[] paddings, Scalar pad_value) args : (Tensor x, int[] paddings, Scalar pad_value)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1959,7 +1959,7 @@ ...@@ -1959,7 +1959,7 @@
func : pad func : pad
backward : pad_grad backward : pad_grad
- api : pad3d - op : pad3d
args : (Tensor x, IntArray paddings, str mode, float pad_value, str data_format) args : (Tensor x, IntArray paddings, str mode, float pad_value, str data_format)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1968,7 +1968,7 @@ ...@@ -1968,7 +1968,7 @@
func : pad3d func : pad3d
backward : pad3d_grad backward : pad3d_grad
- api : pixel_shuffle - op : pixel_shuffle
args : (Tensor x, int upscale_factor, str data_format) args : (Tensor x, int upscale_factor, str data_format)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -1977,7 +1977,7 @@ ...@@ -1977,7 +1977,7 @@
func : pixel_shuffle func : pixel_shuffle
backward : pixel_shuffle_grad backward : pixel_shuffle_grad
- api : pool2d - op : pool2d
args : (Tensor x, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) args : (Tensor x, IntArray kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -1989,7 +1989,7 @@ ...@@ -1989,7 +1989,7 @@
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
backward : pool2d_grad backward : pool2d_grad
- api : pool3d - op : pool3d
args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn) args : (Tensor x, int[] kernel_size, int[] strides, int[] paddings, bool ceil_mode, bool exclusive, str data_format, str pooling_type, bool global_pooling, bool adaptive, str padding_algorithm, bool use_gpudnn)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2001,7 +2001,7 @@ ...@@ -2001,7 +2001,7 @@
use_gpudnn : use_gpudnn use_gpudnn : use_gpudnn
backward : pool3d_grad backward : pool3d_grad
- api : pow - op : pow
args : (Tensor x, Scalar s) args : (Tensor x, Scalar s)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2011,7 +2011,7 @@ ...@@ -2011,7 +2011,7 @@
func : pow func : pow
backward : pow_grad backward : pow_grad
- api : prelu - op : prelu
args : (Tensor x, Tensor alpha, str data_format, str mode) args : (Tensor x, Tensor alpha, str data_format, str mode)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2020,7 +2020,7 @@ ...@@ -2020,7 +2020,7 @@
func : prelu func : prelu
backward : prelu_grad backward : prelu_grad
- api : prior_box - op : prior_box
args : (Tensor input, Tensor image, float[] min_sizes, float[] aspect_ratios, float[] variances, float[] max_sizes = {}, bool flip=true, bool clip=true, float step_w=0.0, float step_h=0.0, float offset=0.5, bool min_max_aspect_ratios_order=false) args : (Tensor input, Tensor image, float[] min_sizes, float[] aspect_ratios, float[] variances, float[] max_sizes = {}, bool flip=true, bool clip=true, float step_w=0.0, float step_h=0.0, float offset=0.5, bool min_max_aspect_ratios_order=false)
output : Tensor(out), Tensor(var) output : Tensor(out), Tensor(var)
infer_meta : infer_meta :
...@@ -2028,7 +2028,7 @@ ...@@ -2028,7 +2028,7 @@
kernel : kernel :
func : prior_box func : prior_box
- api : psroi_pool - op : psroi_pool
args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, int output_channels, float spatial_scale) args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, int output_channels, float spatial_scale)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2039,7 +2039,7 @@ ...@@ -2039,7 +2039,7 @@
optional : boxes_num optional : boxes_num
backward : psroi_pool_grad backward : psroi_pool_grad
- api : put_along_axis - op : put_along_axis
args : (Tensor x, Tensor index, Tensor value, int axis, str reduce) args : (Tensor x, Tensor index, Tensor value, int axis, str reduce)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2051,7 +2051,7 @@ ...@@ -2051,7 +2051,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : put_along_axis_grad backward : put_along_axis_grad
- api : qr - op : qr
args : (Tensor x, str mode) args : (Tensor x, str mode)
output : Tensor(q), Tensor(r) output : Tensor(q), Tensor(r)
infer_meta : infer_meta :
...@@ -2060,7 +2060,7 @@ ...@@ -2060,7 +2060,7 @@
func : qr func : qr
backward : qr_grad backward : qr_grad
- api : randint - op : randint
args : (int low, int high, IntArray shape, DataType dtype=DataType::INT64, Place place={}) args : (int low, int high, IntArray shape, DataType dtype=DataType::INT64, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2072,7 +2072,7 @@ ...@@ -2072,7 +2072,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : randperm - op : randperm
args : (int n, DataType dtype, Place place={}) args : (int n, DataType dtype, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2084,7 +2084,7 @@ ...@@ -2084,7 +2084,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : real - op : real
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2093,7 +2093,7 @@ ...@@ -2093,7 +2093,7 @@
func : real func : real
backward : real_grad backward : real_grad
- api : reciprocal - op : reciprocal
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2103,7 +2103,7 @@ ...@@ -2103,7 +2103,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : reciprocal_grad backward : reciprocal_grad
- api : reduce_prod - op : reduce_prod
args : (Tensor x, IntArray dims, bool keep_dim, bool reduce_all) args : (Tensor x, IntArray dims, bool keep_dim, bool reduce_all)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2112,7 +2112,7 @@ ...@@ -2112,7 +2112,7 @@
func : prod_raw func : prod_raw
backward : reduce_prod_grad backward : reduce_prod_grad
- api : relu - op : relu
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2122,7 +2122,7 @@ ...@@ -2122,7 +2122,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : relu_grad backward : relu_grad
- api : relu6 - op : relu6
args : (Tensor x, float threshold) args : (Tensor x, float threshold)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2132,7 +2132,7 @@ ...@@ -2132,7 +2132,7 @@
func : relu6 func : relu6
backward : relu6_grad backward : relu6_grad
- api : remainder - op : remainder
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2141,7 +2141,7 @@ ...@@ -2141,7 +2141,7 @@
func : remainder func : remainder
inplace : (x -> out) inplace : (x -> out)
- api : renorm - op : renorm
args : (Tensor x, float p, int axis, float max_norm) args : (Tensor x, float p, int axis, float max_norm)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2151,7 +2151,7 @@ ...@@ -2151,7 +2151,7 @@
func : renorm func : renorm
backward : renorm_grad backward : renorm_grad
- api : repeat_interleave - op : repeat_interleave
args : (Tensor x, int repeats, int dim) args : (Tensor x, int repeats, int dim)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2161,7 +2161,7 @@ ...@@ -2161,7 +2161,7 @@
func : repeat_interleave func : repeat_interleave
backward: repeat_interleave_grad backward: repeat_interleave_grad
- api : repeat_interleave_with_tensor_index - op : repeat_interleave_with_tensor_index
args : (Tensor x, Tensor repeats, int dim) args : (Tensor x, Tensor repeats, int dim)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2172,7 +2172,7 @@ ...@@ -2172,7 +2172,7 @@
data_type : x data_type : x
backward: repeat_interleave_with_tensor_index_grad backward: repeat_interleave_with_tensor_index_grad
- api : reshape - op : reshape
args : (Tensor x, IntArray shape) args : (Tensor x, IntArray shape)
output : Tensor(out), Tensor(xshape) output : Tensor(out), Tensor(xshape)
infer_meta : infer_meta :
...@@ -2184,7 +2184,7 @@ ...@@ -2184,7 +2184,7 @@
intermediate : xshape intermediate : xshape
backward: reshape_grad backward: reshape_grad
- api : reverse - op : reverse
args : (Tensor x, IntArray axis) args : (Tensor x, IntArray axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2193,7 +2193,7 @@ ...@@ -2193,7 +2193,7 @@
func : reverse func : reverse
backward : reverse_grad backward : reverse_grad
- api : rmsprop_ - op : rmsprop_
args : (Tensor param, Tensor mean_square, Tensor grad, Tensor moment, Tensor learning_rate, Tensor mean_grad, float epsilon, float decay, float momentum, bool centered) args : (Tensor param, Tensor mean_square, Tensor grad, Tensor moment, Tensor learning_rate, Tensor mean_grad, float epsilon, float decay, float momentum, bool centered)
output : Tensor(param_out), Tensor(moment_out), Tensor(mean_square_out), Tensor(mean_grad_out) output : Tensor(param_out), Tensor(moment_out), Tensor(mean_square_out), Tensor(mean_grad_out)
infer_meta : infer_meta :
...@@ -2204,7 +2204,7 @@ ...@@ -2204,7 +2204,7 @@
optional : mean_grad optional : mean_grad
inplace : (param -> param_out), (moment -> moment_out), (mean_square -> mean_square_out), (mean_grad -> mean_grad_out) inplace : (param -> param_out), (moment -> moment_out), (mean_square -> mean_square_out), (mean_grad -> mean_grad_out)
- api : roi_align - op : roi_align
args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned) args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale, int sampling_ratio, bool aligned)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2215,7 +2215,7 @@ ...@@ -2215,7 +2215,7 @@
optional : boxes_num optional : boxes_num
backward : roi_align_grad backward : roi_align_grad
- api : roi_pool - op : roi_pool
args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale) args : (Tensor x, Tensor boxes, Tensor boxes_num, int pooled_height, int pooled_width, float spatial_scale)
output : Tensor(out), Tensor(arg_max) output : Tensor(out), Tensor(arg_max)
infer_meta : infer_meta :
...@@ -2227,7 +2227,7 @@ ...@@ -2227,7 +2227,7 @@
intermediate : arg_max intermediate : arg_max
backward : roi_pool_grad backward : roi_pool_grad
- api : roll - op : roll
args : (Tensor x, IntArray shifts, int64_t[] axis) args : (Tensor x, IntArray shifts, int64_t[] axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2236,7 +2236,7 @@ ...@@ -2236,7 +2236,7 @@
func : roll func : roll
backward : roll_grad backward : roll_grad
- api : round - op : round
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2246,7 +2246,7 @@ ...@@ -2246,7 +2246,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : round_grad backward : round_grad
- api : rsqrt - op : rsqrt
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2256,7 +2256,7 @@ ...@@ -2256,7 +2256,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : rsqrt_grad backward : rsqrt_grad
- api : scale - op : scale
args : (Tensor x, Scalar scale, float bias, bool bias_after_scale) args : (Tensor x, Scalar scale, float bias, bool bias_after_scale)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2268,7 +2268,7 @@ ...@@ -2268,7 +2268,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : scale_grad backward : scale_grad
- api : scatter - op : scatter
args : (Tensor x, Tensor index, Tensor updates, bool overwrite) args : (Tensor x, Tensor index, Tensor updates, bool overwrite)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2279,7 +2279,7 @@ ...@@ -2279,7 +2279,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : scatter_grad backward : scatter_grad
- api : scatter_nd_add - op : scatter_nd_add
args : (Tensor x, Tensor index, Tensor updates) args : (Tensor x, Tensor index, Tensor updates)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2289,7 +2289,7 @@ ...@@ -2289,7 +2289,7 @@
func : scatter_nd_add func : scatter_nd_add
backward : scatter_nd_add_grad backward : scatter_nd_add_grad
- api : searchsorted - op : searchsorted
args : (Tensor sorted_sequence, Tensor value, bool out_int32, bool right) args : (Tensor sorted_sequence, Tensor value, bool out_int32, bool right)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2298,7 +2298,7 @@ ...@@ -2298,7 +2298,7 @@
func : searchsorted func : searchsorted
data_type : sorted_sequence data_type : sorted_sequence
- api : segment_pool - op : segment_pool
args : (Tensor x, Tensor segment_ids, str pooltype) args : (Tensor x, Tensor segment_ids, str pooltype)
output : Tensor(out), Tensor(summed_ids) output : Tensor(out), Tensor(summed_ids)
infer_meta : infer_meta :
...@@ -2308,7 +2308,7 @@ ...@@ -2308,7 +2308,7 @@
data_type : x data_type : x
backward : segment_pool_grad backward : segment_pool_grad
- api : selu - op : selu
args : (Tensor x, float scale, float alpha) args : (Tensor x, float scale, float alpha)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2318,7 +2318,7 @@ ...@@ -2318,7 +2318,7 @@
func : selu func : selu
backward : selu_grad backward : selu_grad
- api : sgd_ - op : sgd_
args : (Tensor param, Tensor learning_rate, Tensor grad, Tensor master_param, bool multi_precision) args : (Tensor param, Tensor learning_rate, Tensor grad, Tensor master_param, bool multi_precision)
output : Tensor(param_out), Tensor(master_param_out) output : Tensor(param_out), Tensor(master_param_out)
infer_meta : infer_meta :
...@@ -2333,7 +2333,7 @@ ...@@ -2333,7 +2333,7 @@
optional : master_param optional : master_param
inplace : (param -> param_out), (master_param -> master_param_out) inplace : (param -> param_out), (master_param -> master_param_out)
- api : shape - op : shape
args : (Tensor input) args : (Tensor input)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2344,7 +2344,7 @@ ...@@ -2344,7 +2344,7 @@
data_transform: data_transform:
skip_transform : input skip_transform : input
- api : shard_index - op : shard_index
args : (Tensor in, int index_num, int nshards, int shard_id, int ignore_value) args : (Tensor in, int index_num, int nshards, int shard_id, int ignore_value)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2352,7 +2352,7 @@ ...@@ -2352,7 +2352,7 @@
kernel : kernel :
func : shard_index func : shard_index
- api : sigmoid - op : sigmoid
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2361,7 +2361,7 @@ ...@@ -2361,7 +2361,7 @@
func : sigmoid func : sigmoid
backward : sigmoid_grad backward : sigmoid_grad
- api : sigmoid_cross_entropy_with_logits - op : sigmoid_cross_entropy_with_logits
args : (Tensor x, Tensor label, bool normalize, int ignore_index) args : (Tensor x, Tensor label, bool normalize, int ignore_index)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2370,7 +2370,7 @@ ...@@ -2370,7 +2370,7 @@
func : sigmoid_cross_entropy_with_logits func : sigmoid_cross_entropy_with_logits
backward : sigmoid_cross_entropy_with_logits_grad backward : sigmoid_cross_entropy_with_logits_grad
- api : sign - op : sign
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2378,7 +2378,7 @@ ...@@ -2378,7 +2378,7 @@
kernel : kernel :
func : sign func : sign
- api : silu - op : silu
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2387,7 +2387,7 @@ ...@@ -2387,7 +2387,7 @@
func : silu func : silu
backward : silu_grad backward : silu_grad
- api : sin - op : sin
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2396,7 +2396,7 @@ ...@@ -2396,7 +2396,7 @@
func : sin func : sin
backward : sin_grad backward : sin_grad
- api : sinh - op : sinh
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2405,7 +2405,7 @@ ...@@ -2405,7 +2405,7 @@
func : sinh func : sinh
backward : sinh_grad backward : sinh_grad
- api : size - op : size
args : (Tensor x) args : (Tensor x)
output : Tensor(size) output : Tensor(size)
infer_meta : infer_meta :
...@@ -2415,7 +2415,7 @@ ...@@ -2415,7 +2415,7 @@
data_transform: data_transform:
skip_transform : x skip_transform : x
- api : slice - op : slice
args : (Tensor input, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis) args : (Tensor input, int64_t[] axes, IntArray starts, IntArray ends, int64_t[] infer_flags, int64_t[] decrease_axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2424,7 +2424,7 @@ ...@@ -2424,7 +2424,7 @@
func : slice func : slice
backward : slice_grad backward : slice_grad
- api : slogdet - op : slogdet
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2433,7 +2433,7 @@ ...@@ -2433,7 +2433,7 @@
func : slogdeterminant func : slogdeterminant
backward : slogdet_grad backward : slogdet_grad
- api : soft_shrink - op : soft_shrink
args : (Tensor x, float lambda) args : (Tensor x, float lambda)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2443,7 +2443,7 @@ ...@@ -2443,7 +2443,7 @@
func : soft_shrink func : soft_shrink
backward : soft_shrink_grad backward : soft_shrink_grad
- api : softmax - op : softmax
args : (Tensor x, int axis) args : (Tensor x, int axis)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2454,7 +2454,7 @@ ...@@ -2454,7 +2454,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : softmax_grad backward : softmax_grad
- api : softplus - op : softplus
args : (Tensor x, float beta, float threshold) args : (Tensor x, float beta, float threshold)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2464,7 +2464,7 @@ ...@@ -2464,7 +2464,7 @@
func : softplus func : softplus
backward : softplus_grad backward : softplus_grad
- api : softsign - op : softsign
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2474,7 +2474,7 @@ ...@@ -2474,7 +2474,7 @@
func : softsign func : softsign
backward : softsign_grad backward : softsign_grad
- api : spectral_norm - op : spectral_norm
args : (Tensor weight, Tensor u, Tensor v, int dim, int power_iters, float eps) args : (Tensor weight, Tensor u, Tensor v, int dim, int power_iters, float eps)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2484,7 +2484,7 @@ ...@@ -2484,7 +2484,7 @@
data_type : weight data_type : weight
backward : spectral_norm_grad backward : spectral_norm_grad
- api : split - op : split
args : (Tensor x, IntArray sections, Scalar(int) axis) args : (Tensor x, IntArray sections, Scalar(int) axis)
output : Tensor[]{sections.size()} output : Tensor[]{sections.size()}
infer_meta : infer_meta :
...@@ -2493,7 +2493,7 @@ ...@@ -2493,7 +2493,7 @@
func : split func : split
backward : split_grad backward : split_grad
- api : split_with_num - op : split_with_num
args : (Tensor x, int num, Scalar(int) axis) args : (Tensor x, int num, Scalar(int) axis)
output : Tensor[]{num} output : Tensor[]{num}
infer_meta : infer_meta :
...@@ -2502,7 +2502,7 @@ ...@@ -2502,7 +2502,7 @@
func : split_with_num func : split_with_num
backward : split_with_num_grad backward : split_with_num_grad
- api : sqrt - op : sqrt
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2512,7 +2512,7 @@ ...@@ -2512,7 +2512,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : sqrt_grad backward : sqrt_grad
- api : square - op : square
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2521,7 +2521,7 @@ ...@@ -2521,7 +2521,7 @@
func : square func : square
backward : square_grad backward : square_grad
- api : squared_l2_norm - op : squared_l2_norm
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2530,7 +2530,7 @@ ...@@ -2530,7 +2530,7 @@
func : squared_l2_norm func : squared_l2_norm
backward : squared_l2_norm_grad backward : squared_l2_norm_grad
- api : squeeze - op : squeeze
args : (Tensor x, IntArray axes) args : (Tensor x, IntArray axes)
output : Tensor(out), Tensor(xshape) output : Tensor(out), Tensor(xshape)
infer_meta : infer_meta :
...@@ -2542,7 +2542,7 @@ ...@@ -2542,7 +2542,7 @@
intermediate : xshape intermediate : xshape
backward : squeeze_grad backward : squeeze_grad
- api : stack - op : stack
args : (Tensor[] x, int axis) args : (Tensor[] x, int axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2551,7 +2551,7 @@ ...@@ -2551,7 +2551,7 @@
func : stack func : stack
backward : stack_grad backward : stack_grad
- api : strided_slice - op : strided_slice
args : (Tensor x, int[] axes, IntArray starts, IntArray ends, IntArray strides) args : (Tensor x, int[] axes, IntArray starts, IntArray ends, IntArray strides)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2560,7 +2560,7 @@ ...@@ -2560,7 +2560,7 @@
func : strided_slice func : strided_slice
backward : strided_slice_grad backward : strided_slice_grad
- api : subtract - op : subtract
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2570,7 +2570,7 @@ ...@@ -2570,7 +2570,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : subtract_grad backward : subtract_grad
- api : sum - op : sum
args : (Tensor x, IntArray dims={}, DataType out_dtype=DataType::UNDEFINED, bool keep_dim=false) args : (Tensor x, IntArray dims={}, DataType out_dtype=DataType::UNDEFINED, bool keep_dim=false)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2580,7 +2580,7 @@ ...@@ -2580,7 +2580,7 @@
data_type : x data_type : x
backward : sum_grad backward : sum_grad
- api : svd - op : svd
args : (Tensor x, bool full_metrices) args : (Tensor x, bool full_metrices)
output : Tensor(u), Tensor(s), Tensor(vh) output : Tensor(u), Tensor(s), Tensor(vh)
infer_meta : infer_meta :
...@@ -2590,7 +2590,7 @@ ...@@ -2590,7 +2590,7 @@
backward : svd_grad backward : svd_grad
# The python API paddle.nn.functional.swish has no `bete` argument, it may be removed later # The python API paddle.nn.functional.swish has no `bete` argument, it may be removed later
- api : swish - op : swish
args : (Tensor x, float beta=1.0) args : (Tensor x, float beta=1.0)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2600,7 +2600,7 @@ ...@@ -2600,7 +2600,7 @@
func : swish func : swish
backward : swish_grad backward : swish_grad
- api : sync_batch_norm_ - op : sync_batch_norm_
args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu) args : (Tensor x, Tensor scale, Tensor bias, Tensor mean, Tensor variance, float momentum, float epsilon, str data_layout, bool is_test, bool use_global_stats, bool trainable_statistics, bool fuse_with_relu)
output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space) output : Tensor(out), Tensor(mean_out), Tensor(variance_out), Tensor(saved_mean), Tensor(saved_variance), Tensor(reserve_space)
infer_meta : infer_meta :
...@@ -2611,7 +2611,7 @@ ...@@ -2611,7 +2611,7 @@
backward : sync_batch_norm_grad backward : sync_batch_norm_grad
inplace : (mean -> mean_out), (variance -> variance_out) inplace : (mean -> mean_out), (variance -> variance_out)
- api : take_along_axis - op : take_along_axis
args : (Tensor x, Tensor index, int axis) args : (Tensor x, Tensor index, int axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2622,7 +2622,7 @@ ...@@ -2622,7 +2622,7 @@
data_type : x data_type : x
backward : take_along_axis_grad backward : take_along_axis_grad
- api : tan - op : tan
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2631,7 +2631,7 @@ ...@@ -2631,7 +2631,7 @@
func : tan func : tan
backward : tan_grad backward : tan_grad
- api : tanh - op : tanh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2641,7 +2641,7 @@ ...@@ -2641,7 +2641,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : tanh_grad backward : tanh_grad
- api : tanh_shrink - op : tanh_shrink
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2650,7 +2650,7 @@ ...@@ -2650,7 +2650,7 @@
func : tanh_shrink func : tanh_shrink
backward : tanh_shrink_grad backward : tanh_shrink_grad
- api : temporal_shift - op : temporal_shift
args : (Tensor x, int seg_num, float shift_ratio, str data_format_str) args : (Tensor x, int seg_num, float shift_ratio, str data_format_str)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2659,7 +2659,7 @@ ...@@ -2659,7 +2659,7 @@
func : temporal_shift func : temporal_shift
backward : temporal_shift_grad backward : temporal_shift_grad
- api : thresholded_relu - op : thresholded_relu
args : (Tensor x, float threshold) args : (Tensor x, float threshold)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2669,7 +2669,7 @@ ...@@ -2669,7 +2669,7 @@
func : thresholded_relu func : thresholded_relu
backward : thresholded_relu_grad backward : thresholded_relu_grad
- api : tile - op : tile
args : (Tensor x, IntArray repeat_times) args : (Tensor x, IntArray repeat_times)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2678,7 +2678,7 @@ ...@@ -2678,7 +2678,7 @@
func : tile func : tile
backward : tile_grad backward : tile_grad
- api : top_k - op : top_k
args : (Tensor x, Scalar k, int axis = -1, bool largest = true, bool sorted = true) args : (Tensor x, Scalar k, int axis = -1, bool largest = true, bool sorted = true)
output : Tensor(out), Tensor(indices) output : Tensor(out), Tensor(indices)
infer_meta : infer_meta :
...@@ -2687,7 +2687,7 @@ ...@@ -2687,7 +2687,7 @@
func : top_k func : top_k
backward : top_k_grad backward : top_k_grad
- api : transpose - op : transpose
args : (Tensor x, int[] axis) args : (Tensor x, int[] axis)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2696,7 +2696,7 @@ ...@@ -2696,7 +2696,7 @@
func : transpose func : transpose
backward : transpose_grad backward : transpose_grad
- api : triangular_solve - op : triangular_solve
args : (Tensor x, Tensor y, bool upper, bool transpose, bool unitriangular) args : (Tensor x, Tensor y, bool upper, bool transpose, bool unitriangular)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2705,7 +2705,7 @@ ...@@ -2705,7 +2705,7 @@
func : triangular_solve func : triangular_solve
backward : triangular_solve_grad backward : triangular_solve_grad
- api : tril_indices - op : tril_indices
args : (int rows, int cols, int offset, DataType dtype, Place place={}) args : (int rows, int cols, int offset, DataType dtype, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2717,7 +2717,7 @@ ...@@ -2717,7 +2717,7 @@
data_type : dtype data_type : dtype
backend : place backend : place
- api : tril_triu - op : tril_triu
args : (Tensor x, int diagonal, bool lower) args : (Tensor x, int diagonal, bool lower)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2726,7 +2726,7 @@ ...@@ -2726,7 +2726,7 @@
func : tril_triu func : tril_triu
backward : tril_triu_grad backward : tril_triu_grad
- api : trilinear_interp - op : trilinear_interp
args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode) args : (Tensor x, Tensor out_size, Tensor[] size_tensor, Tensor scale_tensor, str data_layout, int out_d, int out_h, int out_w, float[] scale, str interp_method, bool align_corners, int align_mode)
output : Tensor(output) output : Tensor(output)
infer_meta : infer_meta :
...@@ -2737,7 +2737,7 @@ ...@@ -2737,7 +2737,7 @@
data_type : x data_type : x
backward : trilinear_interp_grad backward : trilinear_interp_grad
- api : triu_indices - op : triu_indices
args : (int row, int col, int offset, DataType dtype, Place place={}) args : (int row, int col, int offset, DataType dtype, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2750,7 +2750,7 @@ ...@@ -2750,7 +2750,7 @@
backend : place backend : place
# python API: paddle.nn.initializer.TruncatedNormal # python API: paddle.nn.initializer.TruncatedNormal
- api : truncated_gaussian_random - op : truncated_gaussian_random
args : (int[] shape, float mean, float std, int seed, DataType dtype=DataType::FLOAT32, Place place={}) args : (int[] shape, float mean, float std, int seed, DataType dtype=DataType::FLOAT32, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2762,7 +2762,7 @@ ...@@ -2762,7 +2762,7 @@
backend : place backend : place
data_type : dtype data_type : dtype
- api : unbind - op : unbind
args : (Tensor input, int axis) args : (Tensor input, int axis)
output : Tensor[] {axis<0 ? input.dims()[input.dims().size()+axis]:input.dims()[axis]} output : Tensor[] {axis<0 ? input.dims()[input.dims().size()+axis]:input.dims()[axis]}
infer_meta : infer_meta :
...@@ -2771,7 +2771,7 @@ ...@@ -2771,7 +2771,7 @@
func : unbind func : unbind
backward : unbind_grad backward : unbind_grad
- api : unfold - op : unfold
args : (Tensor x, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) args : (Tensor x, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2780,7 +2780,7 @@ ...@@ -2780,7 +2780,7 @@
func : unfold func : unfold
backward : unfold_grad backward : unfold_grad
- api : uniform_random - op : uniform_random
args : (IntArray shape, DataType dtype, Scalar min, Scalar max, int seed, Place place={}) args : (IntArray shape, DataType dtype, Scalar min, Scalar max, int seed, Place place={})
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2793,7 +2793,7 @@ ...@@ -2793,7 +2793,7 @@
backend : place backend : place
# The `axis` argument of Python API paddle.unique is not vector # The `axis` argument of Python API paddle.unique is not vector
- api : unique - op : unique
args : (Tensor x, bool return_index, bool return_inverse, bool return_counts, int[] axis, DataType dtype=DataType::INT64) args : (Tensor x, bool return_index, bool return_inverse, bool return_counts, int[] axis, DataType dtype=DataType::INT64)
output : Tensor(out), Tensor(indices), Tensor(inverse), Tensor(counts) output : Tensor(out), Tensor(indices), Tensor(inverse), Tensor(counts)
infer_meta : infer_meta :
...@@ -2802,7 +2802,7 @@ ...@@ -2802,7 +2802,7 @@
func : unique func : unique
data_type : x data_type : x
- api : unique_consecutive - op : unique_consecutive
args : (Tensor x, bool return_inverse, bool return_counts, int[] axis, int dtype) args : (Tensor x, bool return_inverse, bool return_counts, int[] axis, int dtype)
output : Tensor(out), Tensor(index), Tensor(counts) output : Tensor(out), Tensor(index), Tensor(counts)
infer_meta : infer_meta :
...@@ -2811,7 +2811,7 @@ ...@@ -2811,7 +2811,7 @@
func : unique_consecutive func : unique_consecutive
data_type : x data_type : x
- api : unsqueeze - op : unsqueeze
args : (Tensor x, IntArray axis) args : (Tensor x, IntArray axis)
output : Tensor(out), Tensor(xshape) output : Tensor(out), Tensor(xshape)
infer_meta : infer_meta :
...@@ -2823,7 +2823,7 @@ ...@@ -2823,7 +2823,7 @@
intermediate : xshape intermediate : xshape
backward : unsqueeze_grad backward : unsqueeze_grad
- api : unstack - op : unstack
args : (Tensor x, int axis, int num) args : (Tensor x, int axis, int num)
output : Tensor[]{num} output : Tensor[]{num}
infer_meta : infer_meta :
...@@ -2832,7 +2832,7 @@ ...@@ -2832,7 +2832,7 @@
func : unstack func : unstack
backward : unstack_grad backward : unstack_grad
- api : viterbi_decode - op : viterbi_decode
args : (Tensor input, Tensor transition, Tensor length, bool include_bos_eos_tag) args : (Tensor input, Tensor transition, Tensor length, bool include_bos_eos_tag)
output : Tensor(scores), Tensor(path) output : Tensor(scores), Tensor(path)
infer_meta : infer_meta :
...@@ -2841,7 +2841,7 @@ ...@@ -2841,7 +2841,7 @@
func : viterbi_decode func : viterbi_decode
data_type : input data_type : input
- api : warpctc - op : warpctc
args : (Tensor logits, Tensor label, Tensor logits_length, Tensor labels_length, int blank, bool norm_by_times) args : (Tensor logits, Tensor label, Tensor logits_length, Tensor labels_length, int blank, bool norm_by_times)
output : Tensor(loss), Tensor(warpctcgrad) output : Tensor(loss), Tensor(warpctcgrad)
infer_meta : infer_meta :
...@@ -2853,7 +2853,7 @@ ...@@ -2853,7 +2853,7 @@
intermediate: warpctcgrad intermediate: warpctcgrad
backward : warpctc_grad backward : warpctc_grad
- api : where - op : where
args : (Tensor condition, Tensor x, Tensor y) args : (Tensor condition, Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -2862,7 +2862,7 @@ ...@@ -2862,7 +2862,7 @@
func : where func : where
backward : where_grad backward : where_grad
- api : where_index - op : where_index
args : (Tensor condition) args : (Tensor condition)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -2870,7 +2870,7 @@ ...@@ -2870,7 +2870,7 @@
kernel : kernel :
func : where_index func : where_index
- api : yolo_box - op : yolo_box
args : (Tensor x, Tensor img_size, int[] anchors, int class_num, float conf_thresh, int downsample_ratio, bool clip_bbox, float scale_x_y=1.0, bool iou_aware=false, float iou_aware_factor=0.5) args : (Tensor x, Tensor img_size, int[] anchors, int class_num, float conf_thresh, int downsample_ratio, bool clip_bbox, float scale_x_y=1.0, bool iou_aware=false, float iou_aware_factor=0.5)
output : Tensor(boxes), Tensor(scores) output : Tensor(boxes), Tensor(scores)
infer_meta : infer_meta :
...@@ -2879,7 +2879,7 @@ ...@@ -2879,7 +2879,7 @@
func : yolo_box func : yolo_box
data_type : x data_type : x
- api : yolov3_loss - op : yolov3_loss
args : (Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0) args : (Tensor x, Tensor gt_box, Tensor gt_label, Tensor gt_score, int[] anchors, int[] anchor_mask, int class_num, float ignore_thresh, int downsample_ratio, bool use_label_smooth=true, float scale_x_y=1.0)
output : Tensor(loss), Tensor(objectness_mask), Tensor(gt_match_mask) output : Tensor(loss), Tensor(objectness_mask), Tensor(gt_match_mask)
infer_meta : infer_meta :
...@@ -2890,17 +2890,17 @@ ...@@ -2890,17 +2890,17 @@
optional : gt_score optional : gt_score
backward : yolov3_loss_grad backward : yolov3_loss_grad
- api : zeros - op : zeros
args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace()) args : (IntArray shape, DataType dtype=DataType::FLOAT32, Place place=CPUPlace())
output : Tensor(out) output : Tensor(out)
invoke : full(shape, 0, dtype, place) invoke : full(shape, 0, dtype, place)
- api : zeros_like - op : zeros_like
args : (Tensor x, DataType dtype=DataType::UNDEFINED, Place place = {}) args : (Tensor x, DataType dtype=DataType::UNDEFINED, Place place = {})
output : Tensor(out) output : Tensor(out)
invoke : full_like(x, 0, dtype, place) invoke : full_like(x, 0, dtype, place)
- api: broadcast_tensors - op: broadcast_tensors
args: (Tensor[] x) args: (Tensor[] x)
output: Tensor[]{x.size()} output: Tensor[]{x.size()}
infer_meta: infer_meta:
...@@ -2909,7 +2909,7 @@ ...@@ -2909,7 +2909,7 @@
func: broadcast_tensors func: broadcast_tensors
backward: broadcast_tensors_grad backward: broadcast_tensors_grad
- api: dirichlet - op: dirichlet
args: (Tensor alpha) args: (Tensor alpha)
output: Tensor(out) output: Tensor(out)
infer_meta: infer_meta:
...@@ -2917,7 +2917,7 @@ ...@@ -2917,7 +2917,7 @@
kernel: kernel:
func: dirichlet func: dirichlet
- api: eig - op: eig
args: (Tensor x) args: (Tensor x)
output: Tensor(out_w), Tensor(out_v) output: Tensor(out_w), Tensor(out_v)
infer_meta: infer_meta:
...@@ -2926,7 +2926,7 @@ ...@@ -2926,7 +2926,7 @@
func: eig func: eig
backward: eig_grad backward: eig_grad
- api: fold - op: fold
args: (Tensor x, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations) args: (Tensor x, int[] output_sizes, int[] kernel_sizes, int[] strides, int[] paddings, int[] dilations)
output: Tensor(out) output: Tensor(out)
infer_meta: infer_meta:
...@@ -2935,7 +2935,7 @@ ...@@ -2935,7 +2935,7 @@
func: fold func: fold
backward: fold_grad backward: fold_grad
- api: overlap_add - op: overlap_add
args: (Tensor x, int hop_length, int axis) args: (Tensor x, int hop_length, int axis)
output: Tensor output: Tensor
infer_meta: infer_meta:
...@@ -2944,7 +2944,7 @@ ...@@ -2944,7 +2944,7 @@
func: overlap_add func: overlap_add
backward: overlap_add_grad backward: overlap_add_grad
- api: uniform_random_inplace - op: uniform_random_inplace
args: (Tensor x, float min, float max, int seed, int diag_num, int diag_step, float diag_val) args: (Tensor x, float min, float max, int seed, int diag_num, int diag_step, float diag_val)
output: Tensor(out) output: Tensor(out)
infer_meta: infer_meta:
...@@ -2955,7 +2955,7 @@ ...@@ -2955,7 +2955,7 @@
inplace: (x -> out) inplace: (x -> out)
backward: uniform_random_inplace_grad backward: uniform_random_inplace_grad
- api: unpool - op: unpool
args: (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format) args: (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, IntArray output_size, str data_format)
output: Tensor(out) output: Tensor(out)
infer_meta: infer_meta:
...@@ -2965,7 +2965,7 @@ ...@@ -2965,7 +2965,7 @@
data_type: x data_type: x
backward: unpool_grad backward: unpool_grad
- api: unpool3d - op: unpool3d
args: (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format) args: (Tensor x, Tensor indices, int[] ksize, int[] strides, int[] padding, int[] output_size, str data_format)
output: Tensor(out) output: Tensor(out)
infer_meta: infer_meta:
......
paddle/phi/api/yaml/api_compat.yaml → paddle/phi/api/yaml/op_compat.yaml
浏览文件 @ 8caaf85a
- api : abs - op : abs
backward : abs_grad backward : abs_grad
extra : extra :
attrs : [bool use_cudnn = false, bool use_mkldnn = false] attrs : [bool use_cudnn = false, bool use_mkldnn = false]
- api : addmm - op : acosh
backward : acosh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : addmm
backward : addmm_grad backward : addmm_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : affine_grid - op : affine_grid
backward : affine_grid_grad backward : affine_grid_grad
extra : extra :
attrs : [bool use_cudnn = true] attrs : [bool use_cudnn = true]
- api : angle - op : angle
backward : angle_grad backward : angle_grad
extra : extra :
attrs : [bool use_cudnn = false, bool use_mkldnn = false] attrs : [bool use_cudnn = false, bool use_mkldnn = false]
- api : atan2 - op : asinh
backward : asinh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : atan2
inputs : inputs :
{x : X1, y : X2} {x : X1, y : X2}
outputs : outputs :
out : Out out : Out
- api : batch_norm - op : atanh
backward : atanh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : batch_norm
backward : batch_norm_grad backward : batch_norm_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool fuse_with_relu = false] attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
- api : bernoulli - op : bernoulli
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : bicubic_interp (bicubic_interp_v2) - op : bicubic_interp (bicubic_interp_v2)
backward : bicubic_interp_grad (bicubic_interp_v2_grad) backward : bicubic_interp_grad (bicubic_interp_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : bilinear_interp (bilinear_interp_v2) - op : bilinear_interp (bilinear_interp_v2)
backward : bilinear_interp_grad (bilinear_interp_v2_grad) backward : bilinear_interp_grad (bilinear_interp_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : cholesky - op : ceil
backward : ceil_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : cholesky
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : cholesky_solve - op : cholesky_solve
inputs : inputs :
{x : X, y : Y} {x : X, y : Y}
outputs : outputs :
out : Out out : Out
- api : clip - op : clip
backward : clip_grad backward : clip_grad
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
- api : concat - op : concat
backward : concat_grad backward : concat_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool use_quantizer = false, str mkldnn_data_type = "float32"] attrs : [bool use_mkldnn = false, bool use_quantizer = false, str mkldnn_data_type = "float32"]
- api : conv2d - op : conv2d
backward : conv2d_grad backward : conv2d_grad
extra : extra :
attrs : [bool is_test = false, bool use_cudnn = true, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false, attrs : [bool is_test = false, bool use_cudnn = true, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
...@@ -77,7 +97,7 @@ ...@@ -77,7 +97,7 @@
float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false, float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
- api : conv2d_fusion - op : conv2d_fusion
extra : extra :
attrs : [bool is_test = false, bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false, attrs : [bool is_test = false, bool use_cudnn = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false, bool use_quantizer = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
...@@ -86,7 +106,7 @@ ...@@ -86,7 +106,7 @@
float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false, float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
- api : conv2d_transpose - op : conv2d_transpose
backward : conv2d_transpose_grad backward : conv2d_transpose_grad
extra : extra :
attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, bool force_fp32_output = false, attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, bool force_fp32_output = false,
...@@ -94,7 +114,7 @@ ...@@ -94,7 +114,7 @@
str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
- api : conv3d - op : conv3d
backward : conv3d_grad backward : conv3d_grad
extra : extra :
attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool fuse_relu = false, attrs : [bool is_test = false, bool use_cudnn = true, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool fuse_relu = false,
...@@ -102,12 +122,22 @@ ...@@ -102,12 +122,22 @@
bool use_addto = false, bool fuse_residual_connection = false, bool force_fp32_output = false, bool use_addto = false, bool fuse_residual_connection = false, bool force_fp32_output = false,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
- api : conv3d_transpose - op : conv3d_transpose
backward : conv3d_transpose_grad backward : conv3d_transpose_grad
extra : extra :
attrs : [bool use_cudnn = true, bool use_mkldnn = false, int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()] attrs : [bool use_cudnn = true, bool use_mkldnn = false, int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
- api : cross - op : cos
backward : cos_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : cosh
backward : cosh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : cross
inputs : inputs :
{x : X, y : Y} {x : X, y : Y}
attrs : attrs :
...@@ -115,12 +145,12 @@ ...@@ -115,12 +145,12 @@
outputs : outputs :
out : Out out : Out
- api : data_norm - op : data_norm
backward : data_norm_grad backward : data_norm_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : depthwise_conv2d - op : depthwise_conv2d
backward : depthwise_conv2d_grad backward : depthwise_conv2d_grad
extra : extra :
attrs : [bool is_test = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false, attrs : [bool is_test = false, bool fuse_relu_before_depthwise_conv = false, bool use_mkldnn = false,
...@@ -130,7 +160,7 @@ ...@@ -130,7 +160,7 @@
float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false, float Scale_in_eltwise = 1.0f, 'float[] Scale_weights = {1.0f}', bool force_fp32_output = false,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB(), bool exhaustive_search = false]
- api : depthwise_conv2d_transpose - op : depthwise_conv2d_transpose
backward : depthwise_conv2d_transpose_grad backward : depthwise_conv2d_transpose_grad
extra : extra :
attrs : [bool is_test = false, bool use_cudnn = false, bool use_mkldnn = false, bool force_fp32_output = false, attrs : [bool is_test = false, bool use_cudnn = false, bool use_mkldnn = false, bool force_fp32_output = false,
...@@ -138,274 +168,421 @@ ...@@ -138,274 +168,421 @@
str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f, str fuse_activation = "", float fuse_alpha = 0.0f, float fuse_beta = 0.0f,
int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()] int workspace_size_MB = platform::GetDefaultConvWorkspaceSizeLimitMB()]
- api : diag (diag_v2) - op : diag (diag_v2)
backward : diag_grad (diag_v2_grad) backward : diag_grad (diag_v2_grad)
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : diagonal - op : diagonal
inputs : inputs :
x : Input x : Input
outputs : outputs :
out : Out out : Out
- api : digamma - op : digamma
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : dist - op : dist
inputs : inputs :
{x : X, y : Y} {x : X, y : Y}
outputs : outputs :
out : Out out : Out
- api : dot - op : dot
inputs : inputs :
{x : X, y : Y} {x : X, y : Y}
outputs : outputs :
out : Out out : Out
- api : dropout - op : dropout
backward : dropout_grad backward : dropout_grad
extra : extra :
attrs : [bool fix_seed = false, int seed = 0] attrs : [bool fix_seed = false, int seed = 0]
- api : dropout_nd - op : dropout_nd
backward : dropout_nd_grad backward : dropout_nd_grad
extra : extra :
attrs : [bool fix_seed = false, int seed = 0] attrs : [bool fix_seed = false, int seed = 0]
- api : erf - op : elu
backward : elu_grad
extra :
attrs : [bool use_mkldnn = false]
- op : erf
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : erfinv - op : erfinv
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : fft_c2c - op : exp
backward : exp_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : expm1
backward : expm1_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : fft_c2c
inputs: {x: X} inputs: {x: X}
outputs: {out: Out} outputs: {out: Out}
- api : fft_c2r - op : fft_c2r
inputs: {x: X} inputs: {x: X}
outputs: {out: Out} outputs: {out: Out}
- api : fft_r2c - op : fft_r2c
inputs: {x: X} inputs: {x: X}
outputs: {out: Out} outputs: {out: Out}
- api : frobenius_norm - op : floor
backward : floor_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : frobenius_norm
backward : frobenius_norm_grad backward : frobenius_norm_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : gelu - op : gelu
backward : gelu_grad backward : gelu_grad
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool use_cudnn = false] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool use_cudnn = false]
- api : grid_sampler - op : grid_sampler
backward : grid_sampler_grad backward : grid_sampler_grad
extra : extra :
attrs : [bool use_cudnn = true] attrs : [bool use_cudnn = true]
- api : gru - op : gru
backward : gru_grad backward : gru_grad
extra : extra :
attrs : [bool is_test = false] attrs : [bool is_test = false]
- api : inplace_abn - op : hard_swish
backward : hard_swish_grad
extra :
attrs : [bool use_mkldnn = false]
- op : inplace_abn
backward : inplace_abn_grad backward : inplace_abn_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool fuse_with_relu = false] attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
- api : layer_norm - op : layer_norm
backward : layer_norm_grad backward : layer_norm_grad
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]
- api : lgamma - op : leaky_relu
backward : leaky_relu_grad
extra :
attrs : [bool use_mkldnn = false]
- op : lgamma
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : linear_interp (linear_interp_v2) - op : linear_interp (linear_interp_v2)
backward : linear_interp_grad (linear_interp_v2_grad) backward : linear_interp_grad (linear_interp_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : log_softmax - op : log
backward : log_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : log10
backward : log10_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : log1p
backward : log1p_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : log2
backward : log2_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : log_softmax
backward : log_softmax_grad backward : log_softmax_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : lrn - op : logsigmoid
backward : logsigmoid_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : lrn
backward : lrn_grad backward : lrn_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool is_test = false] attrs : [bool use_mkldnn = false, bool is_test = false]
- api : matmul (matmul_v2) - op : matmul (matmul_v2)
backward : matmul_grad (matmul_v2_grad) backward : matmul_grad (matmul_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false, 'int[] fused_reshape_Out = {}', 'int[] fused_transpose_Out = {}', attrs : [bool use_mkldnn = false, 'int[] fused_reshape_Out = {}', 'int[] fused_transpose_Out = {}',
str mkldnn_data_type = "float32", 'int[] fused_reshape_X = {}', 'int[] fused_reshape_Y = {}', str mkldnn_data_type = "float32", 'int[] fused_reshape_X = {}', 'int[] fused_reshape_Y = {}',
'int[] fused_transpose_X = {}', 'int[] fused_transpose_Y = {}',] 'int[] fused_transpose_X = {}', 'int[] fused_transpose_Y = {}',]
- api : mv - op : mish
backward : mish_grad
extra :
attrs : [bool use_mkldnn = false]
- op : mv
inputs : inputs :
{x : X, vec : Vec} {x : X, vec : Vec}
outputs : outputs :
out : Out out : Out
- api : nearest_interp (nearest_interp_v2) - op : nearest_interp (nearest_interp_v2)
backward : nearest_interp_grad (nearest_interp_v2_grad) backward : nearest_interp_grad (nearest_interp_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : pad2d - op : pad2d
backward : pad2d_grad backward : pad2d_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : pad3d - op : pad3d
backward : pad3d_grad backward : pad3d_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : partial_sum - op : partial_sum
backward : partial_sum_grad backward : partial_sum_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : poisson - op : poisson
inputs : inputs :
x : X x : X
outputs : outputs :
out : Out out : Out
- api : reduce_all - op : prelu
backward : prelu_grad
extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]
- op : reciprocal
backward : reciprocal_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : reduce_all
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_amax - op : reduce_amax
backward : reduce_amax_grad backward : reduce_amax_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_amin - op : reduce_amin
backward : reduce_amin_grad backward : reduce_amin_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_any - op : reduce_any
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_max - op : reduce_max
backward : reduce_max_grad backward : reduce_max_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_mean - op : reduce_mean
backward : reduce_mean_grad backward : reduce_mean_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_min - op : reduce_min
backward : reduce_min_grad backward : reduce_min_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_prod - op : reduce_prod
backward : reduce_prod_grad backward : reduce_prod_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : reduce_sum - op : reduce_sum
backward : reduce_sum_grad backward : reduce_sum_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : renorm - op : relu
backward : relu_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : relu6
backward : relu6_grad
extra :
attrs : [bool use_mkldnn = false]
- op : renorm
backward : renorm_grad backward : renorm_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false] attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- api : rnn - op : rnn
backward : rnn_grad backward : rnn_grad
extra : extra :
attrs : [bool is_test = false] attrs : [bool is_test = false]
- api : seed - op : round
backward : round_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : rsqrt
backward : rsqrt_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : seed
extra : extra :
attrs : [bool deterministic = false, str rng_name = "", bool force_cpu = false] attrs : [bool deterministic = false, str rng_name = "", bool force_cpu = false]
- api : shape - op : shape
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
- api : shuffle_channel - op : shuffle_channel
backward : shuffle_channel_grad backward : shuffle_channel_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : slice - op : sigmoid
backward : sigmoid_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : silu
backward : silu_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : sin
backward : sin_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : sinh
backward : sinh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : slice
backward : slice_grad backward : slice_grad
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
- api : softmax - op : softmax
backward : softmax_grad backward : softmax_grad
extra : extra :
attrs : [bool use_cudnn = false, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false] attrs : [bool use_cudnn = false, bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false]
- api : prelu
backward : prelu_grad - op : softplus
backward : softplus_grad
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32", bool is_test = false] attrs : [bool use_mkldnn = false, bool use_cudnn = false, str fuse_activation_type = "", float fuse_activation_alpha = 0.0f,
float fuse_activation_beta = 0.0f, float fuse_activation_scale = 1.0f]
- op : softsign
backward : softsign_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- api : solve - op : solve
inputs : inputs :
{x : X, y : Y} {x : X, y : Y}
outputs : outputs :
out : Out out : Out
- api : squeeze (squeeze2) - op : sqrt
backward : sqrt_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : square
backward : square_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : squeeze (squeeze2)
backward : squeeze_grad (squeeze2_grad) backward : squeeze_grad (squeeze2_grad)
extra : extra :
attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"] attrs : [bool use_mkldnn = false, str mkldnn_data_type = "float32"]
- api : stack - op : stack
backward : stack_grad backward : stack_grad
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : sync_batch_norm - op : swish
backward : swish_grad
extra :
attrs : [bool use_mkldnn = false]
- op : sync_batch_norm
backward : sync_batch_norm_grad backward : sync_batch_norm_grad
extra : extra :
attrs : [bool use_mkldnn = false, bool fuse_with_relu = false] attrs : [bool use_mkldnn = false, bool fuse_with_relu = false]
- api : trace - op : tan
backward : tan_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : tanh
backward : tanh_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : tanh_shrink
backward : tanh_shrink_grad
extra :
attrs : [bool use_mkldnn = false, bool use_cudnn = false]
- op : trace
inputs : inputs :
x : Input x : Input
outputs : outputs :
out : Out out : Out
- api : trilinear_interp (trilinear_interp_v2) - op : trilinear_interp (trilinear_interp_v2)
backward : trilinear_interp_grad (trilinear_interp_v2_grad) backward : trilinear_interp_grad (trilinear_interp_v2_grad)
extra : extra :
attrs : [bool use_mkldnn = false] attrs : [bool use_mkldnn = false]
- api : trunc - op : trunc
inputs : inputs :
x : X x : X
outputs : outputs :
......
paddle/phi/api/yaml/api_version.yaml → paddle/phi/api/yaml/op_version.yaml
浏览文件 @ 8caaf85a
- api : trace - op : trace
version : version :
- checkpoint : Upgrade trace add a new attribute [axis2] - checkpoint : Upgrade trace add a new attribute [axis2]
action : action :
......
paddle/phi/api/yaml/api.yaml → paddle/phi/api/yaml/ops.yaml
浏览文件 @ 8caaf85a
- api : atan2 - op : atan2
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -7,7 +7,7 @@ ...@@ -7,7 +7,7 @@
func : atan2 func : atan2
backward : atan2_grad backward : atan2_grad
- api : bernoulli - op : bernoulli
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -15,7 +15,7 @@ ...@@ -15,7 +15,7 @@
kernel : kernel :
func : bernoulli func : bernoulli
- api : cholesky - op : cholesky
args : (Tensor x, bool upper=false) args : (Tensor x, bool upper=false)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -24,7 +24,7 @@ ...@@ -24,7 +24,7 @@
func : cholesky func : cholesky
backward : cholesky_grad backward : cholesky_grad
- api : cholesky_solve - op : cholesky_solve
args : (Tensor x, Tensor y, bool upper=false) args : (Tensor x, Tensor y, bool upper=false)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -33,7 +33,7 @@ ...@@ -33,7 +33,7 @@
func : cholesky_solve func : cholesky_solve
backward : cholesky_solve_grad backward : cholesky_solve_grad
- api : cross - op : cross
args : (Tensor x, Tensor y, int axis = 9) args : (Tensor x, Tensor y, int axis = 9)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -43,7 +43,7 @@ ...@@ -43,7 +43,7 @@
data_type : x data_type : x
backward : cross_grad backward : cross_grad
- api : diag - op : diag
args : (Tensor x, int offset = 0, float padding_value = 0.0) args : (Tensor x, int offset = 0, float padding_value = 0.0)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -52,7 +52,7 @@ ...@@ -52,7 +52,7 @@
func : diag func : diag
backward : diag_grad backward : diag_grad
- api : diagonal - op : diagonal
args : (Tensor x, int offset = 0, int axis1 = 0, int axis2 = 1) args : (Tensor x, int offset = 0, int axis1 = 0, int axis2 = 1)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -61,7 +61,7 @@ ...@@ -61,7 +61,7 @@
func : diagonal func : diagonal
backward : diagonal_grad backward : diagonal_grad
- api : digamma - op : digamma
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -70,7 +70,7 @@ ...@@ -70,7 +70,7 @@
func : digamma func : digamma
backward : digamma_grad backward : digamma_grad
- api : dist - op : dist
args : (Tensor x, Tensor y, float p = 2.0) args : (Tensor x, Tensor y, float p = 2.0)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -79,7 +79,7 @@ ...@@ -79,7 +79,7 @@
func : dist func : dist
backward : dist_grad backward : dist_grad
- api : dot - op : dot
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -89,7 +89,7 @@ ...@@ -89,7 +89,7 @@
data_type : x data_type : x
backward : dot_grad backward : dot_grad
- api : erf - op : erf
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -98,7 +98,7 @@ ...@@ -98,7 +98,7 @@
func : erf func : erf
backward : erf_grad backward : erf_grad
- api : erfinv - op : erfinv
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -108,7 +108,7 @@ ...@@ -108,7 +108,7 @@
inplace : (x -> out) inplace : (x -> out)
backward : erfinv_grad backward : erfinv_grad
- api : fft_c2c - op : fft_c2c
args : (Tensor x, int64_t[] axes, str normalization, bool forward) args : (Tensor x, int64_t[] axes, str normalization, bool forward)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -117,7 +117,7 @@ ...@@ -117,7 +117,7 @@
func : fft_c2c func : fft_c2c
backward : fft_c2c_grad backward : fft_c2c_grad
- api : fft_c2r - op : fft_c2r
args : (Tensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size=0L) args : (Tensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size=0L)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -126,7 +126,7 @@ ...@@ -126,7 +126,7 @@
func : fft_c2r func : fft_c2r
backward : fft_c2r_grad backward : fft_c2r_grad
- api : fft_r2c - op : fft_r2c
args : (Tensor x, int64_t[] axes, str normalization, bool forward, bool onesided) args : (Tensor x, int64_t[] axes, str normalization, bool forward, bool onesided)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -135,7 +135,7 @@ ...@@ -135,7 +135,7 @@
func : fft_r2c func : fft_r2c
backward : fft_r2c_grad backward : fft_r2c_grad
- api : graph_send_uv - op : graph_send_uv
args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") args : (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD")
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -145,7 +145,7 @@ ...@@ -145,7 +145,7 @@
data_type : x data_type : x
backward : graph_send_uv_grad backward : graph_send_uv_grad
- api : lgamma - op : lgamma
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
infer_meta : infer_meta :
...@@ -154,7 +154,7 @@ ...@@ -154,7 +154,7 @@
func : lgamma func : lgamma
backward : lgamma_grad backward : lgamma_grad
- api : mv - op : mv
args : (Tensor x, Tensor vec) args : (Tensor x, Tensor vec)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -163,7 +163,7 @@ ...@@ -163,7 +163,7 @@
func : mv func : mv
backward : mv_grad backward : mv_grad
- api : poisson - op : poisson
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -172,7 +172,7 @@ ...@@ -172,7 +172,7 @@
func : poisson func : poisson
backward : poisson_grad backward : poisson_grad
- api : solve - op : solve
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -182,7 +182,7 @@ ...@@ -182,7 +182,7 @@
data_type : x data_type : x
backward : solve_grad backward : solve_grad
- api : trace - op : trace
args : (Tensor x, int offset = 0, int axis1 = 0, int axis2 = 1) args : (Tensor x, int offset = 0, int axis1 = 0, int axis2 = 1)
output : Tensor output : Tensor
infer_meta : infer_meta :
...@@ -191,7 +191,7 @@ ...@@ -191,7 +191,7 @@
func : trace func : trace
backward : trace_grad backward : trace_grad
- api : trunc - op : trunc
args : (Tensor x) args : (Tensor x)
output : Tensor output : Tensor
infer_meta : infer_meta :
......
paddle/phi/api/yaml/sparse_bw_api.yaml → paddle/phi/api/yaml/sparse_backward.yaml
浏览文件 @ 8caaf85a
- backward_api : abs_grad - backward_op : abs_grad
forward : tanh(Tensor x) -> Tensor(out) forward : tanh(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -6,7 +6,7 @@ ...@@ -6,7 +6,7 @@
func : abs_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : abs_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
abs_csr_grad {sparse_csr, sparse_csr -> sparse_csr} abs_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : acos_grad - backward_op : acos_grad
forward : acos(Tensor x) -> Tensor(out) forward : acos(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -14,7 +14,7 @@ ...@@ -14,7 +14,7 @@
func : acos_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : acos_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acos_csr_grad {sparse_csr, sparse_csr -> sparse_csr} acos_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : acosh_grad - backward_op : acosh_grad
forward : acosh(Tensor x) -> Tensor(out) forward : acosh(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -22,7 +22,7 @@ ...@@ -22,7 +22,7 @@
func : acosh_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : acosh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acosh_csr_grad {sparse_csr, sparse_csr -> sparse_csr} acosh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : add_grad - backward_op : add_grad
forward : add(Tensor x, Tensor y) -> Tensor(out) forward : add(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -30,7 +30,7 @@ ...@@ -30,7 +30,7 @@
func : add_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}, func : add_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
add_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr} add_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
- backward_api : addmm_grad - backward_op : addmm_grad
forward : addmm(Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) -> Tensor(out) forward : addmm(Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) -> Tensor(out)
args : (Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha=1.0, float beta=1.0) args : (Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha=1.0, float beta=1.0)
output : Tensor(input_grad), Tensor(x_grad), Tensor(y_grad) output : Tensor(input_grad), Tensor(x_grad), Tensor(y_grad)
...@@ -40,7 +40,7 @@ ...@@ -40,7 +40,7 @@
addmm_coo_dense_grad {dense, sparse_coo, dense, dense -> dense, sparse_coo, dense}, addmm_coo_dense_grad {dense, sparse_coo, dense, dense -> dense, sparse_coo, dense},
addmm_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo, sparse_coo} addmm_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo, sparse_coo}
- backward_api : asin_grad - backward_op : asin_grad
forward : asin(Tensor x) -> Tensor(out) forward : asin(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -48,7 +48,7 @@ ...@@ -48,7 +48,7 @@
func : asin_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : asin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asin_csr_grad {sparse_csr, sparse_csr -> sparse_csr} asin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : asinh_grad - backward_op : asinh_grad
forward : asinh(Tensor x) -> Tensor(out) forward : asinh(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -56,7 +56,7 @@ ...@@ -56,7 +56,7 @@
func : asinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : asinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr} asinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : atan_grad - backward_op : atan_grad
forward : atan(Tensor x) -> Tensor(out) forward : atan(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -64,7 +64,7 @@ ...@@ -64,7 +64,7 @@
func : atan_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : atan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atan_csr_grad {sparse_csr, sparse_csr -> sparse_csr} atan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : atanh_grad - backward_op : atanh_grad
forward : atanh(Tensor x) -> Tensor(out) forward : atanh(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -72,7 +72,7 @@ ...@@ -72,7 +72,7 @@
func : atanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : atanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr} atanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : cast_grad - backward_op : cast_grad
forward : cast(Tensor x, DataType index_dtype, DataType value_dtype) -> Tensor(out) forward : cast(Tensor x, DataType index_dtype, DataType value_dtype) -> Tensor(out)
args : (Tensor x, Tensor out_grad, DataType value_dtype) args : (Tensor x, Tensor out_grad, DataType value_dtype)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -81,14 +81,14 @@ ...@@ -81,14 +81,14 @@
cast_csr_grad {sparse_csr, sparse_csr -> sparse_csr} cast_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
data_type : out_grad data_type : out_grad
- backward_api : conv3d_coo_grad - backward_op : conv3d_coo_grad
forward : conv3d_coo (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) -> Tensor(out), Tensor(rulebook), Tensor(counter) forward : conv3d_coo (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args : (Tensor x, Tensor kernel, Tensor out, Tensor rulebook, Tensor counter, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) args : (Tensor x, Tensor kernel, Tensor out, Tensor rulebook, Tensor counter, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key)
output : Tensor(x_grad), Tensor(kernel_grad) output : Tensor(x_grad), Tensor(kernel_grad)
kernel : kernel :
func : conv3d_coo_grad{sparse_coo, dense, sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense} func : conv3d_coo_grad{sparse_coo, dense, sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
- backward_api : divide_grad - backward_op : divide_grad
forward : divide(Tensor x, Tensor y) -> Tensor(out) forward : divide(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -96,13 +96,13 @@ ...@@ -96,13 +96,13 @@
func : divide_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}, func : divide_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
divide_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr} divide_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
- backward_api : divide_scalar_grad - backward_op : divide_scalar_grad
forward : divide_scalar (Tensor x, float scalar) -> Tensor(out) forward : divide_scalar (Tensor x, float scalar) -> Tensor(out)
args : (Tensor out_grad, float scalar) args : (Tensor out_grad, float scalar)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : divide_scalar(out_grad, scalar) invoke : divide_scalar(out_grad, scalar)
- backward_api : expm1_grad - backward_op : expm1_grad
forward : expm1(Tensor x) -> Tensor(out) forward : expm1(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -110,7 +110,7 @@ ...@@ -110,7 +110,7 @@
func : expm1_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : expm1_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
expm1_csr_grad {sparse_csr, sparse_csr -> sparse_csr} expm1_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : leaky_relu_grad - backward_op : leaky_relu_grad
forward : leaky_relu(Tensor x, float alpha) -> Tensor(out) forward : leaky_relu(Tensor x, float alpha) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float alpha) args : (Tensor x, Tensor out_grad, float alpha)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -118,7 +118,7 @@ ...@@ -118,7 +118,7 @@
func : leaky_relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : leaky_relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
leaky_relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr} leaky_relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : log1p_grad - backward_op : log1p_grad
forward : log1p(Tensor x) -> Tensor(out) forward : log1p(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -126,14 +126,14 @@ ...@@ -126,14 +126,14 @@
func : log1p_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : log1p_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
log1p_csr_grad {sparse_csr, sparse_csr -> sparse_csr} log1p_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : masked_matmul_grad - backward_op : masked_matmul_grad
forward : masked_matmul(Tensor x, Tensor y, Tensor mask) -> Tensor(out) forward : masked_matmul(Tensor x, Tensor y, Tensor mask) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
kernel : kernel :
func : masked_matmul_csr_grad{dense, dense, sparse_csr -> dense, dense} func : masked_matmul_csr_grad{dense, dense, sparse_csr -> dense, dense}
- backward_api : matmul_grad - backward_op : matmul_grad
forward : matmul(Tensor x, Tensor y) -> Tensor(out) forward : matmul(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -143,14 +143,14 @@ ...@@ -143,14 +143,14 @@
matmul_coo_dense_grad {sparse_coo, dense, dense -> sparse_coo, dense}, matmul_coo_dense_grad {sparse_coo, dense, dense -> sparse_coo, dense},
matmul_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo} matmul_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}
- backward_api : maxpool_grad - backward_op : maxpool_grad
forward : maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook), Tensor(counter) forward : maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args : (Tensor x, Tensor rulebook, Tensor counter, Tensor out, Tensor out_grad, int[] kernel_sizes) args : (Tensor x, Tensor rulebook, Tensor counter, Tensor out, Tensor out_grad, int[] kernel_sizes)
output : Tensor(x_grad) output : Tensor(x_grad)
kernel : kernel :
func : maxpool_coo_grad {sparse_coo, dense, dense, sparse_coo, sparse_coo -> sparse_coo} func : maxpool_coo_grad {sparse_coo, dense, dense, sparse_coo, sparse_coo -> sparse_coo}
- backward_api : multiply_grad - backward_op : multiply_grad
forward : multiply(Tensor x, Tensor y) -> Tensor(out) forward : multiply(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -158,7 +158,7 @@ ...@@ -158,7 +158,7 @@
func : multiply_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}, func : multiply_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
multiply_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr} multiply_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
- backward_api : mv_grad - backward_op : mv_grad
forward : mv(Tensor x, Tensor vec) -> Tensor(out) forward : mv(Tensor x, Tensor vec) -> Tensor(out)
args : (Tensor x, Tensor vec, Tensor out_grad) args : (Tensor x, Tensor vec, Tensor out_grad)
output : Tensor(x_grad), Tensor(vec_grad) output : Tensor(x_grad), Tensor(vec_grad)
...@@ -166,7 +166,7 @@ ...@@ -166,7 +166,7 @@
func : mv_coo_grad{sparse_coo, dense, dense -> sparse_coo, dense}, func : mv_coo_grad{sparse_coo, dense, dense -> sparse_coo, dense},
mv_csr_grad{sparse_csr, dense, dense -> sparse_csr, dense} mv_csr_grad{sparse_csr, dense, dense -> sparse_csr, dense}
- backward_api : pow_grad - backward_op : pow_grad
forward : pow(Tensor x, float factor) -> Tensor(out) forward : pow(Tensor x, float factor) -> Tensor(out)
args : (Tensor x, Tensor out_grad, float factor) args : (Tensor x, Tensor out_grad, float factor)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -174,7 +174,7 @@ ...@@ -174,7 +174,7 @@
func : pow_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : pow_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
pow_csr_grad {sparse_csr, sparse_csr -> sparse_csr} pow_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : relu6_grad - backward_op : relu6_grad
forward : relu6(Tensor x, float threshold) -> Tensor(out) forward : relu6(Tensor x, float threshold) -> Tensor(out)
args : (Tensor out, Tensor out_grad, float threshold) args : (Tensor out, Tensor out_grad, float threshold)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -182,7 +182,7 @@ ...@@ -182,7 +182,7 @@
func : relu6_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : relu6_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu6_csr_grad {sparse_csr, sparse_csr -> sparse_csr} relu6_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : relu_grad - backward_op : relu_grad
forward : relu(Tensor x) -> Tensor(out) forward : relu(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -190,13 +190,13 @@ ...@@ -190,13 +190,13 @@
func : relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr} relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : scale_grad - backward_op : scale_grad
forward : scale(Tensor x, float scale, float bias, bool bias_after_scale) -> Tensor(out) forward : scale(Tensor x, float scale, float bias, bool bias_after_scale) -> Tensor(out)
args : (Tensor out_grad, float scale) args : (Tensor out_grad, float scale)
output : Tensor(x_grad) output : Tensor(x_grad)
invoke : scale(out_grad, scale, 0.0, true) invoke : scale(out_grad, scale, 0.0, true)
- backward_api : sin_grad - backward_op : sin_grad
forward : sin(Tensor x) -> Tensor(out) forward : sin(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -204,7 +204,7 @@ ...@@ -204,7 +204,7 @@
func : sin_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : sin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sin_csr_grad {sparse_csr, sparse_csr -> sparse_csr} sin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : sinh_grad - backward_op : sinh_grad
forward : sinh(Tensor x) -> Tensor(out) forward : sinh(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -212,21 +212,21 @@ ...@@ -212,21 +212,21 @@
func : sinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : sinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr} sinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : softmax_grad - backward_op : softmax_grad
forward : softmax(Tensor x, int axis=-1) -> Tensor(out) forward : softmax(Tensor x, int axis=-1) -> Tensor(out)
args : (Tensor out, Tensor out_grad, int axis) args : (Tensor out, Tensor out_grad, int axis)
output : Tensor(x_grad) output : Tensor(x_grad)
kernel : kernel :
func : softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr} func : softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr}
- backward_api : sparse_coo_tensor_grad - backward_op : sparse_coo_tensor_grad
forward : sparse_coo_tensor(Tensor values, Tensor indices, IntArray dense_shape) -> Tensor(out) forward : sparse_coo_tensor(Tensor values, Tensor indices, IntArray dense_shape) -> Tensor(out)
args : (Tensor indices, Tensor out_grad) args : (Tensor indices, Tensor out_grad)
output : Tensor(values_grad) output : Tensor(values_grad)
kernel : kernel :
func : sparse_coo_tensor_grad{dense, sparse_coo -> dense} func : sparse_coo_tensor_grad{dense, sparse_coo -> dense}
- backward_api : sqrt_grad - backward_op : sqrt_grad
forward : sqrt(Tensor x) -> Tensor(out) forward : sqrt(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -234,7 +234,7 @@ ...@@ -234,7 +234,7 @@
func : sqrt_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : sqrt_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sqrt_csr_grad {sparse_csr, sparse_csr -> sparse_csr} sqrt_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : square_grad - backward_op : square_grad
forward : square(Tensor x) -> Tensor(out) forward : square(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -242,7 +242,7 @@ ...@@ -242,7 +242,7 @@
func : square_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : square_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
square_csr_grad {sparse_csr, sparse_csr -> sparse_csr} square_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : subtract_grad - backward_op : subtract_grad
forward : subtract(Tensor x, Tensor y) -> Tensor(out) forward : subtract(Tensor x, Tensor y) -> Tensor(out)
args : (Tensor x, Tensor y, Tensor out_grad) args : (Tensor x, Tensor y, Tensor out_grad)
output : Tensor(x_grad), Tensor(y_grad) output : Tensor(x_grad), Tensor(y_grad)
...@@ -250,7 +250,7 @@ ...@@ -250,7 +250,7 @@
func : subtract_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}, func : subtract_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr} subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
- backward_api : tan_grad - backward_op : tan_grad
forward : tan(Tensor x) -> Tensor(out) forward : tan(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -258,7 +258,7 @@ ...@@ -258,7 +258,7 @@
func : tan_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : tan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tan_csr_grad {sparse_csr, sparse_csr -> sparse_csr} tan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : tanh_grad - backward_op : tanh_grad
forward : tanh(Tensor x) -> Tensor(out) forward : tanh(Tensor x) -> Tensor(out)
args : (Tensor out, Tensor out_grad) args : (Tensor out, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
...@@ -266,28 +266,28 @@ ...@@ -266,28 +266,28 @@
func : tanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo}, func : tanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr} tanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
- backward_api : to_dense_grad - backward_op : to_dense_grad
forward : to_dense(Tensor x) -> Tensor(out) forward : to_dense(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
kernel : kernel :
func : coo_to_dense_grad{sparse_coo, dense -> sparse_coo} func : coo_to_dense_grad{sparse_coo, dense -> sparse_coo}
- backward_api : to_sparse_coo_grad - backward_op : to_sparse_coo_grad
forward : to_sparse_coo(Tensor x, int64_t sparse_dim) -> Tensor(out) forward : to_sparse_coo(Tensor x, int64_t sparse_dim) -> Tensor(out)
args : (Tensor out_grad) args : (Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
kernel : kernel :
func : coo_to_dense { sparse_coo -> dense } func : coo_to_dense { sparse_coo -> dense }
- backward_api : values_grad - backward_op : values_grad
forward : values_coo(Tensor x) -> Tensor(out) forward : values_coo(Tensor x) -> Tensor(out)
args : (Tensor x, Tensor out_grad) args : (Tensor x, Tensor out_grad)
output : Tensor(x_grad) output : Tensor(x_grad)
kernel : kernel :
func : values_coo_grad{sparse_coo, dense-> sparse_coo} func : values_coo_grad{sparse_coo, dense-> sparse_coo}
- backward_api: fused_attention_grad - backward_op: fused_attention_grad
forward : fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax) forward : fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax)
args: (Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad) args: (Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad)
output : Tensor(query_grad), Tensor(key_grad), Tensor(value_grad) output : Tensor(query_grad), Tensor(key_grad), Tensor(value_grad)
......
paddle/phi/api/yaml/sparse_api.yaml → paddle/phi/api/yaml/sparse_ops.yaml
浏览文件 @ 8caaf85a
- api : abs - op : abs
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -7,7 +7,7 @@ ...@@ -7,7 +7,7 @@
layout : x layout : x
backward : abs_grad backward : abs_grad
- api : acos - op : acos
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -16,7 +16,7 @@ ...@@ -16,7 +16,7 @@
layout : x layout : x
backward : acos_grad backward : acos_grad
- api : acosh - op : acosh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -25,7 +25,7 @@ ...@@ -25,7 +25,7 @@
layout : x layout : x
backward : acosh_grad backward : acosh_grad
- api : add - op : add
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -34,7 +34,7 @@ ...@@ -34,7 +34,7 @@
layout : x layout : x
backward : add_grad backward : add_grad
- api : asin - op : asin
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -43,7 +43,7 @@ ...@@ -43,7 +43,7 @@
layout : x layout : x
backward : asin_grad backward : asin_grad
- api : asinh - op : asinh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -52,7 +52,7 @@ ...@@ -52,7 +52,7 @@
layout : x layout : x
backward : asinh_grad backward : asinh_grad
- api : atan - op : atan
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -61,7 +61,7 @@ ...@@ -61,7 +61,7 @@
layout : x layout : x
backward : atan_grad backward : atan_grad
- api : atanh - op : atanh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -70,7 +70,7 @@ ...@@ -70,7 +70,7 @@
layout : x layout : x
backward : atanh_grad backward : atanh_grad
- api : cast - op : cast
args : (Tensor x, DataType index_dtype=DataType::UNDEFINED, DataType value_dtype=DataType::UNDEFINED) args : (Tensor x, DataType index_dtype=DataType::UNDEFINED, DataType value_dtype=DataType::UNDEFINED)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -80,7 +80,7 @@ ...@@ -80,7 +80,7 @@
data_type : x data_type : x
backward : cast_grad backward : cast_grad
- api : conv3d - op : conv3d
args : (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) args : (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key)
output : Tensor(out), Tensor(rulebook), Tensor(counter) output : Tensor(out), Tensor(rulebook), Tensor(counter)
kernel : kernel :
...@@ -89,7 +89,7 @@ ...@@ -89,7 +89,7 @@
intermediate: rulebook, counter intermediate: rulebook, counter
backward : conv3d_coo_grad backward : conv3d_coo_grad
- api : divide - op : divide
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -98,7 +98,7 @@ ...@@ -98,7 +98,7 @@
layout : x layout : x
backward : divide_grad backward : divide_grad
- api : divide_scalar - op : divide_scalar
args : (Tensor x, float scalar) args : (Tensor x, float scalar)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -106,7 +106,7 @@ ...@@ -106,7 +106,7 @@
divide_csr_scalar{sparse_csr -> sparse_csr} divide_csr_scalar{sparse_csr -> sparse_csr}
backward : divide_scalar_grad backward : divide_scalar_grad
- api : expm1 - op : expm1
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -115,7 +115,7 @@ ...@@ -115,7 +115,7 @@
layout : x layout : x
backward : expm1_grad backward : expm1_grad
- api : leaky_relu - op : leaky_relu
args : (Tensor x, float alpha) args : (Tensor x, float alpha)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -124,7 +124,7 @@ ...@@ -124,7 +124,7 @@
layout : x layout : x
backward : leaky_relu_grad backward : leaky_relu_grad
- api : log1p - op : log1p
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -133,7 +133,7 @@ ...@@ -133,7 +133,7 @@
layout : x layout : x
backward : log1p_grad backward : log1p_grad
- api : multiply - op : multiply
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -142,7 +142,7 @@ ...@@ -142,7 +142,7 @@
layout : x layout : x
backward : multiply_grad backward : multiply_grad
- api : pow - op : pow
args : (Tensor x, float factor) args : (Tensor x, float factor)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -151,7 +151,7 @@ ...@@ -151,7 +151,7 @@
layout : x layout : x
backward : pow_grad backward : pow_grad
- api : relu - op : relu
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -160,7 +160,7 @@ ...@@ -160,7 +160,7 @@
layout : x layout : x
backward : relu_grad backward : relu_grad
- api : relu6 - op : relu6
args : (Tensor x, float threshold) args : (Tensor x, float threshold)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -169,7 +169,7 @@ ...@@ -169,7 +169,7 @@
layout : x layout : x
backward : relu6_grad backward : relu6_grad
- api : scale - op : scale
args : (Tensor x, float scale, float bias, bool bias_after_scale) args : (Tensor x, float scale, float bias, bool bias_after_scale)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -177,7 +177,7 @@ ...@@ -177,7 +177,7 @@
scale_csr{sparse_csr -> sparse_csr} scale_csr{sparse_csr -> sparse_csr}
backward : scale_grad backward : scale_grad
- api : sin - op : sin
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -186,7 +186,7 @@ ...@@ -186,7 +186,7 @@
layout : x layout : x
backward : sin_grad backward : sin_grad
- api : sinh - op : sinh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -195,7 +195,7 @@ ...@@ -195,7 +195,7 @@
layout : x layout : x
backward : sinh_grad backward : sinh_grad
- api : softmax - op : softmax
args : (Tensor x, int axis=-1) args : (Tensor x, int axis=-1)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -203,7 +203,7 @@ ...@@ -203,7 +203,7 @@
layout : x layout : x
backward : softmax_grad backward : softmax_grad
- api : sparse_coo_tensor - op : sparse_coo_tensor
args : (Tensor values, Tensor indices, IntArray dense_shape) args : (Tensor values, Tensor indices, IntArray dense_shape)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -212,7 +212,7 @@ ...@@ -212,7 +212,7 @@
data_type : values data_type : values
backward : sparse_coo_tensor_grad backward : sparse_coo_tensor_grad
- api : sqrt - op : sqrt
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -221,7 +221,7 @@ ...@@ -221,7 +221,7 @@
layout : x layout : x
backward : sqrt_grad backward : sqrt_grad
- api : square - op : square
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -230,7 +230,7 @@ ...@@ -230,7 +230,7 @@
layout : x layout : x
backward : square_grad backward : square_grad
- api : subtract - op : subtract
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -239,7 +239,7 @@ ...@@ -239,7 +239,7 @@
layout : x layout : x
backward : subtract_grad backward : subtract_grad
- api : tan - op : tan
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -248,7 +248,7 @@ ...@@ -248,7 +248,7 @@
layout : x layout : x
backward : tan_grad backward : tan_grad
- api : tanh - op : tanh
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -257,7 +257,7 @@ ...@@ -257,7 +257,7 @@
layout : x layout : x
backward : tanh_grad backward : tanh_grad
- api : to_dense - op : to_dense
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -265,7 +265,7 @@ ...@@ -265,7 +265,7 @@
csr_to_dense {sparse_csr -> dense} csr_to_dense {sparse_csr -> dense}
backward : to_dense_grad backward : to_dense_grad
- api : to_sparse_coo - op : to_sparse_coo
args : (Tensor x, int64_t sparse_dim) args : (Tensor x, int64_t sparse_dim)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -273,14 +273,14 @@ ...@@ -273,14 +273,14 @@
csr_to_coo { sparse_csr -> sparse_coo} csr_to_coo { sparse_csr -> sparse_coo}
backward : to_sparse_coo_grad backward : to_sparse_coo_grad
- api : to_sparse_csr - op : to_sparse_csr
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
func : dense_to_csr {dense -> sparse_csr}, func : dense_to_csr {dense -> sparse_csr},
coo_to_csr {sparse_coo -> sparse_csr} coo_to_csr {sparse_coo -> sparse_csr}
- api : values - op : values
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -289,7 +289,7 @@ ...@@ -289,7 +289,7 @@
layout : x layout : x
backward : values_grad backward : values_grad
- api: addmm - op: addmm
args : (Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) args : (Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -300,14 +300,14 @@ ...@@ -300,14 +300,14 @@
layout : x layout : x
backward: addmm_grad backward: addmm_grad
- api: coalesce - op: coalesce
args : (Tensor x) args : (Tensor x)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
func: coalesce{sparse_coo -> sparse_coo} func: coalesce{sparse_coo -> sparse_coo}
layout : x layout : x
- api: full_like - op: full_like
args : (Tensor x, Scalar value, DataType dtype=DataType::UNDEFINED) args : (Tensor x, Scalar value, DataType dtype=DataType::UNDEFINED)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -316,7 +316,7 @@ ...@@ -316,7 +316,7 @@
layout : x layout : x
data_type : dtype data_type : dtype
- api: fused_attention - op: fused_attention
args : (Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) args : (Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask)
output : Tensor(out), Tensor(softmax) output : Tensor(out), Tensor(softmax)
kernel : kernel :
...@@ -327,7 +327,7 @@ ...@@ -327,7 +327,7 @@
intermediate : softmax intermediate : softmax
backward: fused_attention_grad backward: fused_attention_grad
- api: masked_matmul - op: masked_matmul
args : (Tensor x, Tensor y, Tensor mask) args : (Tensor x, Tensor y, Tensor mask)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -335,7 +335,7 @@ ...@@ -335,7 +335,7 @@
layout : x layout : x
backward: masked_matmul_grad backward: masked_matmul_grad
- api: matmul - op: matmul
args : (Tensor x, Tensor y) args : (Tensor x, Tensor y)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
...@@ -346,7 +346,7 @@ ...@@ -346,7 +346,7 @@
layout : x layout : x
backward: matmul_grad backward: matmul_grad
- api: maxpool - op: maxpool
args : (Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) args : (Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides)
output : Tensor(out), Tensor(rulebook), Tensor(counter) output : Tensor(out), Tensor(rulebook), Tensor(counter)
kernel : kernel :
...@@ -355,7 +355,7 @@ ...@@ -355,7 +355,7 @@
intermediate : rulebook, counter intermediate : rulebook, counter
backward : maxpool_grad backward : maxpool_grad
- api: mv - op: mv
args : (Tensor x, Tensor vec) args : (Tensor x, Tensor vec)
output : Tensor(out) output : Tensor(out)
kernel : kernel :
......
paddle/phi/api/yaml/strings_api.yaml → paddle/phi/api/yaml/strings_ops.yaml
浏览文件 @ 8caaf85a
- api : empty - op : empty
args : (IntArray shape, Place place=CPUPlace()) args : (IntArray shape, Place place=CPUPlace())
output : Tensor(out@StringTensor) output : Tensor(out@StringTensor)
infer_meta : infer_meta :
...@@ -9,7 +9,7 @@ ...@@ -9,7 +9,7 @@
param : [shape] param : [shape]
backend : place backend : place
- api : empty_like - op : empty_like
args : (Tensor x, Place place = {}) args : (Tensor x, Place place = {})
output : Tensor(out@StringTensor) output : Tensor(out@StringTensor)
infer_meta : infer_meta :
...@@ -20,7 +20,7 @@ ...@@ -20,7 +20,7 @@
param : [x] param : [x]
backend : place > x backend : place > x
- api : lower - op : lower
args : (Tensor x, bool use_utf8_encoding) args : (Tensor x, bool use_utf8_encoding)
output : Tensor(out@StringTensor) output : Tensor(out@StringTensor)
infer_meta : infer_meta :
...@@ -29,7 +29,7 @@ ...@@ -29,7 +29,7 @@
kernel : kernel :
func : strings_lower func : strings_lower
- api : upper - op : upper
args : (Tensor x, bool use_utf8_encoding) args : (Tensor x, bool use_utf8_encoding)
output : Tensor(out@StringTensor) output : Tensor(out@StringTensor)
infer_meta : infer_meta :
......
paddle/phi/infermeta/unary.cc
浏览文件 @ 8caaf85a
...@@ -3537,7 +3537,7 @@ void StridedSliceInferMeta(const MetaTensor& x, ...@@ -3537,7 +3537,7 @@ void StridedSliceInferMeta(const MetaTensor& x,
/* Why not use SumRawInferMeta directly? /* Why not use SumRawInferMeta directly?
Because we need make InferMetaFunction's args follow the design of Because we need make InferMetaFunction's args follow the design of
api.yaml ops.yaml
*/ */
void SumInferMeta(const MetaTensor& x, void SumInferMeta(const MetaTensor& x,
const IntArray& axis, const IntArray& axis,
......
python/paddle/fluid/tests/unittests/test_assign_op.py
浏览文件 @ 8caaf85a
...@@ -24,6 +24,9 @@ import paddle.fluid as fluid ...@@ -24,6 +24,9 @@ import paddle.fluid as fluid
from paddle.fluid import compiler, Program, program_guard from paddle.fluid import compiler, Program, program_guard
from paddle.fluid.backward import append_backward from paddle.fluid.backward import append_backward
import paddle.fluid.framework as framework import paddle.fluid.framework as framework
import gradient_checker
from decorator_helper import prog_scope
import paddle.fluid.layers as layers
class TestAssignOp(op_test.OpTest): class TestAssignOp(op_test.OpTest):
...@@ -258,5 +261,79 @@ class TestAssignOpErrorApi(unittest.TestCase): ...@@ -258,5 +261,79 @@ class TestAssignOpErrorApi(unittest.TestCase):
paddle.disable_static() paddle.disable_static()
class TestAssignDoubleGradCheck(unittest.TestCase):
def assign_wrapper(self, x):
return paddle.fluid.layers.assign(x[0])
@prog_scope()
def func(self, place):
# the shape of input variable should be clearly specified, not inlcude -1.
eps = 0.005
dtype = np.float32
data = layers.data('data', [3, 4, 5], False, dtype)
data.persistable = True
out = paddle.fluid.layers.assign(data)
data_arr = np.random.uniform(-1, 1, data.shape).astype(dtype)
gradient_checker.double_grad_check([data],
out,
x_init=[data_arr],
place=place,
eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.double_grad_check_for_dygraph(self.assign_wrapper,
[data],
out,
x_init=[data_arr],
place=place)
def test_grad(self):
paddle.enable_static()
places = [fluid.CPUPlace()]
if core.is_compiled_with_cuda():
places.append(fluid.CUDAPlace(0))
for p in places:
self.func(p)
class TestAssignTripleGradCheck(unittest.TestCase):
def assign_wrapper(self, x):
return paddle.fluid.layers.assign(x[0])
@prog_scope()
def func(self, place):
# the shape of input variable should be clearly specified, not inlcude -1.
eps = 0.005
dtype = np.float32
data = layers.data('data', [3, 4, 5], False, dtype)
data.persistable = True
out = paddle.fluid.layers.assign(data)
data_arr = np.random.uniform(-1, 1, data.shape).astype(dtype)
gradient_checker.triple_grad_check([data],
out,
x_init=[data_arr],
place=place,
eps=eps)
fluid.set_flags({"FLAGS_retain_grad_for_all_tensor": True})
gradient_checker.triple_grad_check_for_dygraph(self.assign_wrapper,
[data],
out,
x_init=[data_arr],
place=place)
def test_grad(self):
paddle.enable_static()
places = [fluid.CPUPlace()]
if core.is_compiled_with_cuda():
places.append(fluid.CUDAPlace(0))
for p in places:
self.func(p)
if __name__ == '__main__': if __name__ == '__main__':
unittest.main() unittest.main()
tools/infrt/generate_phi_kernel_dialect.py
浏览文件 @ 8caaf85a
...@@ -64,7 +64,7 @@ def get_skipped_kernel_list(): ...@@ -64,7 +64,7 @@ def get_skipped_kernel_list():
for api in infer_meta_data: for api in infer_meta_data:
if "kernel" not in api or "infer_meta" not in api: if "kernel" not in api or "infer_meta" not in api:
continue continue
if api["api"] in skiped_api_list["phi_apis"]: if api["op"] in skiped_api_list["phi_apis"]:
skiped_kernel_list.append(api["kernel"]["func"]) skiped_kernel_list.append(api["kernel"]["func"])
skiped_kernel_list += skiped_api_list["phi_kernels"] skiped_kernel_list += skiped_api_list["phi_kernels"]
return skiped_kernel_list return skiped_kernel_list
......
tools/infrt/get_phi_kernel_info.py
浏览文件 @ 8caaf85a
...@@ -39,7 +39,7 @@ def get_skipped_kernel_list(): ...@@ -39,7 +39,7 @@ def get_skipped_kernel_list():
for api in infer_meta_data: for api in infer_meta_data:
if "kernel" not in api or "infer_meta" not in api: if "kernel" not in api or "infer_meta" not in api:
continue continue
if api["api"] in skiped_api_list["phi_apis"]: if api["op"] in skiped_api_list["phi_apis"]:
skiped_kernel_list.append(api["kernel"]["func"]) skiped_kernel_list.append(api["kernel"]["func"])
skiped_kernel_list += skiped_api_list["phi_kernels"] skiped_kernel_list += skiped_api_list["phi_kernels"]
return skiped_kernel_list return skiped_kernel_list
......
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