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体验新版 GitCode,发现更多精彩内容 >>
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6891a4fe
编写于
9月 14, 2022
作者:
C
Chen Weihang
提交者:
GitHub
9月 14, 2022
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
normize yaml backward op label (#46028)
上级
6bd2762c
变更
8
展开全部
隐藏空白更改
内联
并排
Showing
8 changed file
with
322 addition
and
323 deletion
+322
-323
paddle/fluid/eager/auto_code_generator/generator/codegen_utils.py
...luid/eager/auto_code_generator/generator/codegen_utils.py
+4
-4
paddle/fluid/eager/auto_code_generator/generator/eager_gen.py
...le/fluid/eager/auto_code_generator/generator/eager_gen.py
+2
-3
paddle/phi/api/yaml/backward.yaml
paddle/phi/api/yaml/backward.yaml
+21
-21
paddle/phi/api/yaml/generator/backward_api_gen.py
paddle/phi/api/yaml/generator/backward_api_gen.py
+1
-1
paddle/phi/api/yaml/generator/parse_api.py
paddle/phi/api/yaml/generator/parse_api.py
+1
-1
paddle/phi/api/yaml/generator/parse_utils.py
paddle/phi/api/yaml/generator/parse_utils.py
+1
-1
paddle/phi/api/yaml/legacy_backward.yaml
paddle/phi/api/yaml/legacy_backward.yaml
+254
-254
paddle/phi/api/yaml/sparse_backward.yaml
paddle/phi/api/yaml/sparse_backward.yaml
+38
-38
未找到文件。
paddle/fluid/eager/auto_code_generator/generator/codegen_utils.py
浏览文件 @
6891a4fe
...
...
@@ -83,10 +83,10 @@ def ReadBwdFile(filepath):
ret
=
{}
if
contents
is
not
None
:
for
content
in
contents
:
assert
'backward_
api
'
in
content
.
keys
(),
AssertMessage
(
'backward_
api
'
,
content
.
keys
())
if
'backward_
api
'
in
content
.
keys
():
api_name
=
content
[
'backward_
api
'
]
assert
'backward_
op
'
in
content
.
keys
(),
AssertMessage
(
'backward_
op
'
,
content
.
keys
())
if
'backward_
op
'
in
content
.
keys
():
api_name
=
content
[
'backward_
op
'
]
ret
[
api_name
]
=
content
f
.
close
()
...
...
paddle/fluid/eager/auto_code_generator/generator/eager_gen.py
浏览文件 @
6891a4fe
...
...
@@ -1485,7 +1485,7 @@ class DygraphNodeGenerator(DygraphFunctionGeneratorBase):
if
next_grad_api_contents
:
# Fake forward_api_contents and backward_api_contents
forward_api_contents
=
grad_api_contents
forward_api_contents
[
'op'
]
=
forward_api_contents
[
'backward_
api
'
]
forward_api_contents
[
'op'
]
=
forward_api_contents
[
'backward_
op
'
]
backward_api_contents
=
next_grad_api_contents
next_node_generator
=
DygraphFunctionGeneratorBase
(
...
...
@@ -1959,8 +1959,7 @@ class DygraphForwardAndNodesGenerator(GeneratorBase):
forward_api_contents
=
backward_api_contents
# Fake forward_api_content
forward_api_contents
[
'op'
]
=
forward_api_contents
[
'backward_api'
]
forward_api_contents
[
'op'
]
=
forward_api_contents
[
'backward_op'
]
backward_api_contents
=
next_grad_api_contents
if
len
(
namespace
)
>
0
:
...
...
paddle/phi/api/yaml/backward.yaml
浏览文件 @
6891a4fe
-
backward_
api
:
atan2_grad
-
backward_
op
:
atan2_grad
forward
:
atan2 (Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -8,7 +8,7 @@
kernel
:
func
:
atan2_grad
-
backward_
api
:
cholesky_grad
-
backward_
op
:
cholesky_grad
forward
:
cholesky (Tensor x, bool upper) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, bool upper)
output
:
Tensor(x_grad)
...
...
@@ -18,7 +18,7 @@
kernel
:
func
:
cholesky_grad
-
backward_
api
:
cholesky_solve_grad
-
backward_
op
:
cholesky_solve_grad
forward
:
cholesky_solve (Tensor x, Tensor y, bool upper) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out, Tensor out_grad, bool upper)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -28,7 +28,7 @@
kernel
:
func
:
cholesky_solve_grad
-
backward_
api
:
cross_grad
-
backward_
op
:
cross_grad
forward
:
cross (Tensor x, Tensor y, int axis = 9) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad, int axis)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -39,7 +39,7 @@
func
:
cross_grad
data_type
:
out_grad
-
backward_
api
:
diag_grad
-
backward_
op
:
diag_grad
forward
:
diag (Tensor x, int offset, float padding_value) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, int offset)
output
:
Tensor(x_grad)
...
...
@@ -51,7 +51,7 @@
data_type
:
out_grad
no_need_buffer
:
x
-
backward_
api
:
diagonal_grad
-
backward_
op
:
diagonal_grad
forward
:
diagonal (Tensor x, int offset, int axis1, int axis2) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, int offset = 0, int axis1 = 0, int axis2 = 1)
output
:
Tensor(x_grad)
...
...
@@ -63,7 +63,7 @@
data_type
:
out_grad
no_need_buffer
:
x
-
backward_
api
:
digamma_grad
-
backward_
op
:
digamma_grad
forward
:
digamma (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -73,7 +73,7 @@
kernel
:
func
:
digamma_grad
-
backward_
api
:
dist_grad
-
backward_
op
:
dist_grad
forward
:
dist (Tensor x, Tensor y, float p) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out, Tensor out_grad, float p)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -83,7 +83,7 @@
kernel
:
func
:
dist_grad
-
backward_
api
:
dot_grad
-
backward_
op
:
dot_grad
forward
:
dot (Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -94,7 +94,7 @@
func
:
dot_grad
data_type
:
out_grad
-
backward_
api
:
erf_grad
-
backward_
op
:
erf_grad
forward
:
erf (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -105,7 +105,7 @@
func
:
erf_grad
data_type
:
out_grad
-
backward_
api
:
erfinv_grad
-
backward_
op
:
erfinv_grad
forward
:
erfinv (Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -115,7 +115,7 @@
kernel
:
func
:
erfinv_grad
-
backward_
api
:
fft_c2c_grad
-
backward_
op
:
fft_c2c_grad
forward
:
fft_c2c(Tensor x, int64_t[] axes, str normalization, bool forward) -> Tensor(out)
args
:
(Tensor out_grad, int64_t[] axes, str normalization, bool forward)
output
:
Tensor(x_grad)
...
...
@@ -125,7 +125,7 @@
kernel
:
func
:
fft_c2c_grad
-
backward_
api
:
fft_c2r_grad
-
backward_
op
:
fft_c2r_grad
forward
:
fft_c2r(Tensor x, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size) -> Tensor(out)
args
:
(Tensor out_grad, int64_t[] axes, str normalization, bool forward, int64_t last_dim_size)
output
:
Tensor(x_grad)
...
...
@@ -135,7 +135,7 @@
func
:
fft_c2r_grad
data_type
:
out_grad
-
backward_
api
:
fft_r2c_grad
-
backward_
op
:
fft_r2c_grad
forward
:
fft_r2c(Tensor x, int64_t[] axes, str normalization, bool forward, bool onesided) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, int64_t[] axes, str normalization, bool forward, bool onesided)
output
:
Tensor(x_grad)
...
...
@@ -147,7 +147,7 @@
data_type
:
out_grad
no_need_buffer
:
x
-
backward_
api
:
graph_send_uv_grad
-
backward_
op
:
graph_send_uv_grad
forward
:
graph_send_uv (Tensor x, Tensor y, Tensor src_index, Tensor dst_index, str message_op = "ADD") -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor src_index, Tensor dst_index, Tensor out_grad, str message_op = "ADD")
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -158,7 +158,7 @@
func
:
graph_send_uv_grad
data_type
:
x
-
backward_
api
:
lgamma_grad
-
backward_
op
:
lgamma_grad
forward
:
lgamma(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -168,7 +168,7 @@
kernel
:
func
:
lgamma_grad
-
backward_
api
:
mv_grad
-
backward_
op
:
mv_grad
forward
:
mv (Tensor x, Tensor vec) -> Tensor(out)
args
:
(Tensor x, Tensor vec, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(vec_grad)
...
...
@@ -178,7 +178,7 @@
kernel
:
func
:
mv_grad
-
backward_
api
:
poisson_grad
-
backward_
op
:
poisson_grad
forward
:
poisson (Tensor x) -> Tensor(out)
args
:
(Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -188,7 +188,7 @@
kernel
:
func
:
poisson_grad
-
backward_
api
:
solve_grad
-
backward_
op
:
solve_grad
forward
:
solve (Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -198,7 +198,7 @@
kernel
:
func
:
solve_grad
-
backward_
api
:
trace_grad
-
backward_
op
:
trace_grad
forward
:
trace (Tensor x, int offset, int axis1, int axis2) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, int offset, int axis1, int axis2)
output
:
Tensor(x_grad)
...
...
@@ -210,7 +210,7 @@
data_type
:
out_grad
no_need_buffer
:
x
-
backward_
api
:
trunc_grad
-
backward_
op
:
trunc_grad
forward
:
trunc (Tensor x) -> Tensor(out)
args
:
(Tensor out_grad)
output
:
Tensor(x_grad)
...
...
paddle/phi/api/yaml/generator/backward_api_gen.py
浏览文件 @
6891a4fe
...
...
@@ -28,7 +28,7 @@ class BackwardAPI(BaseAPI):
self
.
no_need_buffer
=
self
.
parse_no_need_buffer
(
backward_item_yaml
)
def
get_api_name
(
self
,
api_item_yaml
):
return
api_item_yaml
[
'backward_
api
'
]
return
api_item_yaml
[
'backward_
op
'
]
def
parse_forward_config
(
self
,
forward_config
):
# api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out)
...
...
paddle/phi/api/yaml/generator/parse_api.py
浏览文件 @
6891a4fe
...
...
@@ -27,7 +27,7 @@ def main(api_yaml_path, output_path, backward):
apis
=
[]
else
:
apis
=
[
parse_api_entry
(
api
,
"backward_
api
"
if
backward
else
"op"
)
parse_api_entry
(
api
,
"backward_
op
"
if
backward
else
"op"
)
for
api
in
apis
]
...
...
paddle/phi/api/yaml/generator/parse_utils.py
浏览文件 @
6891a4fe
...
...
@@ -334,7 +334,7 @@ def parse_api_entry(api_entry: Dict[str, Any], name_field="op"):
api
[
"backward"
]
=
backward
# forward for backward_apis
is_backward_api
=
name_field
==
"backward_
api
"
is_backward_api
=
name_field
==
"backward_
op
"
if
is_backward_api
:
if
"forward"
in
api_entry
:
forward
=
parse_forward
(
api_name
,
api_entry
[
"forward"
])
...
...
paddle/phi/api/yaml/legacy_backward.yaml
浏览文件 @
6891a4fe
此差异已折叠。
点击以展开。
paddle/phi/api/yaml/sparse_backward.yaml
浏览文件 @
6891a4fe
-
backward_
api
:
abs_grad
-
backward_
op
:
abs_grad
forward
:
tanh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -6,7 +6,7 @@
func
:
abs_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
abs_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
acos_grad
-
backward_
op
:
acos_grad
forward
:
acos(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -14,7 +14,7 @@
func
:
acos_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acos_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
acosh_grad
-
backward_
op
:
acosh_grad
forward
:
acosh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -22,7 +22,7 @@
func
:
acosh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
acosh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
add_grad
-
backward_
op
:
add_grad
forward
:
add(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -30,7 +30,7 @@
func
:
add_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
add_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
-
backward_
api
:
addmm_grad
-
backward_
op
:
addmm_grad
forward
:
addmm(Tensor input, Tensor x, Tensor y, float alpha=1.0, float beta=1.0) -> Tensor(out)
args
:
(Tensor input, Tensor x, Tensor y, Tensor out_grad, float alpha=1.0, float beta=1.0)
output
:
Tensor(input_grad), Tensor(x_grad), Tensor(y_grad)
...
...
@@ -40,7 +40,7 @@
addmm_coo_dense_grad {dense, sparse_coo, dense, dense -> dense, sparse_coo, dense},
addmm_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo, sparse_coo}
-
backward_
api
:
asin_grad
-
backward_
op
:
asin_grad
forward
:
asin(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -48,7 +48,7 @@
func
:
asin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
asinh_grad
-
backward_
op
:
asinh_grad
forward
:
asinh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -56,7 +56,7 @@
func
:
asinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
asinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
atan_grad
-
backward_
op
:
atan_grad
forward
:
atan(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -64,7 +64,7 @@
func
:
atan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
atanh_grad
-
backward_
op
:
atanh_grad
forward
:
atanh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -72,7 +72,7 @@
func
:
atanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
atanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
cast_grad
-
backward_
op
:
cast_grad
forward
:
cast(Tensor x, DataType index_dtype, DataType value_dtype) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, DataType value_dtype)
output
:
Tensor(x_grad)
...
...
@@ -81,14 +81,14 @@
cast_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
data_type
:
out_grad
-
backward_
api
:
conv3d_coo_grad
-
backward_
op
:
conv3d_coo_grad
forward
:
conv3d_coo (Tensor x, Tensor kernel, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args
:
(Tensor x, Tensor kernel, Tensor out, Tensor rulebook, Tensor counter, Tensor out_grad, int[] paddings, int[] dilations, int[] strides, int groups, bool subm, str key)
output
:
Tensor(x_grad), Tensor(kernel_grad)
kernel
:
func
:
conv3d_coo_grad{sparse_coo, dense, sparse_coo, dense, dense, sparse_coo -> sparse_coo, dense}
-
backward_
api
:
divide_grad
-
backward_
op
:
divide_grad
forward
:
divide(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -96,13 +96,13 @@
func
:
divide_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
divide_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
-
backward_
api
:
divide_scalar_grad
-
backward_
op
:
divide_scalar_grad
forward
:
divide_scalar (Tensor x, float scalar) -> Tensor(out)
args
:
(Tensor out_grad, float scalar)
output
:
Tensor(x_grad)
invoke
:
divide_scalar(out_grad, scalar)
-
backward_
api
:
expm1_grad
-
backward_
op
:
expm1_grad
forward
:
expm1(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -110,7 +110,7 @@
func
:
expm1_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
expm1_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
leaky_relu_grad
-
backward_
op
:
leaky_relu_grad
forward
:
leaky_relu(Tensor x, float alpha) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float alpha)
output
:
Tensor(x_grad)
...
...
@@ -118,7 +118,7 @@
func
:
leaky_relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
leaky_relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
log1p_grad
-
backward_
op
:
log1p_grad
forward
:
log1p(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -126,14 +126,14 @@
func
:
log1p_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
log1p_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
masked_matmul_grad
-
backward_
op
:
masked_matmul_grad
forward
:
masked_matmul(Tensor x, Tensor y, Tensor mask) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
kernel
:
func
:
masked_matmul_csr_grad{dense, dense, sparse_csr -> dense, dense}
-
backward_
api
:
matmul_grad
-
backward_
op
:
matmul_grad
forward
:
matmul(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -143,14 +143,14 @@
matmul_coo_dense_grad {sparse_coo, dense, dense -> sparse_coo, dense},
matmul_coo_coo_grad {sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo}
-
backward_
api
:
maxpool_grad
-
backward_
op
:
maxpool_grad
forward
:
maxpool(Tensor x, int[] kernel_sizes, int[] paddings, int[] dilations, int[] strides) -> Tensor(out), Tensor(rulebook), Tensor(counter)
args
:
(Tensor x, Tensor rulebook, Tensor counter, Tensor out, Tensor out_grad, int[] kernel_sizes)
output
:
Tensor(x_grad)
kernel
:
func
:
maxpool_coo_grad {sparse_coo, dense, dense, sparse_coo, sparse_coo -> sparse_coo}
-
backward_
api
:
multiply_grad
-
backward_
op
:
multiply_grad
forward
:
multiply(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -158,7 +158,7 @@
func
:
multiply_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
multiply_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
-
backward_
api
:
mv_grad
-
backward_
op
:
mv_grad
forward
:
mv(Tensor x, Tensor vec) -> Tensor(out)
args
:
(Tensor x, Tensor vec, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(vec_grad)
...
...
@@ -166,7 +166,7 @@
func
:
mv_coo_grad{sparse_coo, dense, dense -> sparse_coo, dense},
mv_csr_grad{sparse_csr, dense, dense -> sparse_csr, dense}
-
backward_
api
:
pow_grad
-
backward_
op
:
pow_grad
forward
:
pow(Tensor x, float factor) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float factor)
output
:
Tensor(x_grad)
...
...
@@ -174,7 +174,7 @@
func
:
pow_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
pow_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
relu6_grad
-
backward_
op
:
relu6_grad
forward
:
relu6(Tensor x, float threshold) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, float threshold)
output
:
Tensor(x_grad)
...
...
@@ -182,7 +182,7 @@
func
:
relu6_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu6_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
relu_grad
-
backward_
op
:
relu_grad
forward
:
relu(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -190,13 +190,13 @@
func
:
relu_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
relu_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
scale_grad
-
backward_
op
:
scale_grad
forward
:
scale(Tensor x, float scale, float bias, bool bias_after_scale) -> Tensor(out)
args
:
(Tensor out_grad, float scale)
output
:
Tensor(x_grad)
invoke
:
scale(out_grad, scale, 0.0,
true
)
-
backward_
api
:
sin_grad
-
backward_
op
:
sin_grad
forward
:
sin(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -204,7 +204,7 @@
func
:
sin_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sin_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
sinh_grad
-
backward_
op
:
sinh_grad
forward
:
sinh(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -212,21 +212,21 @@
func
:
sinh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sinh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
softmax_grad
-
backward_
op
:
softmax_grad
forward
:
softmax(Tensor x, int axis=-1) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, int axis)
output
:
Tensor(x_grad)
kernel
:
func
:
softmax_csr_grad{sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
sparse_coo_tensor_grad
-
backward_
op
:
sparse_coo_tensor_grad
forward
:
sparse_coo_tensor(Tensor values, Tensor indices, IntArray dense_shape) -> Tensor(out)
args
:
(Tensor indices, Tensor out_grad)
output
:
Tensor(values_grad)
kernel
:
func
:
sparse_coo_tensor_grad{dense, sparse_coo -> dense}
-
backward_
api
:
sqrt_grad
-
backward_
op
:
sqrt_grad
forward
:
sqrt(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -234,7 +234,7 @@
func
:
sqrt_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
sqrt_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
square_grad
-
backward_
op
:
square_grad
forward
:
square(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -242,7 +242,7 @@
func
:
square_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
square_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
subtract_grad
-
backward_
op
:
subtract_grad
forward
:
subtract(Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
...
...
@@ -250,7 +250,7 @@
func
:
subtract_coo_coo_grad{sparse_coo, sparse_coo, sparse_coo -> sparse_coo, sparse_coo},
subtract_csr_csr_grad{sparse_csr, sparse_csr, sparse_csr -> sparse_csr, sparse_csr}
-
backward_
api
:
tan_grad
-
backward_
op
:
tan_grad
forward
:
tan(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -258,7 +258,7 @@
func
:
tan_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tan_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
tanh_grad
-
backward_
op
:
tanh_grad
forward
:
tanh(Tensor x) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
...
...
@@ -266,28 +266,28 @@
func
:
tanh_coo_grad {sparse_coo, sparse_coo -> sparse_coo},
tanh_csr_grad {sparse_csr, sparse_csr -> sparse_csr}
-
backward_
api
:
to_dense_grad
-
backward_
op
:
to_dense_grad
forward
:
to_dense(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
kernel
:
func
:
coo_to_dense_grad{sparse_coo, dense -> sparse_coo}
-
backward_
api
:
to_sparse_coo_grad
-
backward_
op
:
to_sparse_coo_grad
forward
:
to_sparse_coo(Tensor x, int64_t sparse_dim) -> Tensor(out)
args
:
(Tensor out_grad)
output
:
Tensor(x_grad)
kernel
:
func
:
coo_to_dense { sparse_coo -> dense }
-
backward_
api
:
values_grad
-
backward_
op
:
values_grad
forward
:
values_coo(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
kernel
:
func
:
values_coo_grad{sparse_coo, dense-> sparse_coo}
-
backward_
api
:
fused_attention_grad
-
backward_
op
:
fused_attention_grad
forward
:
fused_attention_csr(Tensor query, Tensor key, Tensor value, Tensor sparse_mask, Tensor key_padding_mask, Tensor attn_mask) -> Tensor(out), Tensor(softmax)
args
:
(Tensor query, Tensor key, Tensor value, Tensor softmax, Tensor out_grad)
output
:
Tensor(query_grad), Tensor(key_grad), Tensor(value_grad)
...
...
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