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体验新版 GitCode,发现更多精彩内容 >>
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17fb92b3
编写于
10月 28, 2022
作者:
Z
zyfncg
提交者:
GitHub
10月 28, 2022
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电子邮件补丁
差异文件
generate static graph code for some ops by yaml (#47416)
上级
e77c062e
变更
17
隐藏空白更改
内联
并排
Showing
17 changed file
with
110 addition
and
637 deletion
+110
-637
paddle/fluid/operators/angle_op.cc
paddle/fluid/operators/angle_op.cc
+0
-94
paddle/fluid/operators/argsort_op.cc
paddle/fluid/operators/argsort_op.cc
+0
-115
paddle/fluid/operators/bmm_op.cc
paddle/fluid/operators/bmm_op.cc
+0
-103
paddle/fluid/operators/bmm_op.h
paddle/fluid/operators/bmm_op.h
+0
-63
paddle/fluid/operators/determinant_op.cc
paddle/fluid/operators/determinant_op.cc
+0
-67
paddle/phi/api/yaml/backward.yaml
paddle/phi/api/yaml/backward.yaml
+43
-0
paddle/phi/api/yaml/generator/templates/operator_utils.c.j2
paddle/phi/api/yaml/generator/templates/operator_utils.c.j2
+1
-1
paddle/phi/api/yaml/legacy_backward.yaml
paddle/phi/api/yaml/legacy_backward.yaml
+0
-43
paddle/phi/api/yaml/legacy_ops.yaml
paddle/phi/api/yaml/legacy_ops.yaml
+0
-36
paddle/phi/api/yaml/op_compat.yaml
paddle/phi/api/yaml/op_compat.yaml
+24
-0
paddle/phi/api/yaml/ops.yaml
paddle/phi/api/yaml/ops.yaml
+36
-0
paddle/phi/kernels/cpu/angle_grad_kernel.cc
paddle/phi/kernels/cpu/angle_grad_kernel.cc
+3
-1
paddle/phi/kernels/gpu/angle_grad_kernel.cu
paddle/phi/kernels/gpu/angle_grad_kernel.cu
+3
-1
paddle/phi/ops/compat/angle_sig.cc
paddle/phi/ops/compat/angle_sig.cc
+0
-30
paddle/phi/ops/compat/argsort_sig.cc
paddle/phi/ops/compat/argsort_sig.cc
+0
-29
paddle/phi/ops/compat/bmm_sig.cc
paddle/phi/ops/compat/bmm_sig.cc
+0
-26
paddle/phi/ops/compat/determinant_sig.cc
paddle/phi/ops/compat/determinant_sig.cc
+0
-28
未找到文件。
paddle/fluid/operators/angle_op.cc
已删除
100644 → 0
浏览文件 @
e77c062e
// Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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 <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/backward.h"
#include "paddle/phi/infermeta/unary.h"
namespace
paddle
{
namespace
operators
{
class
AngleOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
};
class
AngleOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor), The input tensor of angle op."
);
AddOutput
(
"Out"
,
"(Tensor), The output tensor of angle op."
);
AddComment
(
R"DOC(
Angle Operator.
This operator is used to perform elementwise angle for input $X$.
$$out = angle(x)$$
)DOC"
);
}
};
class
AngleGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
dtype
=
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
"X"
);
return
framework
::
OpKernelType
(
dtype
,
ctx
.
GetPlace
());
}
};
template
<
typename
T
>
class
AngleGradMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
void
Apply
(
GradOpPtr
<
T
>
retv
)
const
override
{
retv
->
SetType
(
"angle_grad"
);
retv
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
retv
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
retv
->
SetAttrMap
(
this
->
Attrs
());
retv
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
this
->
InputGrad
(
"X"
));
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
angle
,
AngleInferShapeFunctor
,
PD_INFER_META
(
phi
::
RealAndImagInferMeta
));
DECLARE_INFER_SHAPE_FUNCTOR
(
angle_grad
,
AngleGradInferShapeFunctor
,
PD_INFER_META
(
phi
::
AngleGradInferMeta
));
REGISTER_OPERATOR
(
angle
,
ops
::
AngleOp
,
ops
::
AngleOpMaker
,
ops
::
AngleGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
AngleGradMaker
<
paddle
::
imperative
::
OpBase
>
,
AngleInferShapeFunctor
);
REGISTER_OPERATOR
(
angle_grad
,
ops
::
AngleGradOp
,
AngleGradInferShapeFunctor
);
paddle/fluid/operators/argsort_op.cc
已删除
100644 → 0
浏览文件 @
e77c062e
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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 <memory>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/unary.h"
namespace
paddle
{
namespace
operators
{
class
ArgsortOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
};
class
ArgsortGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
ctx
->
ShareLoD
(
"X"
,
/*-->*/
framework
::
GradVarName
(
"X"
));
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
framework
::
GradVarName
(
"Out"
)),
ctx
.
device_context
());
}
};
class
ArgsortOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor) The input of Argsort op."
);
AddOutput
(
"Out"
,
"(Tensor) The sorted tensor of Argsort op, with the same "
"shape as Input(X)."
);
AddOutput
(
"Indices"
,
"(Tensor) The indices of a tensor giving the sorted order, with "
"the same shape as Input(X)."
);
AddComment
(
R"DOC(
Argsort operator
Performs sorting on the input tensor along the given axis and outputs two
tensors, Output(Out) and Output(Indices). They reserve the same shape
with Input(X), and Output(Out) represents the sorted tensor while
Output(Indices) gives the sorted order along the given axis Attr(axis).
)DOC"
);
AddAttr
<
int
>
(
"axis"
,
"(int, default -1) The axis along which to sort the tensor. "
"When axis < 0, the actual axis will be the |axis|'th "
"counting backwards. Default -1, the last dimension."
)
.
SetDefault
(
-
1
);
AddAttr
<
bool
>
(
"descending"
,
"(bool, default false) The descending attribute is a flag to tell"
"algorithm how to sort the input data."
"If descending is true, will sort by descending order,"
"else if false, sort by ascending order. Default value is false."
)
.
SetDefault
(
false
);
}
};
template
<
typename
T
>
class
ArgsortGradOpMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
op
)
const
override
{
op
->
SetType
(
"argsort_grad"
);
op
->
SetInput
(
"Indices"
,
this
->
Output
(
"Indices"
));
op
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
this
->
InputGrad
(
"X"
));
op
->
SetAttrMap
(
this
->
Attrs
());
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERER
(
ArgsortGradNoNeedBufferVarsInferer
,
"X"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
argsort
,
ArgsortInferShapeFunctor
,
PD_INFER_META
(
phi
::
ArgsortInferMeta
));
REGISTER_OPERATOR
(
argsort
,
ops
::
ArgsortOp
,
ops
::
ArgsortOpMaker
,
ops
::
ArgsortGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
ArgsortGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
ArgsortInferShapeFunctor
);
REGISTER_OPERATOR
(
argsort_grad
,
ops
::
ArgsortGradOp
,
ops
::
ArgsortGradNoNeedBufferVarsInferer
);
paddle/fluid/operators/bmm_op.cc
已删除
100644 → 0
浏览文件 @
e77c062e
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* 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/operators/bmm_op.h"
#include <vector>
#include "paddle/fluid/framework/infershape_utils.h"
#include "paddle/phi/core/infermeta_utils.h"
#include "paddle/phi/infermeta/backward.h"
#include "paddle/phi/infermeta/binary.h"
namespace
paddle
{
namespace
operators
{
class
BmmOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
data_type
=
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
"X"
);
return
framework
::
OpKernelType
(
data_type
,
ctx
.
device_context
());
}
};
class
BmmOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor), The first input tensor of Bmm op."
);
AddInput
(
"Y"
,
"(Tensor), The second input tensor of Bmm op."
);
AddOutput
(
"Out"
,
"(Tensor), The output tensor of Bmm op."
);
AddComment
(
R"DOC(
The Bmm operator is used to perform batched matrix multiplication
over the last two dimensions of the input tensors `X` and `Y`
which are both 3-dimentionsal.
Examples:
- X: [B, M, K], Y: [B, K, N] => Out: [B, M, N]
)DOC"
);
}
};
class
BmmOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
framework
::
GradVarName
(
"Out"
)),
ctx
.
device_context
());
}
};
template
<
typename
T
>
class
BmmOpGradMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
retv
)
const
override
{
retv
->
SetType
(
"bmm_grad"
);
retv
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
retv
->
SetInput
(
"Y"
,
this
->
Input
(
"Y"
));
retv
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
retv
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
this
->
InputGrad
(
"X"
));
retv
->
SetOutput
(
framework
::
GradVarName
(
"Y"
),
this
->
InputGrad
(
"Y"
));
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
bmm
,
BmmInferShapeFunctor
,
PD_INFER_META
(
phi
::
BmmInferMeta
));
DECLARE_INFER_SHAPE_FUNCTOR
(
bmm_grad
,
BmmGradInferShapeFunctor
,
PD_INFER_META
(
phi
::
BmmGradInferMeta
));
REGISTER_OPERATOR
(
bmm
,
ops
::
BmmOp
,
ops
::
BmmOpMaker
,
ops
::
BmmOpGradMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
BmmOpGradMaker
<
paddle
::
imperative
::
OpBase
>
,
BmmInferShapeFunctor
);
REGISTER_OPERATOR
(
bmm_grad
,
ops
::
BmmOpGrad
,
BmmGradInferShapeFunctor
);
paddle/fluid/operators/bmm_op.h
已删除
100644 → 0
浏览文件 @
e77c062e
/* Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* 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. */
#ifndef PADDLE_FLUID_OPERATORS_BMM_OP_H_
#define PADDLE_FLUID_OPERATORS_BMM_OP_H_
#include <algorithm>
#include <utility>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/operator.h"
#include "paddle/phi/kernels/funcs/blas/blas.h"
#include "paddle/phi/kernels/funcs/math_function.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
phi
::
DenseTensor
;
static
void
ReshapeTensorIntoMatrixSequence
(
phi
::
DenseTensor
*
x
,
const
phi
::
funcs
::
MatDescriptor
&
descriptor
)
{
int64_t
h
,
w
;
h
=
descriptor
.
height_
;
w
=
descriptor
.
width_
;
if
(
descriptor
.
trans_
)
{
std
::
swap
(
w
,
h
);
}
x
->
Resize
({
descriptor
.
batch_size_
,
h
,
w
});
}
static
void
ReshapeXYOutIntoMatrixSequence
(
phi
::
DenseTensor
*
x
,
phi
::
DenseTensor
*
y
,
phi
::
DenseTensor
*
out
,
bool
trans_x
,
bool
trans_y
)
{
auto
x_dim
=
x
->
dims
();
auto
y_dim
=
y
->
dims
();
auto
mat_dim_x
=
phi
::
funcs
::
CreateMatrixDescriptor
(
x_dim
,
0
,
false
);
auto
mat_dim_y
=
phi
::
funcs
::
CreateMatrixDescriptor
(
y_dim
,
0
,
false
);
out
->
Resize
({
std
::
max
(
mat_dim_x
.
batch_size_
,
mat_dim_y
.
batch_size_
),
mat_dim_x
.
height_
,
mat_dim_y
.
width_
});
ReshapeTensorIntoMatrixSequence
(
x
,
mat_dim_x
);
ReshapeTensorIntoMatrixSequence
(
y
,
mat_dim_y
);
}
}
// namespace operators
}
// namespace paddle
#endif // PADDLE_FLUID_OPERATORS_BMM_OP_H_
paddle/fluid/operators/determinant_op.cc
浏览文件 @
17fb92b3
...
...
@@ -23,57 +23,6 @@
namespace
paddle
{
namespace
operators
{
class
DeterminantOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
};
class
DeterminantOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"Input"
,
"(Tensor) The input tensor of determinant."
);
AddOutput
(
"Out"
,
"(Tensor) The output Tensor containing the determinant"
"value of a square matrix or batches of square matrices "
);
AddComment
(
R"DOC(
Determinant Operator.)DOC"
);
}
};
class
DeterminantGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
framework
::
GradVarName
(
"Out"
)),
ctx
.
GetPlace
());
}
};
template
<
typename
T
>
class
DeterminantGradOpMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
grad_op
)
const
override
{
grad_op
->
SetType
(
"determinant_grad"
);
grad_op
->
SetInput
(
"Input"
,
this
->
Input
(
"Input"
));
grad_op
->
SetInput
(
"Out"
,
this
->
Output
(
"Out"
));
grad_op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
this
->
OutputGrad
(
"Out"
));
grad_op
->
SetOutput
(
framework
::
GradVarName
(
"Input"
),
this
->
InputGrad
(
"Input"
));
grad_op
->
SetAttrMap
(
this
->
Attrs
());
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERER
(
DeterminantGradNoNeedBufferVarsInferer
,
"Input"
);
class
SlogDeterminantOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
...
...
@@ -154,22 +103,6 @@ DECLARE_NO_NEED_BUFFER_VARS_INFERER(SlogDeterminantGradNoNeedBufferVarsInferer,
namespace
ops
=
paddle
::
operators
;
namespace
plat
=
paddle
::
platform
;
DECLARE_INFER_SHAPE_FUNCTOR
(
determinant
,
DeterminantInferShapeFunctor
,
PD_INFER_META
(
phi
::
UnchangedInferMeta
));
REGISTER_OPERATOR
(
determinant
,
ops
::
DeterminantOp
,
ops
::
DeterminantOpMaker
,
ops
::
DeterminantGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
DeterminantGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
DeterminantInferShapeFunctor
);
DECLARE_INFER_SHAPE_FUNCTOR
(
determinant_grad
,
DeterminantGradInferShapeFunctor
,
PD_INFER_META
(
phi
::
GeneralUnaryGradInferMeta
));
REGISTER_OPERATOR
(
determinant_grad
,
ops
::
DeterminantGradOp
,
DeterminantGradInferShapeFunctor
);
DECLARE_INFER_SHAPE_FUNCTOR
(
slogdeterminant
,
SlogDeterminantInferShapeFunctor
,
...
...
paddle/phi/api/yaml/backward.yaml
浏览文件 @
17fb92b3
...
...
@@ -20,6 +20,28 @@
func
:
acosh_grad
inplace
:
(out_grad -> x_grad)
-
backward_op
:
angle_grad
forward
:
angle (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
angle_grad
-
backward_op
:
argsort_grad
forward
:
argsort (Tensor x, int axis, bool descending) -> Tensor(out), Tensor(indices)
args
:
(Tensor indices, Tensor x, Tensor out_grad, int axis, bool descending)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
argsort_grad
data_type
:
out_grad
no_need_buffer
:
x
-
backward_op
:
asin_grad
forward
:
asin (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
...
...
@@ -74,6 +96,16 @@
func
:
atanh_grad
inplace
:
(out_grad -> x_grad)
-
backward_op
:
bmm_grad
forward
:
bmm (Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
BmmGradInferMeta
kernel
:
func
:
bmm_grad
data_type
:
out_grad
-
backward_op
:
cholesky_grad
forward
:
cholesky (Tensor x, bool upper) -> Tensor(out)
args
:
(Tensor out, Tensor out_grad, bool upper)
...
...
@@ -127,6 +159,17 @@
func
:
cross_grad
data_type
:
out_grad
-
backward_op
:
det_grad
forward
:
det (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
determinant_grad
data_type
:
out_grad
-
backward_op
:
diag_grad
forward
:
diag (Tensor x, int offset, float padding_value) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, int offset)
...
...
paddle/phi/api/yaml/generator/templates/operator_utils.c.j2
浏览文件 @
17fb92b3
...
...
@@ -109,7 +109,7 @@ KernelSignature {{api["op_name"] | to_pascal_case }}OpArgumentMapping(const Argu
{% endfor %}
{{get_output_list(api["outputs"], kernel_args)}};
{% if api["kernel"]["func"] | length == 1 %}
KernelSignature sig("{{api["
name"
]}}", std::move(inputs), std::move(attrs), std::move(outputs));
KernelSignature sig("{{api["
kernel"]["func"][0
]}}", std::move(inputs), std::move(attrs), std::move(outputs));
return sig;
{% else %}{# it has kernel for selected rows #}
const char* kernel_name = ctx.IsSelectedRowsInput({{kernel_args[0] | to_opmaker_name_cstr}}) ? "{{api["kernel"]["func"][1]}}" : "{{api["kernel"]["func"][0]}}";
...
...
paddle/phi/api/yaml/legacy_backward.yaml
浏览文件 @
17fb92b3
...
...
@@ -100,30 +100,6 @@
kernel
:
func
:
amin_grad
-
backward_op
:
angle_grad
forward
:
angle (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
angle_grad
data_transform
:
skip_transform
:
out_grad
-
backward_op
:
argsort_grad
forward
:
argsort (Tensor x, int axis, bool descending) -> Tensor(out), Tensor(indices)
args
:
(Tensor indices, Tensor x, Tensor out_grad, int axis, bool descending)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
argsort_grad
data_type
:
out_grad
no_need_buffer
:
x
-
backward_op
:
as_complex_grad
forward
:
as_complex (Tensor x) -> Tensor(out)
args
:
(Tensor out_grad)
...
...
@@ -222,15 +198,6 @@
kernel
:
func
:
bilinear_tensor_product_grad
-
backward_op
:
bmm_grad
forward
:
bmm (Tensor x, Tensor y) -> Tensor(out)
args
:
(Tensor x, Tensor y, Tensor out_grad)
output
:
Tensor(x_grad), Tensor(y_grad)
infer_meta
:
func
:
BmmGradInferMeta
kernel
:
func
:
bmm_grad
-
backward_op
:
brelu_grad
forward
:
brelu (Tensor x, float t_min, float t_max) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad, float t_min, float t_max)
...
...
@@ -515,16 +482,6 @@
kernel
:
func
:
depthwise_conv2d_transpose_grad
-
backward_op
:
det_grad
forward
:
det (Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
determinant_grad
-
backward_op
:
divide_double_grad
forward
:
divide_grad (Tensor x, Tensor y, Tensor out, Tensor grad_out, int axis = -1) -> Tensor(grad_x), Tensor(grad_y)
args
:
(Tensor y, Tensor out, Tensor grad_x, Tensor grad_x_grad, Tensor grad_y_grad, int axis = -1)
...
...
paddle/phi/api/yaml/legacy_ops.yaml
浏览文件 @
17fb92b3
...
...
@@ -144,15 +144,6 @@
func
:
amin
backward
:
amin_grad
-
op
:
angle
args
:
(Tensor x)
output
:
Tensor
infer_meta
:
func
:
RealAndImagInferMeta
kernel
:
func
:
angle
backward
:
angle_grad
-
op
:
any
args
:
(Tensor x, int64_t[] axis={}, bool keepdim=false)
output
:
Tensor(out)
...
...
@@ -191,15 +182,6 @@
kernel
:
func
:
arg_min
-
op
:
argsort
args
:
(Tensor x, int axis=-1, bool descending=false)
output
:
Tensor(out), Tensor(indices)
infer_meta
:
func
:
ArgsortInferMeta
kernel
:
func
:
argsort
backward
:
argsort_grad
-
op
:
as_complex
args
:
(Tensor x)
output
:
Tensor
...
...
@@ -355,15 +337,6 @@
kernel
:
func
:
bitwise_xor
-
op
:
bmm
args
:
(Tensor x, Tensor y)
output
:
Tensor
infer_meta
:
func
:
BmmInferMeta
kernel
:
func
:
bmm
backward
:
bmm_grad
-
op
:
box_coder
args
:
(Tensor prior_box, Tensor prior_box_var, Tensor target_box, str code_type, bool box_normalized, int axis, float[] variance)
output
:
Tensor(output_box)
...
...
@@ -618,15 +591,6 @@
func
:
depthwise_conv2d_transpose
backward
:
depthwise_conv2d_transpose_grad
-
op
:
det
args
:
(Tensor x)
output
:
Tensor
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
determinant
backward
:
det_grad
-
op
:
diag_embed
args
:
(Tensor input, int offset, int dim1, int dim2)
output
:
Tensor(out)
...
...
paddle/phi/api/yaml/op_compat.yaml
浏览文件 @
17fb92b3
...
...
@@ -41,9 +41,20 @@
-
op
:
angle
backward
:
angle_grad
inputs
:
x
:
X
outputs
:
out
:
Out
extra
:
attrs
:
[
bool use_mkldnn = false
]
-
op
:
argsort
inputs
:
x
:
X
outputs
:
out
:
Out
indices
:
Indices
-
op
:
asin
inputs
:
x
:
X
...
...
@@ -101,6 +112,12 @@
extra
:
attrs
:
[
bool use_mkldnn = false
]
-
op
:
bmm
inputs
:
{
x
:
X
,
y
:
Y
}
outputs
:
out
:
Out
-
op
:
ceil
backward
:
ceil_grad
extra
:
...
...
@@ -226,6 +243,13 @@
extra
:
attrs
:
[
float moving_rate = 0.9
]
-
op
:
det (determinant)
backward
:
det_grad (determinant_grad)
inputs
:
x
:
Input
outputs
:
out
:
Out
-
op
:
diag (diag_v2)
backward
:
diag_grad (diag_v2_grad)
inputs
:
...
...
paddle/phi/api/yaml/ops.yaml
浏览文件 @
17fb92b3
...
...
@@ -16,6 +16,24 @@
func
:
acosh
backward
:
acosh_grad
-
op
:
angle
args
:
(Tensor x)
output
:
Tensor
infer_meta
:
func
:
RealAndImagInferMeta
kernel
:
func
:
angle
backward
:
angle_grad
-
op
:
argsort
args
:
(Tensor x, int axis=-1, bool descending=false)
output
:
Tensor(out), Tensor(indices)
infer_meta
:
func
:
ArgsortInferMeta
kernel
:
func
:
argsort
backward
:
argsort_grad
-
op
:
asin
args
:
(Tensor x)
output
:
Tensor
...
...
@@ -69,6 +87,15 @@
kernel
:
func
:
bernoulli
-
op
:
bmm
args
:
(Tensor x, Tensor y)
output
:
Tensor
infer_meta
:
func
:
BmmInferMeta
kernel
:
func
:
bmm
backward
:
bmm_grad
-
op
:
cholesky
args
:
(Tensor x, bool upper=false)
output
:
Tensor
...
...
@@ -115,6 +142,15 @@
data_type
:
x
backward
:
cross_grad
-
op
:
det
args
:
(Tensor x)
output
:
Tensor
infer_meta
:
func
:
UnchangedInferMeta
kernel
:
func
:
determinant
backward
:
det_grad
-
op
:
diag
args
:
(Tensor x, int offset = 0, float padding_value = 0.0)
output
:
Tensor
...
...
paddle/phi/kernels/cpu/angle_grad_kernel.cc
浏览文件 @
17fb92b3
...
...
@@ -25,4 +25,6 @@ PD_REGISTER_KERNEL(angle_grad,
float
,
double
,
phi
::
dtype
::
complex
<
float
>
,
phi
::
dtype
::
complex
<
double
>
)
{}
phi
::
dtype
::
complex
<
double
>
)
{
kernel
->
InputAt
(
1
).
SetDataType
(
phi
::
dtype
::
ToReal
(
kernel_key
.
dtype
()));
}
paddle/phi/kernels/gpu/angle_grad_kernel.cu
浏览文件 @
17fb92b3
...
...
@@ -25,4 +25,6 @@ PD_REGISTER_KERNEL(angle_grad,
float
,
double
,
phi
::
dtype
::
complex
<
float
>
,
phi
::
dtype
::
complex
<
double
>
)
{}
phi
::
dtype
::
complex
<
double
>
)
{
kernel
->
InputAt
(
1
).
SetDataType
(
phi
::
dtype
::
ToReal
(
kernel_key
.
dtype
()));
}
paddle/phi/ops/compat/angle_sig.cc
已删除
100644 → 0
浏览文件 @
e77c062e
/* Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
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/phi/core/compat/op_utils.h"
namespace
phi
{
KernelSignature
AngleOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"angle"
,
{
"X"
},
{},
{
"Out"
});
}
KernelSignature
AngleGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"angle_grad"
,
{
"X"
,
"Out@GRAD"
},
{},
{
"X@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
angle
,
phi
::
AngleOpArgumentMapping
);
PD_REGISTER_ARG_MAPPING_FN
(
angle_grad
,
phi
::
AngleGradOpArgumentMapping
);
paddle/phi/ops/compat/argsort_sig.cc
已删除
100644 → 0
浏览文件 @
e77c062e
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/phi/core/compat/op_utils.h"
namespace
phi
{
KernelSignature
ArgsortGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"argsort_grad"
,
{
"Indices"
,
"X"
,
"Out@GRAD"
},
{
"axis"
,
"descending"
},
{
"X@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
argsort_grad
,
phi
::
ArgsortGradOpArgumentMapping
);
paddle/phi/ops/compat/bmm_sig.cc
已删除
100644 → 0
浏览文件 @
e77c062e
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/phi/core/compat/op_utils.h"
namespace
phi
{
KernelSignature
BmmGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"bmm_grad"
,
{
"X"
,
"Y"
,
"Out@GRAD"
},
{},
{
"X@GRAD"
,
"Y@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
bmm_grad
,
phi
::
BmmGradOpArgumentMapping
);
paddle/phi/ops/compat/determinant_sig.cc
已删除
100644 → 0
浏览文件 @
e77c062e
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// 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/phi/core/compat/op_utils.h"
namespace
phi
{
KernelSignature
DeterminantGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"determinant_grad"
,
{
"Input"
,
"Out"
,
"Out@GRAD"
},
{},
{
"Input@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
determinant_grad
,
phi
::
DeterminantGradOpArgumentMapping
);
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