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提交 1d755225 编写于 作者: J jim19930609
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Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into... 

Merge branch 'develop' of https://github.com/PaddlePaddle/Paddle into eager_dygraph_final_state_auto_codegen
上级 c292c9ff 43919d0a
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Showing with 7732 addition and 3247 deletion
.gitignore
浏览文件 @ 1d755225
......@@ -4,7 +4,8 @@ paddle/fluid/API_DEV.spec
paddle/fluid/API_PR.spec
paddle/fluid/op_use_default_grad_maker_DEV.spec
paddle/fluid/op_use_default_grad_maker_PR.spec
paddle/pten/api/*/api*
paddle/pten/api/*/api.*
paddle/pten/api/*/backward*
paddle/pten/include/*
paddle/pten/extension.h
......
cmake/external/xpu.cmake
浏览文件 @ 1d755225
......@@ -36,7 +36,7 @@ ENDIF()
if(NOT DEFINED XPU_BASE_URL)
SET(XPU_BASE_URL_WITHOUT_DATE "https://baidu-kunlun-product.cdn.bcebos.com/KL-SDK/klsdk-dev")
SET(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20220104")
SET(XPU_BASE_URL "${XPU_BASE_URL_WITHOUT_DATE}/20220116")
else()
SET(XPU_BASE_URL "${XPU_BASE_URL}")
endif()
......
paddle/fluid/distributed/service/brpc_utils.h
浏览文件 @ 1d755225
......@@ -27,7 +27,7 @@ limitations under the License. */
#include "paddle/fluid/framework/selected_rows_utils.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/framework/var_type.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace butil {
class IOBuf;
......@@ -78,11 +78,11 @@ void DeserializeFromMultiVarMsgAndIOBuf(const MultiVarMsg& multi_msg,
const framework::Scope* scope);
void DeserializeLodTensor(framework::Variable* var, const VarMsg& msg,
butil::IOBufBytesIterator& iobuf,
butil::IOBufBytesIterator& iobuf, // NOLINT
const platform::DeviceContext& ctx);
void DeserializeSelectedRows(framework::Variable* var, const VarMsg& msg,
butil::IOBufBytesIterator& iobuf,
butil::IOBufBytesIterator& iobuf, // NOLINT
const platform::DeviceContext& ctx);
std::string GetIntTypeEndpoint(const std::string& ip, const uint32_t& port);
......
paddle/fluid/distributed/table/depends/large_scale_kv.h
浏览文件 @ 1d755225
......@@ -40,9 +40,9 @@
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/string/printf.h"
#include "paddle/fluid/string/string_helper.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace distributed {
......@@ -202,7 +202,7 @@ class ValueBlock {
// value = _alloc.acquire(value_length_);
table[id] = value;
} else {
value = (VALUE *)(void *)(res->second);
value = (VALUE *)(void *)(res->second); // NOLINT
}
return value;
}
......@@ -282,8 +282,8 @@ class ValueBlock {
value->unseen_days_++;
if (value->unseen_days_ >= threshold) {
butil::return_object(iter->second);
//_alloc.release(iter->second);
//_alloc.release(value);
// _alloc.release(iter->second);
// _alloc.release(value);
iter = table.erase(iter);
} else {
++iter;
......
paddle/fluid/eager/accumulation/gradient_accumulation.cc
浏览文件 @ 1d755225
......@@ -216,8 +216,9 @@ void TensorAdd(const egr::EagerTensor& src, egr::EagerTensor* dst) {
#define PADDLE_TENSOR_ADD(cpp_type) \
if (data_type == paddle::framework::DataTypeTrait<cpp_type>::DataType()) { \
TensorAddFunctor<cpp_type> func(numel, src_tensor->data<cpp_type>(), \
dst_tensor->mutable_data<cpp_type>()); \
TensorAddFunctor<cpp_type> func( \
numel, src_tensor->data<cpp_type>(), \
dst_tensor->mutable_data<cpp_type>(place)); \
paddle::platform::VisitPlace(place, func); \
return; \
}
......
paddle/fluid/eager/auto_code_generator/CMakeLists.txt
浏览文件 @ 1d755225
add_subdirectory(final_state_generator)
#add_subdirectory(final_state_generator)
set(EAGER_GENERETOR_DEPS ${GLOB_OP_LIB} ${GLOB_OPERATOR_DEPS} pybind proto_desc executor layer tracer engine imperative_profiler imperative_flag)
......
paddle/fluid/eager/auto_code_generator/final_state_generator/eager_gen.py
浏览文件 @ 1d755225
......@@ -75,6 +75,10 @@ def GetAutoGradMetaName(string):
return f"{string}_autograd_meta"
def GetAutoGradMetaVectorName(string):
return f"{string}_autograd_meta_vec"
######################
### File Readers ###
######################
......@@ -219,10 +223,6 @@ def ParseYamlBackward(args_str, returns_str):
def ForwardsValidationCheck(forward_inputs_list, forward_attrs_list,
forward_returns_list, orig_forward_inputs_list,
orig_forward_attrs_list, orig_forward_returns_list):
# inputs_list = [ [input_name, input_type, orig_position], ...]
# attrs_list = [ [attr_name, attr_type, default_value, orig_position], ...]
# forward_returns_list = [ [ret_name, ret_type, orig_position] ...]
# orig_returns_list = [ [ret_type, orig_position], ...]
for i in range(len(forward_inputs_list)):
forward_input_name = forward_inputs_list[i][0]
forward_input_type = forward_inputs_list[i][1]
......@@ -270,9 +270,6 @@ def ForwardsValidationCheck(forward_inputs_list, forward_attrs_list,
def BackwardValidationCheck(backward_fwd_input_map, backward_grad_input_map,
backward_attrs_list):
# backward_fwd_input_map = { "name" : [type, is_fwd_input, orig_position] ...}
# backward_grad_input_map = { "name" : [type, fwd_position, orig_position] ...}
# backward_attrs_list = [ [attr_name, attr_type, default_value, orig_position], ...]
# Check Order: TensorWrappers, GradTensors, Attributes
max_fwd_input_position = -1
......@@ -291,10 +288,6 @@ def BackwardValidationCheck(backward_fwd_input_map, backward_grad_input_map,
def DetermineForwardPositionMap(forward_inputs_list, forward_returns_list):
# inputs_list = [ [input_name, input_type, orig_position], ...]
# forward_returns_list = [ [ret_name, ret_type, orig_position] ...]
# forward_position_map = { "name" : [type, fwd_position] ...}
forward_inputs_position_map = {}
forward_outputs_position_map = {}
for i in range(len(forward_inputs_list)):
......@@ -319,15 +312,6 @@ def DetermineForwardPositionMap(forward_inputs_list, forward_returns_list):
def SlotNameMatching(backward_inputs_list, backward_returns_list,
forward_inputs_position_map, forward_outputs_position_map):
# backward_inputs_list = [ [input_name, input_type, orig_position], ...]
# backward_returns_list = [ [ret_name, ret_type, orig_position], ...]
# forward_inputs_position_map = { "name" : [type, fwd_position] }
# forward_outputs_position_map = { "name" : [type, fwd_position] }
# backward_fwd_input_map = { "name" : [type, is_fwd_input, orig_position] ...}
# backward_grad_input_map = { "name" : [type, fwd_position, orig_position] ...}
# backward_grad_output_map = { "name" : [type, fwd_position, orig_position] ...}
backward_fwd_input_map = {}
backward_grad_input_map = {}
backward_grad_output_map = {}
......@@ -580,7 +564,14 @@ def GenerateNodeCreationCodes(fwd_api_name, bwd_api_name,
compute_require_grad_args_list = ["trace_backward"]
for name, (ttype, pos) in forward_inputs_position_map.items():
input_autograd_meta_name = GetAutoGradMetaName(name)
input_autograd_meta = f" auto* {input_autograd_meta_name} = egr::EagerUtils::nullable_autograd_meta({name});"
if IsPlainTensorType(ttype):
input_autograd_meta = f" egr::EagerTensor* {input_autograd_meta_name} = egr::EagerUtils::nullable_autograd_meta({name});"
else:
assert IsVectorTensorType(ttype)
input_autograd_meta_vec_name = GetAutoGradMetaVectorName(name)
input_autograd_meta = f" std::vector<egr::EagerTensor*> {input_autograd_meta_vec_name} = egr::EagerUtils::nullable_autograd_meta({name});\n"
input_autograd_meta += f" std::vector<egr::EagerTensor*>* {input_autograd_meta_name} = &{input_autograd_meta_vec_name};"
inputs_autograd_meta_list.append(input_autograd_meta)
compute_require_grad_args_list.append(input_autograd_meta_name)
inputs_autograd_meta_str = "\n".join(inputs_autograd_meta_list)
......@@ -592,11 +583,23 @@ def GenerateNodeCreationCodes(fwd_api_name, bwd_api_name,
num_fwd_outputs = len(forward_outputs_position_map.keys())
for name, (rtype, pos) in forward_outputs_position_map.items():
output_autograd_meta_name = GetAutoGradMetaName(name)
output_autograd_meta_vec_name = GetAutoGradMetaVectorName(name)
if num_fwd_outputs == 1:
output_autograd_meta = f" auto* {output_autograd_meta_name} = egr::EagerUtils::autograd_meta(outputs);"
if IsPlainTensorType(rtype):
output_autograd_meta = f" egr::EagerTensor* {output_autograd_meta_name} = egr::EagerUtils::autograd_meta(outputs);"
else:
assert IsVectorTensorType(rtype)
output_autograd_meta = f" std::vector<egr::EagerTensor*> {output_autograd_meta_vec_name} = egr::EagerUtils::nullable_autograd_meta({outputs});\n"
output_autograd_meta += f" std::vector<egr::EagerTensor*>* {output_autograd_meta_name} = &{output_autograd_meta_vec_name};"
else:
# Tuple api_result
outputs_autograd_meta = f" auto* {output_autograd_meta_name} = egr::EagerUtils::autograd_meta(outputs[{pos}]);"
if IsPlainTensorType(rtype):
outputs_autograd_meta = f" egr::EagerTensor* {output_autograd_meta_name} = egr::EagerUtils::autograd_meta(outputs[{pos}]);"
else:
assert IsVectorTensorType(rtype)
output_autograd_meta = f" std::vector<egr::EagerTensor*> {output_autograd_meta_vec_name} = egr::EagerUtils::nullable_autograd_meta(outputs[{pos}]);\n"
output_autograd_meta += f" std::vector<egr::EagerTensor*>* {output_autograd_meta_name} = &{output_autograd_meta_vec_name};"
outputs_autograd_meta_list.append(output_autograd_meta)
pass_stop_gradient_args_list.append(output_autograd_meta_name)
......@@ -786,7 +789,6 @@ def GenerateForwardDefinition(fwd_api_name, bwd_api_name,
auto outputs = {};
// Node Creation
{}
// Returns
......@@ -903,17 +905,10 @@ if __name__ == "__main__":
# Collect Forward Inputs/Outputs
forward_inputs_list, forward_attrs_list, forward_returns_list = ParseYamlForwardFromBackward(
bwd_forward_str)
print("Parsed Forward Inputs List: ", forward_inputs_list)
print("Prased Forward Attrs List: ", forward_attrs_list)
print("Parsed Forward Returns List: ", forward_returns_list)
# Collect Original Forward Inputs/Outputs and then perform validation checks
orig_forward_inputs_list, orig_forward_attrs_list, orig_forward_returns_list = ParseYamlForward(
fwd_args_str, fwd_returns_str)
print("Parsed Original Forward Inputs List: ", orig_forward_inputs_list)
print("Prased Original Forward Attrs List: ", orig_forward_attrs_list)
print("Parsed Original Forward Returns List: ",
orig_forward_returns_list)
# Forward Validation Checks
ForwardsValidationCheck(forward_inputs_list, forward_attrs_list,
......@@ -924,25 +919,15 @@ if __name__ == "__main__":
# Parse Backward Inputs/Outputs
backward_inputs_list, backward_attrs_list, backward_returns_list = ParseYamlBackward(
bwd_args_str, bwd_returns_str)
print("Parsed Backward Inputs List: ", backward_inputs_list)
print("Prased Backward Attrs List: ", backward_attrs_list)
print("Parsed Backward Returns List: ", backward_returns_list)
# Determine Forward Inputs/Outputs Position
forward_inputs_position_map, forward_outputs_position_map = DetermineForwardPositionMap(
forward_inputs_list, forward_returns_list)
print("Generated Forward Input Position Map: ",
forward_inputs_position_map)
print("Generated Forward Output Position Map: ",
forward_outputs_position_map)
# SlotName Matching
backward_fwd_input_map, backward_grad_input_map, backward_grad_output_map = SlotNameMatching(
backward_inputs_list, backward_returns_list,
forward_inputs_position_map, forward_outputs_position_map)
print("Generated Backward Fwd Input Map: ", backward_fwd_input_map)
print("Generated Backward Grad Input Map: ", backward_grad_input_map)
print("Generated Backward Grad Output Map: ", backward_grad_output_map)
# Backward Validation Check
BackwardValidationCheck(backward_fwd_input_map, backward_grad_input_map,
......@@ -951,13 +936,11 @@ if __name__ == "__main__":
# Node Declaration Generation
node_declaration_str += GenerateNodeDeclaration(
fwd_api_name, backward_fwd_input_map, backward_attrs_list)
print("Generated Node Declaration: ", node_declaration_str)
node_definition_str += GenerateNodeDefinition(
fwd_api_name, bwd_api_name, backward_fwd_input_map,
backward_grad_input_map, backward_grad_output_map,
backward_attrs_list)
print("Generated Node Definition: ", node_definition_str)
# Node Definition Generation
definition_declaration_pair = GenerateForwardDefinition(
......@@ -965,8 +948,6 @@ if __name__ == "__main__":
forward_outputs_position_map, forward_attrs_list,
backward_fwd_input_map, backward_grad_input_map,
backward_grad_output_map, backward_attrs_list)
print("Generated Forward Definition: ", forward_definition_str)
print("Generated Forward Declaration: ", forward_declaration_str)
forward_definition_str += definition_declaration_pair[0]
forward_declaration_str += definition_declaration_pair[1]
......
paddle/fluid/eager/tests/data_structure_tests/accumulation_node_test.cc
浏览文件 @ 1d755225
......@@ -36,7 +36,8 @@ TEST(AccumulationNode, EagerTensor) {
paddle::platform::CPUPlace())
.get(),
meta);
dt0->mutable_data<paddle::platform::float16>()[0] = 10.0;
dt0->mutable_data<paddle::platform::float16>(
paddle::platform::CPUPlace())[0] = 10.0;
EagerTensor et0 = EagerTensor(dt0);
std::shared_ptr<pten::DenseTensor> dt1 = std::make_shared<pten::DenseTensor>(
......@@ -45,7 +46,8 @@ TEST(AccumulationNode, EagerTensor) {
.get(),
meta);
dt1->mutable_data<paddle::platform::float16>()[0] = 20.0;
dt1->mutable_data<paddle::platform::float16>(
paddle::platform::CPUPlace())[0] = 20.0;
EagerTensor et1 = EagerTensor(dt1);
std::shared_ptr<pten::DenseTensor> grad_dt =
......
paddle/fluid/eager/tests/data_structure_tests/autograd_meta_test.cc
浏览文件 @ 1d755225
......@@ -46,7 +46,7 @@ TEST(AutogradMeta, MemberFunction) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 5.0f;
dt_ptr[1] = 10.0f;
grad_t->set_impl(dt);
......
paddle/fluid/eager/tests/data_structure_tests/eager_tensor_test.cc
浏览文件 @ 1d755225
......@@ -40,7 +40,7 @@ TEST(EagerTensor, Constructor) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 5.0f;
dt_ptr[1] = 10.0f;
egr::EagerTensor et3 = egr::EagerTensor(dt);
......@@ -70,7 +70,7 @@ TEST(EagerTensor, MemberFunction) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 5.0f;
dt_ptr[1] = 10.0f;
VLOG(6) << "Make Dense Tensor";
......
paddle/fluid/eager/tests/data_structure_tests/grad_node_info_test.cc
浏览文件 @ 1d755225
......@@ -45,7 +45,7 @@ TEST(GradNodeInfo, GradNodeBase) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 5.0f;
egr::EagerTensor et1(dt);
grads = {{et1}};
......@@ -102,7 +102,7 @@ TEST(GradNodeInfo, GradNodeBase) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 6.0f;
auto* et_ptr =
std::dynamic_pointer_cast<pten::DenseTensor>(et.impl())->data<float>();
......@@ -121,8 +121,8 @@ TEST(GradNodeInfo, GradNodeBase) {
VLOG(6) << "Test Reduce Hook";
auto reduce_hook = [&](void) -> void {
auto* et_ptr = std::dynamic_pointer_cast<pten::DenseTensor>(et1.impl())
->mutable_data<float>();
auto* et_ptr =
std::dynamic_pointer_cast<pten::DenseTensor>(et1.impl())->data<float>();
et_ptr[0] = 100.0;
VLOG(6) << "Running Reduce Hook";
};
......
paddle/fluid/eager/tests/data_structure_tests/grad_node_test.h
浏览文件 @ 1d755225
......@@ -41,7 +41,7 @@ class GradTestNode : public egr::GradNodeBase {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 6.0f;
egr::EagerTensor et1(dt);
std::vector<std::vector<egr::EagerTensor>> res = {{et1}};
......
paddle/fluid/eager/tests/data_structure_tests/grad_tensor_holder_test.cc
浏览文件 @ 1d755225
......@@ -57,7 +57,7 @@ TEST(GradTensorHolder, Interfaces) {
paddle::platform::CPUPlace())
.get(),
meta);
dt0->mutable_data<float>()[0] = 10.0;
dt0->mutable_data<float>(paddle::platform::CPUPlace())[0] = 10.0;
EagerTensor et0 = EagerTensor(dt0);
std::shared_ptr<pten::DenseTensor> dt1 = std::make_shared<pten::DenseTensor>(
......@@ -65,7 +65,7 @@ TEST(GradTensorHolder, Interfaces) {
paddle::platform::CPUPlace())
.get(),
meta);
dt1->mutable_data<float>()[0] = 20.0;
dt1->mutable_data<float>(paddle::platform::CPUPlace())[0] = 20.0;
EagerTensor et1 = EagerTensor(dt1);
// Constructor empty GradTensorHolder
......
paddle/fluid/eager/tests/data_structure_tests/tensor_wrapper_test.cc
浏览文件 @ 1d755225
......@@ -29,7 +29,7 @@ TEST(TensorWrapper, Basic) {
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<float>();
auto* dt_ptr = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr[0] = 5.0f;
dt_ptr[1] = 10.0f;
et1.set_impl(dt);
......@@ -56,7 +56,7 @@ TEST(TensorWrapper, Basic) {
paddle::platform::CPUPlace())
.get(),
meta2);
auto* dt_ptr2 = dt->mutable_data<float>();
auto* dt_ptr2 = dt->mutable_data<float>(paddle::platform::CPUPlace());
dt_ptr2[0] = 6.0f;
dt_ptr2[1] = 11.0f;
et2.set_impl(dt2);
......
paddle/fluid/eager/tests/task_tests/eager_utils_test.cc
浏览文件 @ 1d755225
......@@ -35,7 +35,7 @@ TEST(EagerUtils, AutoGradMeta) {
paddle::platform::CPUPlace())
.get(),
meta);
dt0->mutable_data<float>()[0] = 10.0;
dt0->mutable_data<float>(paddle::platform::CPUPlace())[0] = 10.0;
EagerTensor et0 = EagerTensor(dt0);
std::shared_ptr<pten::DenseTensor> dt1 = std::make_shared<pten::DenseTensor>(
......@@ -43,7 +43,7 @@ TEST(EagerUtils, AutoGradMeta) {
paddle::platform::CPUPlace())
.get(),
meta);
dt1->mutable_data<float>()[0] = 20.0;
dt1->mutable_data<float>(paddle::platform::CPUPlace())[0] = 20.0;
EagerTensor et1 = EagerTensor(dt1);
std::vector<EagerTensor> ets = {et0, et1};
......@@ -112,7 +112,7 @@ egr::EagerTensor CreateTestCPUTensor(T val,
paddle::platform::CPUPlace())
.get(),
meta);
auto* dt_ptr = dt->mutable_data<T>();
auto* dt_ptr = dt->mutable_data<T>(paddle::platform::CPUPlace());
for (int64_t i = 0; i < dt->numel(); i++) {
dt_ptr[i] = val;
}
......
paddle/fluid/eager/tests/task_tests/fwd_bwd_joint_test.cc
浏览文件 @ 1d755225
......@@ -44,8 +44,8 @@ egr::EagerTensor hook_function(const egr::EagerTensor& t) {
paddle::memory::Alloc(place, bytes_size)),
std::move(ret_meta));
float* t_ptr = t_dense->mutable_data<float>();
float* ret_ptr = ret_dense->mutable_data<float>();
float* t_ptr = t_dense->mutable_data<float>(place);
float* ret_ptr = ret_dense->mutable_data<float>(place);
for (int i = 0; i < ret_dense->numel(); i++) {
ret_ptr[i] = t_ptr[i] + 5.0;
}
......@@ -184,7 +184,7 @@ TEST(FwdBwdJoint, BranchedNodes) {
// Examine Forward Output 2
{
auto dense_out = std::dynamic_pointer_cast<pten::DenseTensor>(out2.impl());
float* ptr = dense_out->mutable_data<float>();
float* ptr = dense_out->mutable_data<float>(paddle::platform::CPUPlace());
for (int i = 0; i < 20; i++) {
PADDLE_ENFORCE(ptr[i] == 150.0,
paddle::platform::errors::Fatal(
......
paddle/fluid/eager/tests/task_tests/hook_test.cc
浏览文件 @ 1d755225
......@@ -45,8 +45,8 @@ egr::EagerTensor hook_function(const egr::EagerTensor& t) {
paddle::memory::Alloc(place, bytes_size)),
std::move(ret_meta));
float* t_ptr = t_dense->mutable_data<float>();
float* ret_ptr = ret_dense->mutable_data<float>();
float* t_ptr = t_dense->mutable_data<float>(place);
float* ret_ptr = ret_dense->mutable_data<float>(place);
for (int i = 0; i < ret_dense->numel(); i++) {
ret_ptr[i] = t_ptr[i] + 3.0;
}
......
paddle/fluid/eager/tests/test_utils.h
浏览文件 @ 1d755225
......@@ -34,7 +34,7 @@ bool CompareGradTensorWithValue(const egr::EagerTensor& target, T value) {
egr::AutogradMeta* meta = egr::EagerUtils::unsafe_autograd_meta(target);
auto grad_dense =
std::dynamic_pointer_cast<pten::DenseTensor>(meta->Grad().impl());
T* ptr = grad_dense->mutable_data<T>();
T* ptr = grad_dense->data<T>();
std::vector<T> host_data(grad_dense->numel());
if (paddle::platform::is_gpu_place(grad_dense->place())) {
......@@ -67,7 +67,7 @@ template <typename T>
bool CompareTensorWithValue(const egr::EagerTensor& target, T value) {
// TODO(jiabin): Support Selected Rows later
auto dense_t = std::dynamic_pointer_cast<pten::DenseTensor>(target.impl());
T* ptr = dense_t->mutable_data<T>();
T* ptr = dense_t->data<T>();
std::vector<T> host_data(dense_t->numel());
if (paddle::platform::is_gpu_place(dense_t->place())) {
......
paddle/fluid/framework/data_type.h
浏览文件 @ 1d755225
......@@ -20,9 +20,9 @@ limitations under the License. */
#include "paddle/fluid/framework/framework.pb.h"
#include "paddle/fluid/platform/bfloat16.h"
#include "paddle/fluid/platform/complex.h"
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/device_worker.h
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......@@ -38,8 +38,8 @@ limitations under the License. */
#include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/operators/reader/blocking_queue.h"
#include "paddle/fluid/platform/place.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/timer.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace framework {
......
paddle/fluid/framework/expect.h
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......@@ -19,14 +19,18 @@
#define _LINUX
#endif
#ifdef _LINUX
#ifndef likely
#define likely(x) __builtin_expect((x), 1)
#ifdef _LINUX
#define likely(expr) (__builtin_expect(!!(expr), 1))
#else
#define likely(expr) (expr)
#endif
#endif
#ifdef _LINUX
#ifndef unlikely
#define unlikely(x) __builtin_expect((x), 0)
#ifdef _LINUX
#define unlikely(expr) (__builtin_expect(!!(expr), 0))
#else
#define unlikely(expr) (expr)
#endif
#endif
paddle/fluid/framework/io/shell.cc
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......@@ -12,6 +12,7 @@
// See the License for the specific language governing permissions and
// limitations under the License.
#define GLOG_NO_ABBREVIATED_SEVERITIES // msvc conflict logging with windows.h
#include "paddle/fluid/framework/io/shell.h"
#include "paddle/fluid/platform/enforce.h"
......
paddle/fluid/framework/io/shell.h
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......@@ -34,8 +34,8 @@
#include <utility>
#include <vector>
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/string/string_helper.h"
#include "paddle/pten/backends/dynload/port.h"
#if defined(__arm__) || defined(__aarch64__) || defined(__ARM_NEON) || \
defined(__ARM_NEON__)
......
paddle/fluid/framework/trainer.h
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......@@ -34,7 +34,7 @@ limitations under the License. */
#include "paddle/fluid/framework/trainer_desc.pb.h"
#include "paddle/fluid/framework/variable_helper.h"
#include "paddle/fluid/operators/reader/blocking_queue.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace framework {
......
paddle/fluid/inference/analysis/analyzer_tester.cc
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......@@ -19,7 +19,7 @@
#include "paddle/fluid/inference/analysis/ut_helper.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/inference/api/paddle_inference_pass.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace inference {
......
paddle/fluid/inference/analysis/helper.h
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......@@ -28,7 +28,7 @@ limitations under the License. */
#include "paddle/fluid/framework/scope.h"
#include "paddle/fluid/framework/variable.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
#ifdef _WIN32
#include <direct.h>
......
paddle/fluid/inference/analysis/passes/memory_optimize_pass.h
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......@@ -20,7 +20,7 @@
#include <vector>
#include "paddle/fluid/inference/analysis/analysis_pass.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace framework {
......
paddle/fluid/inference/api/helper.h
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......@@ -31,8 +31,8 @@
#include "paddle/fluid/framework/data_type.h"
#include "paddle/fluid/inference/api/paddle_inference_api.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/string/printf.h"
#include "paddle/pten/backends/dynload/port.h"
extern std::string paddle::framework::DataTypeToString(
const framework::proto::VarType::Type type);
......
paddle/fluid/inference/tests/test_helper.h
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......@@ -22,8 +22,8 @@ limitations under the License. */
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/inference/io.h"
#include "paddle/fluid/platform/errors.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/profiler.h"
#include "paddle/pten/backends/dynload/port.h"
DECLARE_bool(use_mkldnn);
......
paddle/fluid/operators/CMakeLists.txt
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......@@ -8,7 +8,6 @@ set(pybind_file_final ${PADDLE_BINARY_DIR}/paddle/fluid/pybind/pybind.h)
file(WRITE ${pybind_file} "// Generated by the paddle/fluid/operators/CMakeLists.txt. DO NOT EDIT!\n\n")
add_subdirectory(math)
add_subdirectory(eigen)
add_subdirectory(controlflow)
add_subdirectory(detection)
add_subdirectory(elementwise)
......
paddle/fluid/operators/activation_op.cc
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......@@ -23,7 +23,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_version_registry.h"
#include "paddle/fluid/operators/common_infer_shape_functions.h"
#include "paddle/fluid/operators/mkldnn/mkldnn_activation_op.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
DECLARE_bool(use_mkldnn);
......
paddle/fluid/operators/controlflow/compare_op.h
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......@@ -22,49 +22,40 @@ limitations under the License. */
namespace paddle {
namespace operators {
template <typename T>
struct LessThanFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const { return a < b; }
};
template <typename T>
struct LessEqualFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const { return a <= b; }
};
template <typename T>
struct GreaterThanFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const { return a > b; }
};
template <typename T>
struct GreaterEqualFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const { return a >= b; }
};
template <typename T>
#define COMPARE_FUNCTOR(func_name, op) \
template <typename InT, typename OutT = bool> \
struct func_name { \
using ELEM_TYPE = InT; \
HOSTDEVICE OutT operator()(const InT a, const InT b) const { \
return static_cast<OutT>(a op b); \
} \
};
COMPARE_FUNCTOR(LessThanFunctor, <)
COMPARE_FUNCTOR(LessEqualFunctor, <=)
COMPARE_FUNCTOR(GreaterThanFunctor, >)
COMPARE_FUNCTOR(GreaterEqualFunctor, >=)
#undef COMPARE_FUNCTOR
template <typename InT, typename OutT = bool>
struct EqualFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const {
if (std::is_floating_point<T>::value) {
using ELEM_TYPE = InT;
HOSTDEVICE OutT operator()(const InT a, const InT b) const {
if (std::is_floating_point<InT>::value) {
// This branch will be optimized while compiling if T is integer. It is
// safe to cast a and b to double.
return fabs(static_cast<double>(a - b)) < 1e-8;
return static_cast<OutT>(fabs(static_cast<double>(a - b)) < 1e-8);
} else {
return (a == b);
return static_cast<OutT>(a == b);
}
}
};
template <typename T>
template <typename InT, typename OutT = bool>
struct NotEqualFunctor {
using ELEM_TYPE = T;
HOSTDEVICE bool operator()(const T a, const T b) const {
return !EqualFunctor<T>()(a, b);
using ELEM_TYPE = InT;
HOSTDEVICE bool operator()(const InT a, const InT b) const {
return !EqualFunctor<InT, OutT>()(a, b);
}
};
......
paddle/fluid/operators/eigen/CMakeLists.txt 已删除 100644 → 0
浏览文件 @ c292c9ff
file(GLOB EIGEN_CC_SOURCES RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.cc")
file(GLOB EIGEN_CU_SOURCES RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "*.cu")
if(WITH_GPU)
nv_library(eigen_function SRCS ${EIGEN_CC_SOURCES} ${EIGEN_CU_SOURCES} DEPS eigen3)
elseif(WITH_ROCM)
hip_library(eigen_function SRCS ${EIGEN_CC_SOURCES} ${EIGEN_CU_SOURCES} DEPS eigen3)
else()
cc_library(eigen_function SRCS ${EIGEN_CC_SOURCES} DEPS eigen3)
endif()
paddle/fluid/operators/eigen/eigen_function.h
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......@@ -18,243 +18,71 @@ limitations under the License. */
#ifndef NOMINMAX
#define NOMINMAX
#endif
#include "unsupported/Eigen/CXX11/Tensor"
#include "paddle/pten/kernels/funcs/eigen/eigen_function.h"
namespace paddle {
namespace operators {
template <typename EigenDevice, typename T, int Rank>
struct EigenBroadcast {
using Array = Eigen::DSizes<Eigen::DenseIndex, Rank>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using InType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<const T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
using OutType = Eigen::TensorMap<
Eigen::Tensor<T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
static void Eval(const EigenDevice& dev, OutType out, InType in,
const Array& bcast);
static void Eval(const EigenDevice& dev, OutType32BitIndex out,
InType32BitIndex in, const Array& bcast);
};
using EigenBroadcast = pten::funcs::EigenBroadcast<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T, int Rank>
struct EigenBroadcastGrad {
using Array = Eigen::DSizes<Eigen::DenseIndex, Rank>;
using Array2 = Eigen::DSizes<Eigen::DenseIndex, Rank * 2>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, InType in,
const Array& reduce_dims, const Array2& reshape_dims);
};
using EigenBroadcastGrad =
pten::funcs::EigenBroadcastGrad<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T, int Rank>
struct EigenConstant {
using Type = Eigen::TensorMap<
Eigen::Tensor<T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, Type out, const T value);
};
using EigenConstant = pten::funcs::EigenConstant<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T>
struct EigenSign {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in);
};
using EigenSign = pten::funcs::EigenSign<EigenDevice, T>;
template <typename EigenDevice, typename T, int Rank>
struct EigenReverse {
using Array = Eigen::DSizes<bool, Rank>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType = Eigen::TensorMap<
Eigen::Tensor<T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in,
const Array& reverse);
};
using EigenReverse = pten::funcs::EigenReverse<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T>
struct EigenAdd {
using InType = Eigen::TensorMap<Eigen::TensorFixedSize<
const T, Eigen::Sizes<>, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType = Eigen::TensorMap<Eigen::TensorFixedSize<
T, Eigen::Sizes<>, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in,
const T value);
};
using EigenAdd = pten::funcs::EigenAdd<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenSub {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& left,
const InType& right);
};
using EigenSub = pten::funcs::EigenSub<EigenDevice, T>;
template <typename EigenDevice, typename T, int Rank>
struct EigenSlice {
using Array = Eigen::DSizes<Eigen::DenseIndex, Rank>;
using Array32Bit = Eigen::DSizes<int, Rank>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using InType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<const T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
using OutType = Eigen::TensorMap<
Eigen::Tensor<T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in,
const Array& offsets, const Array& extents);
static void Eval(const EigenDevice& dev, OutType32BitIndex out,
const InType32BitIndex& in, const Array32Bit& offsets,
const Array32Bit& extents);
};
using EigenSlice = pten::funcs::EigenSlice<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T, int Rank>
struct EigenPad {
using Array = std::array<std::pair<int64_t, int64_t>, Rank>;
using Array32Bit = std::array<std::pair<int, int>, Rank>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using InType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<const T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
using OutType = Eigen::TensorMap<
Eigen::Tensor<T, Rank, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType32BitIndex =
Eigen::TensorMap<Eigen::Tensor<T, Rank, Eigen::RowMajor, int>,
Eigen::Aligned>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in,
const Array& padding, const T value);
static void Eval(const EigenDevice& dev, OutType32BitIndex out,
const InType32BitIndex& in, const Array32Bit& padding,
const T value);
};
using EigenPad = pten::funcs::EigenPad<EigenDevice, T, Rank>;
template <typename EigenDevice, typename T>
struct EigenScale {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in,
const T scale, const T bias, const bool bias_after_scale);
};
using EigenScale = pten::funcs::EigenScale<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenErf {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in);
};
using EigenErf = pten::funcs::EigenErf<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenErfGrad {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType din, const InType& in,
const InType& dout);
};
using EigenErfGrad = pten::funcs::EigenErfGrad<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenRankLoss {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& label,
const InType& left, const InType& right);
};
using EigenRankLoss = pten::funcs::EigenRankLoss<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenRankLossGrad {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void EvalLeft(const EigenDevice& dev, OutType dleft,
const InType& dout, const InType& label,
const InType& left, const InType& right);
static void EvalRight(const EigenDevice& dev, OutType dright,
const InType& dout, const InType& label,
const InType& left, const InType& right);
};
using EigenRankLossGrad = pten::funcs::EigenRankLossGrad<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenLogLoss {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& pred,
const InType& label, const T& epsilon);
};
using EigenLogLoss = pten::funcs::EigenLogLoss<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenLogLossGrad {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType dpred, const InType& dloss,
const InType& pred, const InType& label, const T& epsilon);
};
using EigenLogLossGrad = pten::funcs::EigenLogLossGrad<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenHingeLoss {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType loss, const InType& pred,
const InType& label);
};
using EigenHingeLoss = pten::funcs::EigenHingeLoss<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenHingeLossGrad {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType dpred, const InType& dloss,
const InType& pred, const InType& label);
};
using EigenHingeLossGrad = pten::funcs::EigenHingeLossGrad<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenL1Norm {
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType = Eigen::TensorMap<Eigen::TensorFixedSize<
T, Eigen::Sizes<>, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType out, const InType& in);
};
using EigenL1Norm = pten::funcs::EigenL1Norm<EigenDevice, T>;
template <typename EigenDevice, typename T>
struct EigenL1NormGrad {
using Array = Eigen::DSizes<Eigen::DenseIndex, 1>;
using InType = Eigen::TensorMap<
Eigen::Tensor<const T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
using OutType =
Eigen::TensorMap<Eigen::Tensor<T, 1, Eigen::RowMajor, Eigen::DenseIndex>>;
static void Eval(const EigenDevice& dev, OutType din, const InType& dout,
const InType& in, const Array& bcast);
};
using EigenL1NormGrad = pten::funcs::EigenL1NormGrad<EigenDevice, T>;
} // namespace operators
} // namespace paddle
paddle/fluid/operators/fused/mkldnn/fusion_gru_mkldnn_op.cc
浏览文件 @ 1d755225
......@@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/expect.h"
#include "paddle/fluid/operators/fused/fusion_gru_op.h"
#include "paddle/fluid/operators/fused/mkldnn/fusion_rnn_mkldnn.h"
......@@ -41,7 +42,7 @@ class GRUMKLDNNHandler : public RNNMKLDNNHandler<T, dnnl::gru_forward, T_out> {
ctx.InputName("X") + ctx.InputName("WeightH")) {
const bool is_INT8 = std::is_same<T, uint8_t>::value;
if (!this->isCached()) {
if (unlikely(!this->isCached())) {
// oneDNN kernel has hardcoded activation functions
PADDLE_ENFORCE_EQ(
ctx.Attr<std::string>("gate_activation"), "sigmoid",
......
paddle/fluid/operators/fused/mkldnn/fusion_lstm_mkldnn_op.cc
浏览文件 @ 1d755225
......@@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/expect.h"
#include "paddle/fluid/operators/fused/fusion_lstm_op.h"
#include "paddle/fluid/operators/fused/mkldnn/fusion_rnn_mkldnn.h"
......@@ -40,7 +41,7 @@ class LSTMMKLDNNHandler
ctx, dev_ctx, mkldnn_engine, ctx.GetPlace(), input, weight_h, h0,
is_reverse, N, Ti, IC, OC, 4,
ctx.InputName("X") + ctx.InputName("WeightH")) {
if (!this->isCached()) {
if (unlikely(!this->isCached())) {
const bool is_INT8 = std::is_same<T, uint8_t>::value;
const bool use_peepholes = ctx.Attr<bool>("use_peepholes");
// oneDNN kernel has hardcoded activation functions
......
paddle/fluid/operators/kernel_primitives/functor_primitives.h
浏览文件 @ 1d755225
......@@ -15,9 +15,9 @@
#pragma once
#include "paddle/fluid/operators/amp/fp16_type_traits.h"
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/float16.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/math/selected_rows_functor.cc
浏览文件 @ 1d755225
......@@ -477,6 +477,155 @@ struct MergeAdd<platform::CPUDeviceContext, T> {
}
};
#ifdef PADDLE_WITH_XPU
template <typename T>
struct MergeAdd<platform::XPUDeviceContext, T> {
framework::SelectedRows operator()(const platform::XPUDeviceContext& context,
const framework::SelectedRows& input,
const bool sorted_result = false) {
framework::SelectedRows out;
(*this)(context, input, &out, sorted_result);
return out;
}
void operator()(const platform::XPUDeviceContext& context,
const framework::SelectedRows& input,
framework::SelectedRows* output,
const bool sorted_result = false) {
framework::Vector<int64_t> input_rows(input.rows());
if (input_rows.size() == 0) {
return;
}
framework::SelectedRows& out = *output;
std::set<int64_t> row_set(input_rows.begin(), input_rows.end());
std::vector<int64_t> merge_rows(row_set.begin(), row_set.end());
auto input_width = input.value().dims()[1];
out.set_rows(merge_rows);
out.set_height(input.height());
out.mutable_value()->mutable_data<T>(
framework::make_ddim(
{static_cast<int64_t>(merge_rows.size()), input_width}),
context.GetPlace());
int r =
xpu::constant<T>(context.x_context(), out.mutable_value()->data<T>(),
merge_rows.size() * input_width, static_cast<T>(0.f));
PADDLE_ENFORCE_EQ(r, xpu::Error_t::SUCCESS,
platform::errors::External("XPU constant op return"
" wrong value[%d %s].",
r, XPUAPIErrorMsg[r]));
std::unordered_map<int64_t, size_t> rows_to_id;
for (size_t i = 0; i < merge_rows.size(); ++i) {
rows_to_id[merge_rows[i]] = i;
}
auto* out_data = out.mutable_value()->data<T>();
auto* input_data = input.value().data<T>();
int n = input_width;
for (size_t i = 0; i < input_rows.size(); i++) {
size_t out_i = rows_to_id[input_rows[i]];
auto r = xpu::add(context.x_context(), &input_data[i * input_width],
&out_data[out_i * input_width],
&out_data[out_i * input_width], n);
PADDLE_ENFORCE_EQ(
r, XPU_SUCCESS,
platform::errors::External("XPU API return wrong value[%d %s], ", r,
XPUAPIErrorMsg[r]));
}
}
void operator()(const platform::XPUDeviceContext& context,
const std::vector<const framework::SelectedRows*>& inputs,
framework::SelectedRows* output,
const bool sorted_result = false) {
if (inputs.size() == 0) {
VLOG(3) << "no input! return";
return;
}
const framework::SelectedRows* has_value_input = nullptr;
for (auto* in : inputs) {
if (in->rows().size() > 0) {
has_value_input = in;
break;
}
}
if (has_value_input == nullptr) {
VLOG(3) << "no input has value! just return" << std::endl;
return;
}
auto input_width = has_value_input->value().dims()[1];
auto input_height = has_value_input->height();
framework::SelectedRows& out = *output;
std::set<int64_t> merged_row_set;
size_t row_num = 0;
for (auto* input : inputs) {
if (input->rows().size() == 0) {
continue;
}
PADDLE_ENFORCE_EQ(input_width, input->value().dims()[1],
platform::errors::InvalidArgument(
"All inputs should have same "
"dimension except for the first one."));
PADDLE_ENFORCE_EQ(input_height, input->height(),
platform::errors::InvalidArgument(
"All inputs should have same height."));
row_num += input->rows().size();
merged_row_set.insert(input->rows().begin(), input->rows().end());
}
std::vector<int64_t> merge_rows(merged_row_set.begin(),
merged_row_set.end());
if (sorted_result) {
std::sort(merge_rows.begin(), merge_rows.end());
}
out.set_rows(merge_rows);
out.set_height(input_height);
out.mutable_value()->mutable_data<T>(
framework::make_ddim(
{static_cast<int64_t>(merged_row_set.size()), input_width}),
context.GetPlace());
int r =
xpu::constant<T>(context.x_context(), out.mutable_value()->data<T>(),
merge_rows.size() * input_width, static_cast<T>(0.f));
PADDLE_ENFORCE_EQ(r, xpu::Error_t::SUCCESS,
platform::errors::External("XPU constant op return"
" wrong value[%d %s].",
r, XPUAPIErrorMsg[r]));
float* out_data = reinterpret_cast<float*>(out.mutable_value()->data<T>());
std::unordered_map<int64_t, size_t> rows_to_id;
for (size_t i = 0; i < merge_rows.size(); ++i) {
rows_to_id[merge_rows[i]] = i;
}
for (auto* input : inputs) {
if (input->rows().size() == 0) {
continue;
}
auto& input_rows = input->rows();
int n = input_width;
for (size_t i = 0; i < input_rows.size(); i++) {
size_t out_i = rows_to_id[input_rows[i]];
auto r = xpu::add(
context.x_context(), input->value().data<T>() + i * input_width,
&out_data[out_i * input_width], &out_data[out_i * input_width], n);
PADDLE_ENFORCE_EQ(
r, XPU_SUCCESS,
platform::errors::External("XPU API return wrong value[%d %s], ", r,
XPUAPIErrorMsg[r]));
}
}
}
};
#endif
template <typename T>
struct MergeAverage<platform::CPUDeviceContext, T> {
framework::SelectedRows operator()(const platform::CPUDeviceContext& context,
......@@ -589,6 +738,10 @@ template struct MergeAdd<platform::CPUDeviceContext,
template struct MergeAdd<platform::CPUDeviceContext,
paddle::platform::bfloat16>;
#ifdef PADDLE_WITH_XPU
template struct MergeAdd<platform::XPUDeviceContext, float>;
#endif
template struct MergeAverage<platform::CPUDeviceContext, int>;
template struct MergeAverage<platform::CPUDeviceContext, int64_t>;
template struct MergeAverage<platform::CPUDeviceContext, float>;
......
paddle/fluid/operators/matrix_rank_op.cc
浏览文件 @ 1d755225
......@@ -219,18 +219,20 @@ class MatrixRankCPUKernel : public framework::OpKernel<T> {
tol_tensor.Resize(detail::NewAxisDim(tol_tensor.dims(), 1));
Tensor compare_result;
compare_result.mutable_data<int>(detail::NewAxisDim(dim_out, k),
context.GetPlace());
compare_result.mutable_data<int64_t>(detail::NewAxisDim(dim_out, k),
context.GetPlace());
int axis = -1;
if (eigenvalue_tensor.dims().size() >= tol_tensor.dims().size()) {
ElementwiseComputeEx<GreaterThanFunctor<T>, platform::CPUDeviceContext, T,
int>(context, &eigenvalue_tensor, &tol_tensor, axis,
GreaterThanFunctor<T>(), &compare_result);
ElementwiseComputeEx<GreaterThanFunctor<T, int64_t>,
platform::CPUDeviceContext, T, int>(
context, &eigenvalue_tensor, &tol_tensor, axis,
GreaterThanFunctor<T, int64_t>(), &compare_result);
} else {
ElementwiseComputeEx<LessThanFunctor<T>, platform::CPUDeviceContext, T,
int>(context, &eigenvalue_tensor, &tol_tensor, axis,
LessThanFunctor<T>(), &compare_result);
ElementwiseComputeEx<LessThanFunctor<T, int64_t>,
platform::CPUDeviceContext, T, int>(
context, &eigenvalue_tensor, &tol_tensor, axis,
LessThanFunctor<T, int64_t>(), &compare_result);
}
auto dito_int =
math::DeviceIndependenceTensorOperations<platform::CPUDeviceContext,
......
paddle/fluid/operators/matrix_rank_op.cu
浏览文件 @ 1d755225
......@@ -129,10 +129,10 @@ class MatrixRankGPUKernel : public framework::OpKernel<T> {
compare_result.mutable_data<int64_t>(detail::NewAxisDim(dim_out, k),
context.GetPlace());
int axis = -1;
ElementwiseComputeEx<GreaterThanFunctor<T>, platform::CUDADeviceContext, T,
int64_t>(context, &eigenvalue_tensor, &tol_tensor,
axis, GreaterThanFunctor<T>(),
&compare_result);
ElementwiseComputeEx<GreaterThanFunctor<T, int64_t>,
platform::CUDADeviceContext, T, int64_t>(
context, &eigenvalue_tensor, &tol_tensor, axis,
GreaterThanFunctor<T, int64_t>(), &compare_result);
auto dito_int =
math::DeviceIndependenceTensorOperations<platform::CUDADeviceContext,
int64_t>(context);
......
paddle/fluid/operators/matrix_rank_op.h
浏览文件 @ 1d755225
......@@ -16,6 +16,7 @@
#include <vector>
#include "paddle/fluid/framework/ddim.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/operators/controlflow/compare_op.h"
namespace paddle {
namespace operators {
......@@ -46,16 +47,6 @@ static DDim RemoveLastDim(const DDim& dim) {
}
} // namespace detail
template <typename T>
struct GreaterThanFunctor {
HOSTDEVICE int operator()(const T a, const T b) const { return a > b; }
};
template <typename T>
struct LessThanFunctor {
HOSTDEVICE int operator()(const T a, const T b) const { return a < b; }
};
template <typename T>
struct GreaterElementFunctor {
HOSTDEVICE T operator()(const T a, const T b) const {
......
paddle/fluid/operators/mkldnn/conv_mkldnn_op.cc
浏览文件 @ 1d755225
......@@ -14,6 +14,7 @@
#include <tuple>
#include "paddle/fluid/framework/expect.h"
#include "paddle/fluid/operators/conv_op.h"
#include "paddle/fluid/platform/cpu_info.h"
#include "paddle/fluid/platform/mkldnn_helper.h"
......@@ -79,7 +80,7 @@ class ConvMKLDNNHandlerT
dev_ctx, mkldnn_engine, cpu_place,
platform::CreateKey(dev_ctx, framework::vectorize(input->dims()),
unique_name)) {
if (!this->isCached()) {
if (unlikely(!this->isCached())) {
PADDLE_ENFORCE_EQ(
input->layout(), framework::DataLayout::kMKLDNN,
platform::errors::InvalidArgument(
......@@ -264,7 +265,7 @@ class ConvMKLDNNHandlerT
dev_ctx, dev_ctx.GetEngine(), cpu_place,
platform::CreateKey(dev_ctx, framework::vectorize(in->dims()),
unique_name)) {
if (!this->isBwdCached()) {
if (unlikely(!this->isBwdCached())) {
PADDLE_ENFORCE_EQ(
in->layout(), framework::DataLayout::kMKLDNN,
platform::errors::InvalidArgument(
......
paddle/fluid/operators/mkldnn/prelu_mkldnn_op.cc
浏览文件 @ 1d755225
......@@ -12,6 +12,7 @@ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/expect.h"
#include "paddle/fluid/platform/mkldnn_reuse.h"
namespace paddle {
......@@ -39,7 +40,7 @@ class PReluMKLDNNHandler
dev_ctx, engine, cpu_place,
platform::CreateKey(dev_ctx, framework::vectorize(x->dims()),
uniq_name)) {
if (!this->isCached()) {
if (unlikely(!this->isCached())) {
auto x_md = memory::desc(framework::vectorize(x->dims()),
MKLDNNGetDataType<T>(), x->format());
......
paddle/fluid/operators/optimizers/adam_op_xpu.cc
浏览文件 @ 1d755225
......@@ -14,6 +14,7 @@ limitations under the License. */
#include "paddle/fluid/operators/optimizers/adam_op.h"
#include "gflags/gflags.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
namespace paddle {
namespace operators {
......@@ -155,6 +156,11 @@ class AdamOpXPUKernel : public framework::OpKernel<T> {
mom2_out.template mutable_data<float>(ctx.GetPlace()),
param_out.template mutable_data<float>(ctx.GetPlace()),
beta1, beta2, epsilon, param.numel());
xpu_wait(dev_ctx.x_context()->xpu_stream);
PADDLE_ENFORCE_EQ(
r == xpu::Error_t::SUCCESS, true,
platform::errors::External("XPU API return wrong value[%d],", r));
if (!use_global_beta_pow) {
// update in cpu and then copy to xpu
if (beta1_pow.place() == platform::CPUPlace() &&
......@@ -165,7 +171,6 @@ class AdamOpXPUKernel : public framework::OpKernel<T> {
const float* beta2_pow_p = beta2_pow.template data<float>();
beta2_pow_out->mutable_data<float>(platform::CPUPlace())[0] =
beta2 * beta2_pow_p[0];
xpu_wait(dev_ctx.x_context()->xpu_stream);
} else {
float* beta1_pow_out_p =
beta1_pow_out->mutable_data<float>(ctx.GetPlace());
......@@ -177,23 +182,129 @@ class AdamOpXPUKernel : public framework::OpKernel<T> {
PADDLE_ENFORCE_EQ(
r, xpu::SUCCESS,
platform::errors::External(
"XPU kernel scale occur error in adamw error code ", r,
"XPU kernel scale occur error in adam error code ", r,
XPUAPIErrorMsg[r]));
r = xpu::scale(dev_ctx.x_context(), beta2_pow_ptr, beta2_pow_out_p,
beta2_pow.numel(), false, beta2, 0.0f);
PADDLE_ENFORCE_EQ(
r, xpu::SUCCESS,
platform::errors::External(
"XPU kernel scale occur error in adamw error code ", r,
"XPU kernel scale occur error in adam error code ", r,
XPUAPIErrorMsg[r]));
xpu_wait(dev_ctx.x_context()->xpu_stream);
}
}
} else if (grad_var->IsType<framework::SelectedRows>()) {
auto* grad = ctx.Input<framework::SelectedRows>("Grad");
auto& dev_ctx = ctx.template device_context<DeviceContext>();
if (grad->rows().size() == 0) {
VLOG(3) << "grad row size is 0!!";
return;
}
std::vector<int64_t> cpu_rows(grad->rows().begin(), grad->rows().end());
bool is_strict_sorted = true;
for (size_t i = 1; i < cpu_rows.size(); ++i) {
if (cpu_rows[i - 1] >= cpu_rows[i]) {
is_strict_sorted = false;
break;
}
}
framework::SelectedRows tmp_grad_merge;
const framework::SelectedRows* grad_merge_ptr;
if (is_strict_sorted) {
grad_merge_ptr = grad;
} else {
scatter::MergeAdd<platform::XPUDeviceContext, T> merge_func;
merge_func(ctx.template device_context<platform::XPUDeviceContext>(),
*grad, &tmp_grad_merge, true);
xpu_wait(dev_ctx.x_context()->xpu_stream);
grad_merge_ptr = &tmp_grad_merge;
}
const T* beta1_pow_ptr = beta1_pow.template data<T>();
const T* beta2_pow_ptr = beta2_pow.template data<T>();
Tensor xpu_beta1_pow;
Tensor xpu_beta2_pow;
if (beta1_pow.place() == platform::CPUPlace() &&
beta2_pow.place() == platform::CPUPlace()) {
paddle::framework::TensorCopy(beta1_pow, ctx.GetPlace(), dev_ctx,
&xpu_beta1_pow);
paddle::framework::TensorCopy(beta2_pow, ctx.GetPlace(), dev_ctx,
&xpu_beta2_pow);
dev_ctx.Wait();
beta1_pow_ptr = xpu_beta1_pow.template data<T>();
beta2_pow_ptr = xpu_beta2_pow.template data<T>();
}
auto& grad_merge = *grad_merge_ptr;
auto& grad_tensor = grad_merge.value();
const T* grad_data = grad_tensor.template data<T>();
int row_count = grad_merge.rows().size();
std::vector<int> rows(row_count);
xpu::ctx_guard RAII_GUARD(dev_ctx.x_context());
int* xpu_rows = RAII_GUARD.alloc_l3_or_gm<int>(row_count);
std::vector<int64_t> merge_rows(grad_merge.rows().begin(),
grad_merge.rows().end());
for (size_t i = 0; i < grad_merge.rows().size(); ++i) {
rows[i] = static_cast<int>(merge_rows[i]);
}
xpu_wait(dev_ctx.x_context()->xpu_stream);
memory::Copy(ctx.GetPlace(), xpu_rows, platform::CPUPlace(), rows.data(),
row_count * sizeof(int));
auto row_numel = grad_tensor.numel() / grad_merge.rows().size();
auto ori_rows = param.numel() / row_numel;
PADDLE_ENFORCE_EQ(r == xpu::Error_t::SUCCESS, true,
platform::errors::External(
"XPU API return wrong value[%d], please check "
"where Baidu Kunlun Card is properly installed.",
r));
int lazy_mode = static_cast<int>(ctx.Attr<bool>("lazy_mode"));
int r = xpu::sparse_adam(
dev_ctx.x_context(), grad_data, mom1.template data<T>(),
mom2.template data<T>(), param.template data<T>(), beta1_pow_ptr,
beta2_pow_ptr, lr.template data<T>(),
mom1_out.template mutable_data<T>(ctx.GetPlace()),
mom2_out.template mutable_data<T>(ctx.GetPlace()),
param_out.template mutable_data<T>(ctx.GetPlace()), beta1, beta2,
epsilon, ori_rows, xpu_rows, row_numel, grad_merge.rows().size(),
lazy_mode);
PADDLE_ENFORCE_EQ(
r == xpu::Error_t::SUCCESS, true,
platform::errors::External("XPU API return wrong value[%d],", r));
if (!use_global_beta_pow) {
// update in cpu and then copy to xpu
if (beta1_pow.place() == platform::CPUPlace() &&
beta2_pow.place() == platform::CPUPlace()) {
const float* beta1_pow_p = beta1_pow.template data<float>();
beta1_pow_out->mutable_data<float>(platform::CPUPlace())[0] =
beta1 * beta1_pow_p[0];
const float* beta2_pow_p = beta2_pow.template data<float>();
beta2_pow_out->mutable_data<float>(platform::CPUPlace())[0] =
beta2 * beta2_pow_p[0];
} else {
float* beta1_pow_out_p =
beta1_pow_out->mutable_data<float>(ctx.GetPlace());
float* beta2_pow_out_p =
beta2_pow_out->mutable_data<float>(ctx.GetPlace());
int r =
xpu::scale(dev_ctx.x_context(), beta1_pow_ptr, beta1_pow_out_p,
beta1_pow.numel(), false, beta1, 0.0f);
PADDLE_ENFORCE_EQ(
r, xpu::SUCCESS,
platform::errors::External(
"XPU kernel scale occur error in adam error code ", r,
XPUAPIErrorMsg[r]));
r = xpu::scale(dev_ctx.x_context(), beta2_pow_ptr, beta2_pow_out_p,
beta2_pow.numel(), false, beta2, 0.0f);
PADDLE_ENFORCE_EQ(
r, xpu::SUCCESS,
platform::errors::External(
"XPU kernel scale occur error in adam error code ", r,
XPUAPIErrorMsg[r]));
}
}
xpu_wait(dev_ctx.x_context()->xpu_stream);
} else {
PADDLE_ENFORCE_EQ(1, 2, platform::errors::InvalidArgument(
"Variable type not supported by adam_op"));
......
paddle/fluid/operators/optimizers/lamb_op.h
浏览文件 @ 1d755225
......@@ -22,8 +22,8 @@ limitations under the License. */
#include "paddle/fluid/operators/math/algorithm.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
#include "paddle/fluid/operators/math/squared_l2_norm.h"
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/fluid/platform/for_range.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/save_combine_op.h
浏览文件 @ 1d755225
......@@ -27,7 +27,7 @@ limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/string_array.h"
#include "paddle/fluid/platform/device_context.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace operators {
......
paddle/fluid/operators/viterbi_decode_op.cu
浏览文件 @ 1d755225
......@@ -72,7 +72,8 @@ struct BinaryOperation<platform::CUDADeviceContext, BinaryFunctor, T> {
}
};
template <template <typename T> typename CompareFunctor, typename T>
template <template <typename InT, typename OutT> typename CompareFunctor,
typename T>
struct GetMask<platform::CUDADeviceContext, CompareFunctor, T> {
void operator()(const framework::ExecutionContext& ctx, const Tensor& lhs,
const Tensor& rhs, Tensor* mask) {
......@@ -81,7 +82,7 @@ struct GetMask<platform::CUDADeviceContext, CompareFunctor, T> {
auto& dev_ctx = ctx.template device_context<platform::CUDADeviceContext>();
paddle::operators::LaunchSameDimsElementwiseCudaKernel<
ElementwiseType::kBinary, int64_t, T>(dev_ctx, ins, &outs,
CompareFunctor<int64_t>());
CompareFunctor<int64_t, T>());
}
};
......
paddle/fluid/operators/viterbi_decode_op.h
浏览文件 @ 1d755225
......@@ -112,12 +112,13 @@ void SameDimsBinaryOP(const Tensor& lhs, const Tensor& rhs, Tensor* out) {
}
}
template <typename DeviceContext, template <typename T> typename CompareFunctor,
template <typename DeviceContext,
template <typename InT, typename OutT> typename CompareFunctor,
typename T>
struct GetMask {
void operator()(const framework::ExecutionContext& ctx, const Tensor& lhs,
const Tensor& rhs, Tensor* mask) {
SameDimsBinaryOP<int64_t, CompareFunctor<int64_t>, T>(lhs, rhs, mask);
SameDimsBinaryOP<int64_t, CompareFunctor<int64_t, T>, T>(lhs, rhs, mask);
}
};
......
paddle/fluid/platform/bfloat16_test.cc
浏览文件 @ 1d755225
......@@ -10,7 +10,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/bfloat16.h"
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
#define GLOG_NO_ABBREVIATED_SEVERITIES // msvc conflict logging with windows.h
#include "gtest/gtest.h"
......
paddle/fluid/platform/complex_test.cc
浏览文件 @ 1d755225
......@@ -14,7 +14,7 @@
#include "paddle/fluid/platform/complex.h"
#include <complex>
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
#define GLOG_NO_ABBREVIATED_SEVERITIES // msvc conflict logging with windows.h
#include "gtest/gtest.h"
......@@ -267,56 +267,56 @@ TEST(complex, print) {
TEST(complex, isinf) {
// *********** complex<float> *************
complex<float> a;
a.real = float(INFINITY);
a.real = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(a), true);
a.imag = float(INFINITY);
a.imag = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(a), true);
complex<float> b = float(INFINITY);
complex<float> b = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(b), true);
complex<float> c(float(INFINITY), 0);
complex<float> c(static_cast<float>(INFINITY), 0);
EXPECT_EQ(std::isinf(c), true);
// *********** complex<double> *************
complex<double> a1;
a1.real = double(INFINITY);
a1.real = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(a1), true);
a1.imag = double(INFINITY);
a1.imag = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(a1), true);
complex<double> b1 = double(INFINITY);
complex<double> b1 = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(b1), true);
complex<double> c1(double(INFINITY), 0);
complex<double> c1(static_cast<double>(INFINITY), 0);
EXPECT_EQ(std::isinf(c1), true);
}
TEST(complex, isnan) {
// *********** complex<float> *************
complex<float> a;
a.real = float(NAN);
a.real = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(a), true);
a.imag = float(NAN);
a.imag = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(a), true);
complex<float> b = float(NAN);
complex<float> b = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(b), true);
complex<float> c(float(NAN), 0);
complex<float> c(static_cast<float>(NAN), 0);
EXPECT_EQ(std::isnan(c), true);
// *********** complex<double> *************
complex<double> a1;
a1.real = double(NAN);
a1.real = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(a1), true);
a1.imag = double(NAN);
a1.imag = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(a1), true);
complex<double> b1 = double(NAN);
complex<double> b1 = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(b1), true);
complex<double> c1(double(NAN), 0);
complex<double> c1(static_cast<double>(NAN), 0);
EXPECT_EQ(std::isnan(c1), true);
}
......
paddle/fluid/platform/complex_test.cu
浏览文件 @ 1d755225
......@@ -23,8 +23,8 @@
#include "paddle/fluid/framework/lod_tensor.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/platform/eigen_ext.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/pten/kernels/funcs/eigen/extensions.h"
#if defined(PADDLE_WITH_CUDA) || defined(PADDLE_WITH_HIP)
namespace paddle {
......@@ -303,59 +303,59 @@ TEST(complex, print) {
TEST(complex, isinf) {
// *********** complex<float> *************
complex<float> a;
a.real = float(INFINITY);
a.real = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(a), true);
a.imag = float(INFINITY);
a.imag = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(a), true);
complex<float> b = float(INFINITY);
complex<float> b = static_cast<float>(INFINITY);
EXPECT_EQ(std::isinf(b), true);
complex<float> c(float(INFINITY), 0);
complex<float> c(static_cast<float>(INFINITY), 0);
EXPECT_EQ(std::isinf(c), true);
// *********** complex<double> *************
complex<double> a1;
a1.real = double(INFINITY);
a1.real = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(a1), true);
a1.imag = double(INFINITY);
a1.imag = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(a1), true);
complex<double> b1 = double(INFINITY);
complex<double> b1 = static_cast<double>(INFINITY);
EXPECT_EQ(std::isinf(b1), true);
complex<double> c1(double(INFINITY), 0);
complex<double> c1(static_cast<double>(INFINITY), 0);
EXPECT_EQ(std::isinf(c1), true);
}
TEST(complex, isnan) {
// *********** complex<float> *************
complex<float> a;
a.real = float(NAN);
a.real = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(a), true);
a.imag = float(NAN);
a.imag = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(a), true);
complex<float> b = float(NAN);
complex<float> b = static_cast<float>(NAN);
EXPECT_EQ(std::isnan(b), true);
complex<float> c(float(NAN), 0);
complex<float> c(static_cast<float>(NAN), 0);
EXPECT_EQ(std::isnan(c), true);
// *********** complex<double> *************
complex<double> a1;
a1.real = double(NAN);
a1.real = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(a1), true);
a1.imag = double(NAN);
a1.imag = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(a1), true);
complex<double> b1 = double(NAN);
complex<double> b1 = static_cast<double>(NAN);
EXPECT_EQ(std::isnan(b1), true);
complex<double> c1(double(NAN), 0);
complex<double> c1(static_cast<double>(NAN), 0);
EXPECT_EQ(std::isnan(c1), true);
}
} // namespace platform
} // namespace paddle
#endif
\ No newline at end of file
#endif
paddle/fluid/platform/device/npu/dynload/hccl.h
浏览文件 @ 1d755225
......@@ -20,7 +20,7 @@ limitations under the License. */
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
#define HCOM_GROUP_PREFIX "HCOM_GROUP_"
......
paddle/fluid/platform/device_context.cc
浏览文件 @ 1d755225
......@@ -25,6 +25,7 @@ limitations under the License. */
#include "paddle/fluid/platform/ipu/ipu_backend.h"
#endif
#include "glog/logging.h"
#include "paddle/fluid/framework/expect.h"
#include "paddle/fluid/platform/profiler.h"
namespace paddle {
......@@ -841,15 +842,6 @@ unsigned int MKLDNNDeviceContext::GetCachedObjectsNumber(void) const {
return num_entries;
}
// TODO(jczaja): Replace with C++20 equivalents when applicable
#ifdef _WIN32
#define likely(expr) (expr)
#define unlikely(expr) (expr)
#else
#define likely(expr) (__builtin_expect(!!(expr), 1))
#define unlikely(expr) (__builtin_expect(!!(expr), 0))
#endif
MKLDNNDeviceContext::BlobPtr_t<void> MKLDNNDeviceContext::GetBlob(
const std::string& name) const {
BlobMap* pMap = p_blobmap_.get();
......
paddle/fluid/platform/dynload/CMakeLists.txt
浏览文件 @ 1d755225
cc_library(dynamic_loader SRCS dynamic_loader.cc DEPS glog gflags enforce)
cc_library(dynamic_loader SRCS dynamic_loader.cc DEPS glog gflags enforce pten_dynamic_loader)
list(APPEND CUDA_SRCS cublas.cc cublasLt.cc cudnn.cc curand.cc cusolver.cc cusparse.cc nvtx.cc cufft.cc)
......@@ -34,24 +34,24 @@ if (CUPTI_FOUND)
list(APPEND CUDA_SRCS cupti.cc)
endif(CUPTI_FOUND)
if(WITH_ROCM)
hip_library(dynload_cuda SRCS ${HIP_SRCS} DEPS dynamic_loader)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc)
hip_library(dynload_cuda SRCS ${HIP_SRCS} DEPS dynamic_loader pten_dynload_cuda)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc pten_dynload_warpctc)
elseif (WITH_ASCEND_CL)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc npu_hccl)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc npu_hccl pten_dynload_warpctc)
else()
nv_library(dynload_cuda SRCS ${CUDA_SRCS} DEPS dynamic_loader)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc)
nv_library(dynload_cuda SRCS ${CUDA_SRCS} DEPS dynamic_loader pten_dynload_cuda)
cc_library(dynload_warpctc SRCS warpctc.cc DEPS dynamic_loader warpctc pten_dynload_warpctc)
endif()
if (WITH_MKLML)
cc_library(dynload_mklml SRCS mklml.cc DEPS dynamic_loader mklml)
cc_library(dynload_mklml SRCS mklml.cc DEPS dynamic_loader mklml pten_dynload_mklml)
endif()
cc_library(dynload_lapack SRCS lapack.cc DEPS dynamic_loader)
cc_library(dynload_lapack SRCS lapack.cc DEPS dynamic_loader pten_dynload_lapack)
add_dependencies(dynload_lapack extern_lapack)
# TODO(TJ): add iomp, mkldnn?
if (MKL_FOUND AND WITH_ONEMKL)
message("ONEMKL INCLUDE directory is ${MKL_INCLUDE}")
cc_library(dynload_mklrt SRCS mklrt.cc DEPS dynamic_loader)
cc_library(dynload_mklrt SRCS mklrt.cc DEPS dynamic_loader pten_dynload_mklrt)
target_include_directories(dynload_mklrt PRIVATE ${MKL_INCLUDE})
endif()
paddle/fluid/platform/dynload/cublas.cc
浏览文件 @ 1d755225
......@@ -17,8 +17,6 @@ limitations under the License. */
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cublas_dso_flag;
void *cublas_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
......
paddle/fluid/platform/dynload/cublas.h
浏览文件 @ 1d755225
......@@ -20,16 +20,12 @@ limitations under the License. */
#include <mutex> // NOLINT
#include <type_traits>
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cublas.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cublas_dso_flag;
extern void *cublas_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load cublas routine
......@@ -37,19 +33,8 @@ extern void *cublas_dso_handle;
*
* note: default dynamic linked libs
*/
#define DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
inline auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using cublas_func = \
decltype(::__name(std::declval<Args>()...)) (*)(Args...); \
std::call_once(cublas_dso_flag, []() { \
cublas_dso_handle = paddle::platform::dynload::GetCublasDsoHandle(); \
}); \
static void *p_##__name = dlsym(cublas_dso_handle, #__name); \
return reinterpret_cast<cublas_func>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define CUBLAS_BLAS_ROUTINE_EACH(__macro) \
......@@ -99,7 +84,7 @@ extern void *cublas_dso_handle;
__macro(cublasSgetrsBatched); \
__macro(cublasDgetrsBatched);
CUBLAS_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
CUBLAS_BLAS_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
// APIs available after CUDA 8.0
#if CUDA_VERSION >= 8000
......@@ -111,7 +96,7 @@ CUBLAS_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
__macro(cublasZgemmStridedBatched); \
__macro(cublasHgemmStridedBatched);
CUBLAS_BLAS_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
CUBLAS_BLAS_ROUTINE_EACH_R2(PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
#endif
// APIs available after CUDA 9.0
......@@ -120,7 +105,7 @@ CUBLAS_BLAS_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
__macro(cublasSetMathMode); \
__macro(cublasGetMathMode);
CUBLAS_BLAS_ROUTINE_EACH_R3(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
CUBLAS_BLAS_ROUTINE_EACH_R3(PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
#endif
// APIs available after CUDA 9.1
......@@ -129,10 +114,10 @@ CUBLAS_BLAS_ROUTINE_EACH_R3(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
__macro(cublasGemmBatchedEx); \
__macro(cublasGemmStridedBatchedEx);
CUBLAS_BLAS_ROUTINE_EACH_R4(DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
CUBLAS_BLAS_ROUTINE_EACH_R4(PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP)
#endif
#undef DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLAS_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/cublasLt.cc
浏览文件 @ 1d755225
......@@ -17,8 +17,6 @@ limitations under the License. */
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cublasLt_dso_flag;
void *cublasLt_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
......
paddle/fluid/platform/dynload/cublasLt.h
浏览文件 @ 1d755225
......@@ -19,16 +19,12 @@ limitations under the License. */
#include <mutex> // NOLINT
#include <type_traits>
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cublasLt.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cublasLt_dso_flag;
extern void *cublasLt_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load cublasLt routine
......@@ -36,20 +32,8 @@ extern void *cublasLt_dso_handle;
*
* note: default dynamic linked libs
*/
#define DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
inline auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using cublasLt_func = \
decltype(::__name(std::declval<Args>()...)) (*)(Args...); \
std::call_once(cublasLt_dso_flag, []() { \
cublasLt_dso_handle = \
paddle::platform::dynload::GetCublasLtDsoHandle(); \
}); \
static void *p_##__name = dlsym(cublasLt_dso_handle, #__name); \
return reinterpret_cast<cublasLt_func>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
// APIs available after CUDA 10.1
......@@ -69,10 +53,10 @@ extern void *cublasLt_dso_handle;
__macro(cublasLtMatrixTransformDescDestroy); \
__macro(cublasLtMatrixTransformDescSetAttribute);
CUBLASLT_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP)
CUBLASLT_BLAS_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP)
// #endif
#undef DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_CUBLASLT_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/cuda_driver.cc
浏览文件 @ 1d755225
......@@ -13,14 +13,12 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/cuda_driver.h"
#include "paddle/pten/backends/dynload/cuda_driver.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cuda_dso_flag;
void* cuda_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
#if CUDA_VERSION >= 10020
......@@ -28,10 +26,7 @@ CUDA_ROUTINE_EACH_VVM(DEFINE_WRAP);
#endif
CUDA_ROUTINE_EACH(DEFINE_WRAP);
bool HasCUDADriver() {
std::call_once(cuda_dso_flag, []() { cuda_dso_handle = GetCUDADsoHandle(); });
return cuda_dso_handle != nullptr;
}
bool HasCUDADriver() { return pten::dynload::HasCUDADriver(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cuda_driver.h
浏览文件 @ 1d755225
......@@ -17,30 +17,17 @@ limitations under the License. */
#include <cuda.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cuda_driver.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cuda_dso_flag;
extern void* cuda_dso_handle;
extern bool HasCUDADriver();
#define DECLARE_DYNAMIC_LOAD_CUDA_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using cuda_func = decltype(&::__name); \
std::call_once(cuda_dso_flag, []() { \
cuda_dso_handle = paddle::platform::dynload::GetCUDADsoHandle(); \
}); \
static void* p_##__name = dlsym(cuda_dso_handle, #__name); \
return reinterpret_cast<cuda_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUDA_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed cuda driver functions
......@@ -72,12 +59,12 @@ extern bool HasCUDADriver();
__macro(cuMemRelease); \
__macro(cuMemAddressFree)
CUDA_ROUTINE_EACH_VVM(DECLARE_DYNAMIC_LOAD_CUDA_WRAP);
CUDA_ROUTINE_EACH_VVM(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDA_WRAP);
#endif
CUDA_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUDA_WRAP);
CUDA_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDA_WRAP);
#undef DECLARE_DYNAMIC_LOAD_CUDA_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_CUDA_WRAP
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cudnn.cc
浏览文件 @ 1d755225
......@@ -13,13 +13,11 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/cudnn.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/pten/backends/dynload/cudnn.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cudnn_dso_flag;
void* cudnn_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
......@@ -45,19 +43,7 @@ CUDNN_DNN_ROUTINE_EACH_AFTER_R7(DEFINE_WRAP);
CUDNN_DNN_ROUTINE_EACH_R8(DEFINE_WRAP);
#endif
bool HasCUDNN() {
std::call_once(cudnn_dso_flag,
[]() { cudnn_dso_handle = GetCUDNNDsoHandle(); });
return cudnn_dso_handle != nullptr;
}
void EnforceCUDNNLoaded(const char* fn_name) {
PADDLE_ENFORCE_NOT_NULL(
cudnn_dso_handle,
platform::errors::PreconditionNotMet(
"Cannot load cudnn shared library. Cannot invoke method %s.",
fn_name));
}
bool HasCUDNN() { return pten::dynload::HasCUDNN(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cudnn.h
浏览文件 @ 1d755225
......@@ -18,32 +18,17 @@ limitations under the License. */
#include <glog/logging.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cudnn.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cudnn_dso_flag;
extern void* cudnn_dso_handle;
extern bool HasCUDNN();
extern void EnforceCUDNNLoaded(const char* fn_name);
#define DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using cudnn_func = decltype(&::__name); \
std::call_once(cudnn_dso_flag, []() { \
cudnn_dso_handle = paddle::platform::dynload::GetCUDNNDsoHandle(); \
}); \
EnforceCUDNNLoaded(#__name); \
static void* p_##__name = dlsym(cudnn_dso_handle, #__name); \
return reinterpret_cast<cudnn_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed cudnn functions in HPPL
......@@ -127,7 +112,7 @@ extern void EnforceCUDNNLoaded(const char* fn_name);
__macro(cudnnGetActivationDescriptor); \
__macro(cudnnDestroyActivationDescriptor); \
__macro(cudnnSetRNNDescriptor_v6);
CUDNN_DNN_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#if CUDNN_VERSION >= 7000 && CUDNN_VERSION < 8000
#define CUDNN_DNN_ROUTINE_EACH_AFTER_R7_LESS_R8(__macro) \
......@@ -135,7 +120,8 @@ CUDNN_DNN_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
__macro(cudnnGetConvolutionForwardAlgorithm); \
__macro(cudnnGetConvolutionBackwardDataAlgorithm); \
__macro(cudnnSetRNNDescriptor);
CUDNN_DNN_ROUTINE_EACH_AFTER_R7_LESS_R8(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH_AFTER_R7_LESS_R8(
PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#endif
#if CUDNN_VERSION >= 7001
......@@ -153,7 +139,7 @@ CUDNN_DNN_ROUTINE_EACH_AFTER_R7_LESS_R8(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
__macro(cudnnGetConvolutionBackwardFilterAlgorithm_v7); \
__macro(cudnnGetConvolutionForwardAlgorithm_v7); \
__macro(cudnnGetConvolutionBackwardFilterAlgorithmMaxCount);
CUDNN_DNN_ROUTINE_EACH_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH_R7(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#endif
#if CUDNN_VERSION >= 7201
......@@ -166,7 +152,7 @@ CUDNN_DNN_ROUTINE_EACH_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
__macro(cudnnRNNBackwardDataEx); \
__macro(cudnnRNNBackwardWeightsEx); \
__macro(cudnnRNNForwardInferenceEx);
CUDNN_DNN_ROUTINE_EACH_AFTER_TWO_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH_AFTER_TWO_R7(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#endif
#if CUDNN_VERSION >= 7401
......@@ -176,7 +162,7 @@ CUDNN_DNN_ROUTINE_EACH_AFTER_TWO_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
__macro(cudnnGetBatchNormalizationBackwardExWorkspaceSize); \
__macro(cudnnBatchNormalizationBackwardEx); \
__macro(cudnnGetBatchNormalizationTrainingExReserveSpaceSize);
CUDNN_DNN_ROUTINE_EACH_AFTER_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH_AFTER_R7(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#endif
#if CUDNN_VERSION >= 8000
......@@ -192,7 +178,7 @@ CUDNN_DNN_ROUTINE_EACH_AFTER_R7(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
__macro(cudnnSetFusedOpsConstParamPackAttribute); \
__macro(cudnnSetFusedOpsVariantParamPackAttribute); \
__macro(cudnnMakeFusedOpsPlan);
CUDNN_DNN_ROUTINE_EACH_R8(DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
CUDNN_DNN_ROUTINE_EACH_R8(PLATFORM_DECLARE_DYNAMIC_LOAD_CUDNN_WRAP)
#endif
} // namespace dynload
......
paddle/fluid/platform/dynload/cufft.cc
浏览文件 @ 1d755225
......@@ -13,31 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/cufft.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/pten/backends/dynload/cufft.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cufft_dso_flag;
void* cufft_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
CUFFT_FFT_ROUTINE_EACH(DEFINE_WRAP);
bool HasCUFFT() {
std::call_once(cufft_dso_flag,
[]() { cufft_dso_handle = GetCUFFTDsoHandle(); });
return cufft_dso_handle != nullptr;
}
void EnforceCUFFTLoaded(const char* fn_name) {
PADDLE_ENFORCE_NOT_NULL(
cufft_dso_handle,
platform::errors::PreconditionNotMet(
"Cannot load cufft shared library. Cannot invoke method %s.",
fn_name));
}
bool HasCUFFT() { return pten::dynload::HasCUFFT(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cufft.h
浏览文件 @ 1d755225
......@@ -19,32 +19,17 @@ limitations under the License. */
#include <glog/logging.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cufft.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cufft_dso_flag;
extern void* cufft_dso_handle;
extern bool HasCUFFT();
extern void EnforceCUFFTLoaded(const char* fn_name);
#define DECLARE_DYNAMIC_LOAD_CUFFT_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using cufft_func = decltype(&::__name); \
std::call_once(cufft_dso_flag, []() { \
cufft_dso_handle = paddle::platform::dynload::GetCUFFTDsoHandle(); \
}); \
EnforceCUFFTLoaded(#__name); \
static void* p_##__name = dlsym(cufft_dso_handle, #__name); \
return reinterpret_cast<cufft_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUFFT_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed cufft functions in HPPL
......@@ -104,7 +89,7 @@ extern void EnforceCUFFTLoaded(const char* fn_name);
__macro(cufftXtExecDescriptor); \
__macro(cufftXtSetWorkAreaPolicy);
CUFFT_FFT_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUFFT_WRAP)
CUFFT_FFT_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUFFT_WRAP)
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cupti.cc
浏览文件 @ 1d755225
......@@ -20,9 +20,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cupti_dso_flag;
void *cupti_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
CUPTI_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/cupti.h
浏览文件 @ 1d755225
......@@ -19,16 +19,12 @@ limitations under the License. */
#include <cupti.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cupti.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cupti_dso_flag;
extern void *cupti_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load cupti routine
......@@ -36,18 +32,8 @@ extern void *cupti_dso_handle;
*
* note: default dynamic linked libs
*/
#define DECLARE_DYNAMIC_LOAD_CUPTI_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
inline CUptiResult CUPTIAPI operator()(Args... args) { \
using cuptiFunc = decltype(&::__name); \
std::call_once(cupti_dso_flag, []() { \
cupti_dso_handle = paddle::platform::dynload::GetCUPTIDsoHandle(); \
}); \
static void *p_##__name = dlsym(cupti_dso_handle, #__name); \
return reinterpret_cast<cuptiFunc>(p_##__name)(args...); \
} \
}; \
#define DECLARE_DYNAMIC_LOAD_CUPTI_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define CUPTI_ROUTINE_EACH(__macro) \
......
paddle/fluid/platform/dynload/curand.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag curand_dso_flag;
void *curand_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
CURAND_RAND_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/curand.h
浏览文件 @ 1d755225
......@@ -16,27 +16,14 @@ limitations under the License. */
#include <curand.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/curand.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag curand_dso_flag;
extern void *curand_dso_handle;
#define DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
curandStatus_t operator()(Args... args) { \
using curandFunc = decltype(&::__name); \
std::call_once(curand_dso_flag, []() { \
curand_dso_handle = paddle::platform::dynload::GetCurandDsoHandle(); \
}); \
static void *p_##__name = dlsym(curand_dso_handle, #__name); \
return reinterpret_cast<curandFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define CURAND_RAND_ROUTINE_EACH(__macro) \
......@@ -48,7 +35,7 @@ extern void *curand_dso_handle;
__macro(curandGenerateNormal); \
__macro(curandDestroyGenerator);
CURAND_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CURAND_WRAP);
CURAND_RAND_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CURAND_WRAP);
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/cusolver.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cusolver_dso_flag;
void *cusolver_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
CUSOLVER_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/cusolver.h
浏览文件 @ 1d755225
......@@ -17,28 +17,14 @@ limitations under the License. */
#include <cusolverDn.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cusolver.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cusolver_dso_flag;
extern void *cusolver_dso_handle;
#define DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
cusolverStatus_t operator()(Args... args) { \
using cusolverFunc = decltype(&::__name); \
std::call_once(cusolver_dso_flag, []() { \
cusolver_dso_handle = \
paddle::platform::dynload::GetCusolverDsoHandle(); \
}); \
static void *p_##__name = dlsym(cusolver_dso_handle, #__name); \
return reinterpret_cast<cusolverFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define CUSOLVER_ROUTINE_EACH(__macro) \
......@@ -62,7 +48,7 @@ extern void *cusolver_dso_handle;
__macro(cusolverDnCheevd); \
__macro(cusolverDnZheevd);
CUSOLVER_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP);
CUSOLVER_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP);
#if CUDA_VERSION >= 9020
#define CUSOLVER_ROUTINE_EACH_R1(__macro) \
......@@ -105,7 +91,7 @@ CUSOLVER_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP);
__macro(cusolverDnCungqr); \
__macro(cusolverDnZungqr);
CUSOLVER_ROUTINE_EACH_R1(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP)
CUSOLVER_ROUTINE_EACH_R1(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP)
#endif
#if CUDA_VERSION >= 9020
......@@ -117,10 +103,10 @@ CUSOLVER_ROUTINE_EACH_R1(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP)
__macro(cusolverDnDsyevj); \
__macro(cusolverDnDestroySyevjInfo);
CUSOLVER_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP)
CUSOLVER_ROUTINE_EACH_R2(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP)
#endif
#undef DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_CUSOLVER_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/cusparse.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag cusparse_dso_flag;
void *cusparse_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
#ifdef CUSPARSE_ROUTINE_EACH
......
paddle/fluid/platform/dynload/cusparse.h
浏览文件 @ 1d755225
......@@ -17,28 +17,14 @@ limitations under the License. */
#include <cusparse.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/cusparse.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag cusparse_dso_flag;
extern void *cusparse_dso_handle;
#define DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
cusparseStatus_t operator()(Args... args) { \
using cusparseFunc = decltype(&::__name); \
std::call_once(cusparse_dso_flag, []() { \
cusparse_dso_handle = \
paddle::platform::dynload::GetCusparseDsoHandle(); \
}); \
static void *p_##__name = dlsym(cusparse_dso_handle, #__name); \
return reinterpret_cast<cusparseFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#if defined(PADDLE_WITH_CUDA)
......@@ -54,7 +40,7 @@ extern void *cusparse_dso_handle;
__macro(cusparseSetMatType); \
__macro(cusparseSetMatIndexBase);
CUSPARSE_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP);
CUSPARSE_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP);
// APIs available after CUDA 11.2
#if CUDA_VERSION >= 11020
......@@ -74,7 +60,7 @@ CUSPARSE_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP);
__macro(cusparseSparseToDense_bufferSize); \
__macro(cusparseSparseToDense);
CUSPARSE_ROUTINE_EACH_11020(DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP)
CUSPARSE_ROUTINE_EACH_11020(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP)
// APIs available after CUDA 11.3
#if CUDA_VERSION >= 11030
......@@ -83,13 +69,13 @@ CUSPARSE_ROUTINE_EACH_11020(DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP)
__macro(cusparseSDDMM_preprocess); \
__macro(cusparseSDDMM);
CUSPARSE_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP)
CUSPARSE_ROUTINE_EACH_R2(PLATFORM_DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP)
#endif
#endif
#endif
#endif
#undef DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_CUSPARSE_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/hipfft.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag hipfft_dso_flag;
void *hipfft_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
HIPFFT_FFT_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/hipfft.h
浏览文件 @ 1d755225
......@@ -17,8 +17,7 @@ limitations under the License. */
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/hipfft.h"
namespace paddle {
namespace platform {
......@@ -26,18 +25,8 @@ namespace dynload {
extern std::once_flag hipfft_dso_flag;
extern void *hipfft_dso_handle;
#define DECLARE_DYNAMIC_LOAD_HIPFFT_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using hipfftFunc = decltype(&::__name); \
std::call_once(hipfft_dso_flag, []() { \
hipfft_dso_handle = paddle::platform::dynload::GetROCFFTDsoHandle(); \
}); \
static void *p_##__name = dlsym(hipfft_dso_handle, #__name); \
return reinterpret_cast<hipfftFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_HIPFFT_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define HIPFFT_FFT_ROUTINE_EACH(__macro) \
......@@ -70,53 +59,8 @@ extern void *hipfft_dso_handle;
__macro(hipfftGetVersion); \
__macro(hipfftGetProperty);
HIPFFT_FFT_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_HIPFFT_WRAP);
HIPFFT_FFT_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_HIPFFT_WRAP);
inline const char *hipfftGetErrorString(hipfftResult_t status) {
switch (status) {
case HIPFFT_SUCCESS:
return "'HIPFFT_SUCCESS'. The hipFFT operation was successful.";
case HIPFFT_INVALID_PLAN:
return "'HIPFFT_INVALID_PLAN'. hipFFT was passed an invalid plan handle.";
case HIPFFT_ALLOC_FAILED:
return "'HIPFFT_ALLOC_FAILED'. hipFFT failed to allocate GPU or CPU "
"memory.";
case HIPFFT_INVALID_TYPE:
return "'HIPFFT_INVALID_TYPE'. No longer used.";
case HIPFFT_INVALID_VALUE:
return "'HIPFFT_INVALID_VALUE'. User specified an invalid pointer or "
"parameter.";
case HIPFFT_INTERNAL_ERROR:
return "'HIPFFT_INTERNAL_ERROR'. Driver or internal hipFFT library "
"error.";
case HIPFFT_EXEC_FAILED:
return "'HIPFFT_EXEC_FAILED'. Failed to execute an FFT on the GPU.";
case HIPFFT_SETUP_FAILED:
return "'HIPFFT_SETUP_FAILED'. The hipFFT library failed to initialize.";
case HIPFFT_INVALID_SIZE:
return "'HIPFFT_INVALID_SIZE'. User specified an invalid transform size.";
case HIPFFT_UNALIGNED_DATA:
return "'HIPFFT_UNALIGNED_DATA'. No longer used.";
case HIPFFT_INCOMPLETE_PARAMETER_LIST:
return "'HIPFFT_INCOMPLETE_PARAMETER_LIST'. Missing parameters in call.";
case HIPFFT_INVALID_DEVICE:
return "'HIPFFT_INVALID_DEVICE'. Execution of a plan was on different "
"GPU than plan creation.";
case HIPFFT_PARSE_ERROR:
return "'HIPFFT_PARSE_ERROR'. Internal plan database error.";
case HIPFFT_NO_WORKSPACE:
return "'HIPFFT_NO_WORKSPACE'. No workspace has been provided prior to "
"plan execution.";
case HIPFFT_NOT_IMPLEMENTED:
return "'HIPFFT_NOT_IMPLEMENTED'. Function does not implement "
"functionality for parameters given.";
case HIPFFT_NOT_SUPPORTED:
return "'HIPFFT_NOT_SUPPORTED'. Operation is not supported for "
"parameters given.";
default:
return "HIPFFT_STATUS_UNKNOWN_ERROR";
}
}
} // namespace dynload
} // namespace platform
} // namespace paddle
......
paddle/fluid/platform/dynload/hiprand.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag hiprand_dso_flag;
void *hiprand_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
HIPRAND_RAND_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/hiprand.h
浏览文件 @ 1d755225
......@@ -16,28 +16,15 @@ limitations under the License. */
#include <hiprand.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/port.h"
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/pten/backends/dynload/hiprand.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag hiprand_dso_flag;
extern void *hiprand_dso_handle;
#define DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
hiprandStatus_t operator()(Args... args) { \
using hiprandFunc = decltype(&::__name); \
std::call_once(hiprand_dso_flag, []() { \
hiprand_dso_handle = paddle::platform::dynload::GetCurandDsoHandle(); \
}); \
static void *p_##__name = dlsym(hiprand_dso_handle, #__name); \
return reinterpret_cast<hiprandFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_CURAND_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define HIPRAND_RAND_ROUTINE_EACH(__macro) \
......@@ -49,7 +36,7 @@ extern void *hiprand_dso_handle;
__macro(hiprandGenerateNormal); \
__macro(hiprandDestroyGenerator);
HIPRAND_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_CURAND_WRAP);
HIPRAND_RAND_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_CURAND_WRAP);
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/hiprtc.cc
浏览文件 @ 1d755225
......@@ -13,23 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/hiprtc.h"
#include "paddle/pten/backends/dynload/hiprtc.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag hiprtc_dso_flag;
void* hiprtc_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
HIPRTC_ROUTINE_EACH(DEFINE_WRAP);
bool HasNVRTC() {
std::call_once(hiprtc_dso_flag,
[]() { hiprtc_dso_handle = GetNVRTCDsoHandle(); });
return hiprtc_dso_handle != nullptr;
}
bool HasNVRTC() { return pten::dynload::HasNVRTC(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/hiprtc.h
浏览文件 @ 1d755225
......@@ -16,30 +16,17 @@ limitations under the License. */
#include <hip/hiprtc.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/hiprtc.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag hiprtc_dso_flag;
extern void* hiprtc_dso_handle;
extern bool HasNVRTC();
#define DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using hiprtc_func = decltype(&::__name); \
std::call_once(hiprtc_dso_flag, []() { \
hiprtc_dso_handle = paddle::platform::dynload::GetNVRTCDsoHandle(); \
}); \
static void* p_##__name = dlsym(hiprtc_dso_handle, #__name); \
return reinterpret_cast<hiprtc_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed hiprtc functions
......@@ -55,9 +42,9 @@ extern bool HasNVRTC();
__macro(hiprtcGetProgramLog); \
__macro(hiprtcGetProgramLogSize)
HIPRTC_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP);
HIPRTC_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP);
#undef DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_HIPRTC_WRAP
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/lapack.cc
浏览文件 @ 1d755225
......@@ -13,15 +13,11 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/lapack.h"
#include <mutex>
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag lapack_dso_flag;
void* lapack_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
LAPACK_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/lapack.h
浏览文件 @ 1d755225
......@@ -16,122 +16,20 @@ limitations under the License. */
#include <complex>
#include <mutex>
#include "paddle/fluid/platform/complex.h"
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
// Note(zhouwei): because lapack doesn't provide appropriate header file.
// should expose API statement yourself.
// getrf_(For example)
extern "C" void dgetrf_(int *m, int *n, double *a, int *lda, int *ipiv,
int *info);
extern "C" void sgetrf_(int *m, int *n, float *a, int *lda, int *ipiv,
int *info);
// evd
extern "C" void zheevd_(char *jobz, char *uplo, int *n, std::complex<double> *a,
int *lda, double *w, std::complex<double> *work,
int *lwork, double *rwork, int *lrwork, int *iwork,
int *liwork, int *info);
extern "C" void cheevd_(char *jobz, char *uplo, int *n, std::complex<float> *a,
int *lda, float *w, std::complex<float> *work,
int *lwork, float *rwork, int *lrwork, int *iwork,
int *liwork, int *info);
extern "C" void dsyevd_(char *jobz, char *uplo, int *n, double *a, int *lda,
double *w, double *work, int *lwork, int *iwork,
int *liwork, int *info);
extern "C" void ssyevd_(char *jobz, char *uplo, int *n, float *a, int *lda,
float *w, float *work, int *lwork, int *iwork,
int *liwork, int *info);
// geev
extern "C" void dgeev_(char *jobvl, char *jobvr, int *n, double *a, int *lda,
double *wr, double *wi, double *vl, int *ldvl,
double *vr, int *ldvr, double *work, int *lwork,
int *info);
extern "C" void sgeev_(char *jobvl, char *jobvr, int *n, float *a, int *lda,
float *wr, float *wi, float *vl, int *ldvl, float *vr,
int *ldvr, float *work, int *lwork, int *info);
extern "C" void zgeev_(char *jobvl, char *jobvr, int *n,
std::complex<double> *a, int *lda,
std::complex<double> *w, std::complex<double> *vl,
int *ldvl, std::complex<double> *vr, int *ldvr,
std::complex<double> *work, int *lwork, double *rwork,
int *info);
extern "C" void cgeev_(char *jobvl, char *jobvr, int *n, std::complex<float> *a,
int *lda, std::complex<float> *w,
std::complex<float> *vl, int *ldvl,
std::complex<float> *vr, int *ldvr,
std::complex<float> *work, int *lwork, float *rwork,
int *info);
// gels
extern "C" void dgels_(char *trans, int *m, int *n, int *nrhs, double *a,
int *lda, double *b, int *ldb, double *work, int *lwork,
int *info);
extern "C" void sgels_(char *trans, int *m, int *n, int *nrhs, float *a,
int *lda, float *b, int *ldb, float *work, int *lwork,
int *info);
// gelsd
extern "C" void dgelsd_(int *m, int *n, int *nrhs, double *a, int *lda,
double *b, int *ldb, double *s, double *rcond,
int *rank, double *work, int *lwork, int *iwork,
int *info);
extern "C" void sgelsd_(int *m, int *n, int *nrhs, float *a, int *lda, float *b,
int *ldb, float *s, float *rcond, int *rank,
float *work, int *lwork, int *iwork, int *info);
// gelsy
extern "C" void dgelsy_(int *m, int *n, int *nrhs, double *a, int *lda,
double *b, int *ldb, int *jpvt, double *rcond,
int *rank, double *work, int *lwork, int *info);
extern "C" void sgelsy_(int *m, int *n, int *nrhs, float *a, int *lda, float *b,
int *ldb, int *jpvt, float *rcond, int *rank,
float *work, int *lwork, int *info);
// gelss
extern "C" void dgelss_(int *m, int *n, int *nrhs, double *a, int *lda,
double *b, int *ldb, double *s, double *rcond,
int *rank, double *work, int *lwork, int *info);
extern "C" void sgelss_(int *m, int *n, int *nrhs, float *a, int *lda, float *b,
int *ldb, float *s, float *rcond, int *rank,
float *work, int *lwork, int *info);
extern "C" void zpotrs_(char *uplo, int *n, int *nrhs, std::complex<double> *a,
int *lda, std::complex<double> *b, int *ldb, int *info);
extern "C" void cpotrs_(char *uplo, int *n, int *nrhs, std::complex<float> *a,
int *lda, std::complex<float> *b, int *ldb, int *info);
extern "C" void dpotrs_(char *uplo, int *n, int *nrhs, double *a, int *lda,
double *b, int *ldb, int *info);
extern "C" void spotrs_(char *uplo, int *n, int *nrhs, float *a, int *lda,
float *b, int *ldb, int *info);
#include "paddle/pten/backends/dynload/lapack.h"
#include "paddle/pten/common/complex.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag lapack_dso_flag;
extern void *lapack_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load lapack routine
* via operator overloading.
*/
#define DYNAMIC_LOAD_LAPACK_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using lapackFunc = decltype(&::__name); \
std::call_once(lapack_dso_flag, []() { \
lapack_dso_handle = paddle::platform::dynload::GetLAPACKDsoHandle(); \
}); \
static void *p_##_name = dlsym(lapack_dso_handle, #__name); \
return reinterpret_cast<lapackFunc>(p_##_name)(args...); \
} \
}; \
#define DYNAMIC_LOAD_LAPACK_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define DECLARE_DYNAMIC_LOAD_LAPACK_WRAP(__name) \
......
paddle/fluid/platform/dynload/miopen.cc
浏览文件 @ 1d755225
......@@ -13,13 +13,11 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/miopen.h"
#include "paddle/fluid/platform/enforce.h"
#include "paddle/pten/backends/dynload/cudnn.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag miopen_dso_flag;
void* miopen_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
......@@ -50,19 +48,7 @@ MIOPEN_DNN_ROUTINE_EACH_R7(DEFINE_WRAP);
MIOPEN_DNN_ROUTINE_EACH_AFTER_R7(DEFINE_WRAP);
#endif
bool HasCUDNN() {
std::call_once(miopen_dso_flag,
[]() { miopen_dso_handle = GetCUDNNDsoHandle(); });
return miopen_dso_handle != nullptr;
}
void EnforceCUDNNLoaded(const char* fn_name) {
PADDLE_ENFORCE_NOT_NULL(
miopen_dso_handle,
platform::errors::PreconditionNotMet(
"Cannot load miopen shared library. Cannot invoke method %s.",
fn_name));
}
bool HasCUDNN() { return pten::dynload::HasCUDNN(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/miopen.h
浏览文件 @ 1d755225
......@@ -18,66 +18,17 @@ limitations under the License. */
#include <miopen/miopen.h>
#include <miopen/version.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#define MIOPEN_VERSION \
(MIOPEN_VERSION_MAJOR * 1000 + MIOPEN_VERSION_MINOR * 10 + \
MIOPEN_VERSION_PATCH) // NOLINT
// MIOPEN only support NCHW, just for compatibility with CUDNN API
typedef enum {
MIOPEN_TENSOR_NCHW = 0,
MIOPEN_TENSOR_NHWC = 1,
} miopenTensorFormat_t;
#include "paddle/pten/backends/dynload/miopen.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag miopen_dso_flag;
extern void* miopen_dso_handle;
extern bool HasCUDNN();
inline const char* miopenGetErrorString(miopenStatus_t status) {
switch (status) {
case miopenStatusSuccess:
return "MIOPEN_STATUS_SUCCESS";
case miopenStatusNotInitialized:
return "MIOPEN_STATUS_NOT_INITIALIZED";
case miopenStatusInvalidValue:
return "MIOPEN_STATUS_INVALID_VALUE";
case miopenStatusBadParm:
return "MIOPEN_STATUS_BAD_PARAM";
case miopenStatusAllocFailed:
return "MIOPEN_STATUS_ALLOC_FAILED";
case miopenStatusInternalError:
return "MIOPEN_STATUS_INTERNAL_ERROR";
case miopenStatusNotImplemented:
return "MIOPEN_STATUS_NOT_IMPLEMENTED";
case miopenStatusUnsupportedOp:
return "MIOPEN_STATUS_UNSUPPORTED_OP";
case miopenStatusUnknownError:
default:
return "MIOPEN_STATUS_UNKNOWN_ERROR";
}
}
extern void EnforceCUDNNLoaded(const char* fn_name);
#define DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using miopen_func = decltype(&::__name); \
std::call_once(miopen_dso_flag, []() { \
miopen_dso_handle = paddle::platform::dynload::GetCUDNNDsoHandle(); \
}); \
EnforceCUDNNLoaded(#__name); \
static void* p_##__name = dlsym(miopen_dso_handle, #__name); \
return reinterpret_cast<miopen_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed miopen functions in HPPL
......@@ -145,23 +96,23 @@ extern void EnforceCUDNNLoaded(const char* fn_name);
__macro(miopenRNNForwardInference); \
__macro(miopenGetTensorNumBytes);
MIOPEN_DNN_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
#define MIOPEN_DNN_ROUTINE_EACH_R2(__macro) \
__macro(miopenConvolutionBackwardData);
MIOPEN_DNN_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_R2(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
// APIs available after R3:
#define MIOPEN_DNN_ROUTINE_EACH_AFTER_R3(__macro) \
__macro(miopenConvolutionBackwardWeightsGetWorkSpaceSize);
MIOPEN_DNN_ROUTINE_EACH_AFTER_R3(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_AFTER_R3(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
// APIs available after R4:
#define MIOPEN_DNN_ROUTINE_EACH_AFTER_R4(__macro) \
__macro(miopenBatchNormalizationForwardTraining); \
__macro(miopenBatchNormalizationForwardInference); \
__macro(miopenBatchNormalizationBackward);
MIOPEN_DNN_ROUTINE_EACH_AFTER_R4(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_AFTER_R4(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
// APIs in R5
#define MIOPEN_DNN_ROUTINE_EACH_R5(__macro) \
......@@ -169,12 +120,12 @@ MIOPEN_DNN_ROUTINE_EACH_AFTER_R4(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
__macro(miopenSetActivationDescriptor); \
__macro(miopenGetActivationDescriptor); \
__macro(miopenDestroyActivationDescriptor);
MIOPEN_DNN_ROUTINE_EACH_R5(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_R5(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
// APIs in R6
#define MIOPEN_DNN_ROUTINE_EACH_R6(__macro) \
/*__macro(miopenSetRNNDescriptor_v6);*/
MIOPEN_DNN_ROUTINE_EACH_R6(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_R6(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
#define MIOPEN_DNN_ROUTINE_EACH_R7(__macro) \
__macro(miopenSetConvolutionGroupCount); \
......@@ -184,7 +135,7 @@ MIOPEN_DNN_ROUTINE_EACH_R6(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
__macro(miopenSetCTCLossDescriptor); \
__macro(miopenGetCTCLossWorkspaceSize); \
__macro(miopenCTCLoss);
MIOPEN_DNN_ROUTINE_EACH_R7(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_R7(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
#define MIOPEN_DNN_ROUTINE_EACH_AFTER_R7(__macro) \
/*__macro(cudnnGetBatchNormalizationForwardTrainingExWorkspaceSize); \
......@@ -192,7 +143,7 @@ __macro(cudnnBatchNormalizationForwardTrainingEx); \
__macro(cudnnGetBatchNormalizationBackwardExWorkspaceSize); \
__macro(cudnnBatchNormalizationBackwardEx); \
__macro(cudnnGetBatchNormalizationTrainingExReserveSpaceSize);*/
MIOPEN_DNN_ROUTINE_EACH_AFTER_R7(DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
MIOPEN_DNN_ROUTINE_EACH_AFTER_R7(PLATFORM_DECLARE_DYNAMIC_LOAD_MIOPEN_WRAP)
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/mklml.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag mklml_dso_flag;
void* mklml_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
MKLML_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/mklml.h
浏览文件 @ 1d755225
......@@ -17,36 +17,23 @@ limitations under the License. */
#include <mkl.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/mklml.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag mklml_dso_flag;
extern void *mklml_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load mklml routine
* via operator overloading.
*/
#define DYNAMIC_LOAD_MKLML_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using mklmlFunc = decltype(&::__name); \
std::call_once(mklml_dso_flag, []() { \
mklml_dso_handle = paddle::platform::dynload::GetMKLMLDsoHandle(); \
}); \
static void *p_##_name = dlsym(mklml_dso_handle, #__name); \
return reinterpret_cast<mklmlFunc>(p_##_name)(args...); \
} \
}; \
#define DYNAMIC_LOAD_MKLML_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define DECLARE_DYNAMIC_LOAD_MKLML_WRAP(__name) DYNAMIC_LOAD_MKLML_WRAP(__name)
#define PLATFORM_DECLARE_DYNAMIC_LOAD_MKLML_WRAP(__name) \
DYNAMIC_LOAD_MKLML_WRAP(__name)
#define MKLML_ROUTINE_EACH(__macro) \
__macro(cblas_sgemm); \
......@@ -111,7 +98,7 @@ extern void *mklml_dso_handle;
__macro(MKL_Set_Num_Threads); \
__macro(MKL_Get_Max_Threads);
MKLML_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_MKLML_WRAP);
MKLML_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_MKLML_WRAP);
#if !defined(_WIN32)
DYNAMIC_LOAD_MKLML_WRAP(mkl_scsrmm);
......
paddle/fluid/platform/dynload/mklrt.h
浏览文件 @ 1d755225
......@@ -18,7 +18,7 @@ limitations under the License. */
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/port.h"
namespace paddle {
namespace platform {
......@@ -32,18 +32,8 @@ extern void* mklrt_dso_handle;
* (for each function) to dynamic load mkldfti routine
* via operator overloading.
*/
#define DYNAMIC_LOAD_MKLRT_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using mklrtFunc = decltype(&::__name); \
std::call_once(mklrt_dso_flag, []() { \
mklrt_dso_handle = paddle::platform::dynload::GetMKLRTDsoHandle(); \
}); \
static void* p_##__name = dlsym(mklrt_dso_handle, #__name); \
return reinterpret_cast<mklrtFunc>(p_##__name)(args...); \
} \
}; \
#define DYNAMIC_LOAD_MKLRT_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
// mkl_dfti.h has a macro that shadows the function with the same name
......
paddle/fluid/platform/dynload/nccl.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag nccl_dso_flag;
void *nccl_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
NCCL_RAND_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/nccl.h
浏览文件 @ 1d755225
......@@ -16,28 +16,14 @@ limitations under the License. */
#include <nccl.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/nccl.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag nccl_dso_flag;
extern void* nccl_dso_handle;
#define DECLARE_DYNAMIC_LOAD_NCCL_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> decltype(__name(args...)) { \
using nccl_func = decltype(&::__name); \
std::call_once(nccl_dso_flag, []() { \
nccl_dso_handle = paddle::platform::dynload::GetNCCLDsoHandle(); \
}); \
static void* p_##__name = dlsym(nccl_dso_handle, #__name); \
return reinterpret_cast<nccl_func>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define NCCL_RAND_ROUTINE_EACH(__macro) \
......@@ -57,30 +43,30 @@ extern void* nccl_dso_handle;
__macro(ncclReduceScatter); \
__macro(ncclGetErrorString);
NCCL_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
NCCL_RAND_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
#if NCCL_VERSION_CODE >= 2212
#define NCCL_RAND_ROUTINE_EACH_AFTER_2212(__macro) __macro(ncclBroadcast);
NCCL_RAND_ROUTINE_EACH_AFTER_2212(DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
NCCL_RAND_ROUTINE_EACH_AFTER_2212(PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
#endif
#if NCCL_VERSION_CODE >= 2304
#define NCCL_RAND_ROUTINE_EACH_AFTER_2304(__macro) __macro(ncclGetVersion);
NCCL_RAND_ROUTINE_EACH_AFTER_2304(DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
NCCL_RAND_ROUTINE_EACH_AFTER_2304(PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
#endif
#if NCCL_VERSION_CODE >= 2703
#define NCCL_RAND_ROUTINE_EACH_AFTER_2703(__macro) \
__macro(ncclSend); \
__macro(ncclRecv);
NCCL_RAND_ROUTINE_EACH_AFTER_2703(DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
NCCL_RAND_ROUTINE_EACH_AFTER_2703(PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
#endif
#if NCCL_VERSION_CODE >= 21100
#define NCCL_RAND_ROUTINE_EACH_AFTER_21100(__macro) \
__macro(ncclRedOpCreatePreMulSum); \
__macro(ncclRedOpDestroy);
NCCL_RAND_ROUTINE_EACH_AFTER_21100(DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
NCCL_RAND_ROUTINE_EACH_AFTER_21100(PLATFORM_DECLARE_DYNAMIC_LOAD_NCCL_WRAP)
#endif
} // namespace dynload
......
paddle/fluid/platform/dynload/nvjpeg.cc
浏览文件 @ 1d755225
......@@ -15,9 +15,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag nvjpeg_dso_flag;
void *nvjpeg_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
NVJPEG_RAND_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/nvjpeg.h
浏览文件 @ 1d755225
......@@ -14,27 +14,14 @@ limitations under the License. */
#include <nvjpeg.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/nvjpeg.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag nvjpeg_dso_flag;
extern void *nvjpeg_dso_handle;
#define DECLARE_DYNAMIC_LOAD_NVJPEG_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
nvjpegStatus_t operator()(Args... args) { \
using nvjpegFunc = decltype(&::__name); \
std::call_once(nvjpeg_dso_flag, []() { \
nvjpeg_dso_handle = paddle::platform::dynload::GetNvjpegDsoHandle(); \
}); \
static void *p_##__name = dlsym(nvjpeg_dso_handle, #__name); \
return reinterpret_cast<nvjpegFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_NVJPEG_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define NVJPEG_RAND_ROUTINE_EACH(__macro) \
......@@ -44,7 +31,7 @@ extern void *nvjpeg_dso_handle;
__macro(nvjpegJpegStateDestroy); \
__macro(nvjpegDecode);
NVJPEG_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_NVJPEG_WRAP);
NVJPEG_RAND_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_NVJPEG_WRAP);
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/nvrtc.cc
浏览文件 @ 1d755225
......@@ -13,23 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/nvrtc.h"
#include "paddle/pten/backends/dynload/nvrtc.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag nvrtc_dso_flag;
void* nvrtc_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
NVRTC_ROUTINE_EACH(DEFINE_WRAP);
bool HasNVRTC() {
std::call_once(nvrtc_dso_flag,
[]() { nvrtc_dso_handle = GetNVRTCDsoHandle(); });
return nvrtc_dso_handle != nullptr;
}
bool HasNVRTC() { return pten::dynload::HasNVRTC(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/nvrtc.h
浏览文件 @ 1d755225
......@@ -17,30 +17,17 @@ limitations under the License. */
#include <nvrtc.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/nvrtc.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag nvrtc_dso_flag;
extern void* nvrtc_dso_handle;
extern bool HasNVRTC();
#define DECLARE_DYNAMIC_LOAD_NVRTC_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using nvrtc_func = decltype(&::__name); \
std::call_once(nvrtc_dso_flag, []() { \
nvrtc_dso_handle = paddle::platform::dynload::GetNVRTCDsoHandle(); \
}); \
static void* p_##__name = dlsym(nvrtc_dso_handle, #__name); \
return reinterpret_cast<nvrtc_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_NVRTC_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed nvrtc functions
......@@ -56,9 +43,9 @@ extern bool HasNVRTC();
__macro(nvrtcGetProgramLog); \
__macro(nvrtcGetProgramLogSize)
NVRTC_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_NVRTC_WRAP);
NVRTC_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_NVRTC_WRAP);
#undef DECLARE_DYNAMIC_LOAD_NVRTC_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_NVRTC_WRAP
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/nvtx.cc
浏览文件 @ 1d755225
......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag nvtx_dso_flag;
void *nvtx_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
NVTX_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/nvtx.h
浏览文件 @ 1d755225
......@@ -17,36 +17,23 @@ limitations under the License. */
#include <nvToolsExt.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/nvtx.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag nvtx_dso_flag;
extern void *nvtx_dso_handle;
#define DECLARE_DYNAMIC_LOAD_NVTX_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
int operator()(Args... args) { \
using nvtxFunc = decltype(&::__name); \
std::call_once(nvtx_dso_flag, []() { \
nvtx_dso_handle = paddle::platform::dynload::GetNvtxDsoHandle(); \
}); \
static void *p_##__name = dlsym(nvtx_dso_handle, #__name); \
return reinterpret_cast<nvtxFunc>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_NVTX_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define NVTX_ROUTINE_EACH(__macro) \
__macro(nvtxRangePushA); \
__macro(nvtxRangePop);
NVTX_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_NVTX_WRAP);
NVTX_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_NVTX_WRAP);
#undef DECLARE_DYNAMIC_LOAD_NVTX_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_NVTX_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
......
paddle/fluid/platform/dynload/rccl.cc
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......@@ -18,9 +18,6 @@ namespace paddle {
namespace platform {
namespace dynload {
std::once_flag rccl_dso_flag;
void *rccl_dso_handle;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
RCCL_RAND_ROUTINE_EACH(DEFINE_WRAP);
......
paddle/fluid/platform/dynload/rccl.h
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......@@ -16,28 +16,14 @@ limitations under the License. */
#include <rccl.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/rccl.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag rccl_dso_flag;
extern void* rccl_dso_handle;
#define DECLARE_DYNAMIC_LOAD_RCCL_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> decltype(__name(args...)) { \
using nccl_func = decltype(&::__name); \
std::call_once(rccl_dso_flag, []() { \
rccl_dso_handle = paddle::platform::dynload::GetNCCLDsoHandle(); \
}); \
static void* p_##__name = dlsym(rccl_dso_handle, #__name); \
return reinterpret_cast<nccl_func>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_RCCL_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define RCCL_RAND_ROUTINE_EACH(__macro) \
......@@ -57,18 +43,18 @@ extern void* rccl_dso_handle;
__macro(ncclReduceScatter); \
__macro(ncclGetErrorString);
RCCL_RAND_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
RCCL_RAND_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
#if NCCL_VERSION_CODE >= 2212
#define RCCL_RAND_ROUTINE_EACH_AFTER_2212(__macro) __macro(ncclBroadcast);
RCCL_RAND_ROUTINE_EACH_AFTER_2212(DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
RCCL_RAND_ROUTINE_EACH_AFTER_2212(PLATFORM_DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
#endif
#if NCCL_VERSION_CODE >= 2703
#define RCCL_RAND_ROUTINE_EACH_AFTER_2703(__macro) \
__macro(ncclSend); \
__macro(ncclRecv);
RCCL_RAND_ROUTINE_EACH_AFTER_2703(DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
RCCL_RAND_ROUTINE_EACH_AFTER_2703(PLATFORM_DECLARE_DYNAMIC_LOAD_RCCL_WRAP)
#endif
} // namespace dynload
......
paddle/fluid/platform/dynload/rocblas.cc
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namespace paddle {
namespace platform {
namespace dynload {
std::once_flag rocblas_dso_flag;
void *rocblas_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
......
paddle/fluid/platform/dynload/rocblas.h
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......@@ -19,16 +19,12 @@ limitations under the License. */
#include <mutex> // NOLINT
#include <type_traits>
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/rocblas.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag rocblas_dso_flag;
extern void *rocblas_dso_handle;
/**
* The following macro definition can generate structs
* (for each function) to dynamic load cublas routine
......@@ -36,18 +32,8 @@ extern void *rocblas_dso_handle;
*
* note: default dynamic linked libs
*/
#define DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
rocblas_status operator()(Args... args) { \
using rocblas_func = decltype(&::__name); \
std::call_once(rocblas_dso_flag, []() { \
rocblas_dso_handle = paddle::platform::dynload::GetCublasDsoHandle(); \
}); \
static void *p_##__name = dlsym(rocblas_dso_handle, #__name); \
return reinterpret_cast<rocblas_func>(p_##__name)(args...); \
} \
}; \
#define PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
#define ROCBLAS_BLAS_ROUTINE_EACH(__macro) \
......@@ -83,7 +69,7 @@ extern void *rocblas_dso_handle;
__macro(rocblas_set_pointer_mode); \
__macro(rocblas_get_pointer_mode);
ROCBLAS_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
ROCBLAS_BLAS_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
// APIs available after CUDA 8.0
#define ROCBLAS_BLAS_ROUTINE_EACH_R2(__macro) \
......@@ -94,21 +80,21 @@ ROCBLAS_BLAS_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
__macro(rocblas_zgemm_strided_batched); \
__macro(rocblas_hgemm_strided_batched);
ROCBLAS_BLAS_ROUTINE_EACH_R2(DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
ROCBLAS_BLAS_ROUTINE_EACH_R2(PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
// HIP not supported in ROCM3.5
// #define ROCBLAS_BLAS_ROUTINE_EACH_R3(__macro)
// __macro(cublasSetMathMode);
// __macro(cublasGetMathMode);
// ROCBLAS_BLAS_ROUTINE_EACH_R3(DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
// ROCBLAS_BLAS_ROUTINE_EACH_R3(PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
#define ROCBLAS_BLAS_ROUTINE_EACH_R4(__macro) \
__macro(rocblas_gemm_batched_ex); \
__macro(rocblas_gemm_strided_batched_ex);
ROCBLAS_BLAS_ROUTINE_EACH_R4(DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
ROCBLAS_BLAS_ROUTINE_EACH_R4(PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP)
#undef DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_ROCBLAS_WRAP
} // namespace dynload
} // namespace platform
} // namespace paddle
paddle/fluid/platform/dynload/rocm_driver.cc
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......@@ -13,22 +13,17 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/platform/dynload/rocm_driver.h"
#include "paddle/pten/backends/dynload/rocm_driver.h"
namespace paddle {
namespace platform {
namespace dynload {
std::once_flag rocm_dso_flag;
void* rocm_dso_handle = nullptr;
#define DEFINE_WRAP(__name) DynLoad__##__name __name
ROCM_ROUTINE_EACH(DEFINE_WRAP);
bool HasCUDADriver() {
std::call_once(rocm_dso_flag, []() { rocm_dso_handle = GetCUDADsoHandle(); });
return rocm_dso_handle != nullptr;
}
bool HasCUDADriver() { return pten::dynload::HasCUDADriver(); }
} // namespace dynload
} // namespace platform
......
paddle/fluid/platform/dynload/rocm_driver.h
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......@@ -17,30 +17,17 @@ limitations under the License. */
#include <hip/hip_runtime.h>
#include <mutex> // NOLINT
#include "paddle/fluid/platform/dynload/dynamic_loader.h"
#include "paddle/fluid/platform/port.h"
#include "paddle/pten/backends/dynload/rocm_driver.h"
namespace paddle {
namespace platform {
namespace dynload {
extern std::once_flag rocm_dso_flag;
extern void* rocm_dso_handle;
extern bool HasCUDADriver();
#define DECLARE_DYNAMIC_LOAD_ROCM_WRAP(__name) \
struct DynLoad__##__name { \
template <typename... Args> \
auto operator()(Args... args) -> DECLARE_TYPE(__name, args...) { \
using rocm_func = decltype(&::__name); \
std::call_once(rocm_dso_flag, []() { \
rocm_dso_handle = paddle::platform::dynload::GetCUDADsoHandle(); \
}); \
static void* p_##__name = dlsym(rocm_dso_handle, #__name); \
return reinterpret_cast<rocm_func>(p_##__name)(args...); \
} \
}; \
extern struct DynLoad__##__name __name
#define PLATFORM_DECLARE_DYNAMIC_LOAD_ROCM_WRAP(__name) \
using DynLoad__##__name = pten::dynload::DynLoad__##__name; \
extern DynLoad__##__name __name
/**
* include all needed cuda driver functions
......@@ -59,9 +46,9 @@ extern bool HasCUDADriver();
__macro(hipGetDeviceCount); \
__macro(hipDevicePrimaryCtxGetState)
ROCM_ROUTINE_EACH(DECLARE_DYNAMIC_LOAD_ROCM_WRAP);
ROCM_ROUTINE_EACH(PLATFORM_DECLARE_DYNAMIC_LOAD_ROCM_WRAP);
#undef DECLARE_DYNAMIC_LOAD_ROCM_WRAP
#undef PLATFORM_DECLARE_DYNAMIC_LOAD_ROCM_WRAP
} // namespace dynload
} // namespace platform
......
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