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体验新版 GitCode,发现更多精彩内容 >>
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提交
3e170163
编写于
7月 25, 2022
作者:
L
lyq
提交者:
GitHub
7月 25, 2022
浏览文件
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差异文件
[Phi] Migrate squared_l2_norm_op to phi (#44492)
上级
c0a29d2f
变更
24
隐藏空白更改
内联
并排
Showing
24 changed file
with
340 addition
and
160 deletion
+340
-160
paddle/fluid/framework/new_executor/standalone_executor_test.cc
.../fluid/framework/new_executor/standalone_executor_test.cc
+2
-1
paddle/fluid/operators/inplace_abn_op.cu
paddle/fluid/operators/inplace_abn_op.cu
+0
-1
paddle/fluid/operators/optimizers/lamb_op.h
paddle/fluid/operators/optimizers/lamb_op.h
+9
-8
paddle/fluid/operators/squared_l2_norm_op.cc
paddle/fluid/operators/squared_l2_norm_op.cc
+19
-32
paddle/fluid/operators/squared_l2_norm_op.cu
paddle/fluid/operators/squared_l2_norm_op.cu
+0
-24
paddle/fluid/operators/squared_l2_norm_op.h
paddle/fluid/operators/squared_l2_norm_op.h
+0
-71
paddle/fluid/operators/squared_l2_norm_op_mlu.cc
paddle/fluid/operators/squared_l2_norm_op_mlu.cc
+0
-1
paddle/fluid/operators/squared_l2_norm_op_npu.cc
paddle/fluid/operators/squared_l2_norm_op_npu.cc
+1
-1
paddle/phi/api/yaml/legacy_api.yaml
paddle/phi/api/yaml/legacy_api.yaml
+9
-0
paddle/phi/api/yaml/legacy_backward.yaml
paddle/phi/api/yaml/legacy_backward.yaml
+10
-0
paddle/phi/infermeta/unary.cc
paddle/phi/infermeta/unary.cc
+4
-0
paddle/phi/infermeta/unary.h
paddle/phi/infermeta/unary.h
+2
-0
paddle/phi/kernels/cpu/squared_l2_norm_grad_kernel.cc
paddle/phi/kernels/cpu/squared_l2_norm_grad_kernel.cc
+26
-0
paddle/phi/kernels/cpu/squared_l2_norm_kernel.cc
paddle/phi/kernels/cpu/squared_l2_norm_kernel.cc
+23
-0
paddle/phi/kernels/funcs/squared_l2_norm.h
paddle/phi/kernels/funcs/squared_l2_norm.h
+15
-18
paddle/phi/kernels/gpu/squared_l2_norm_grad_kernel.cu
paddle/phi/kernels/gpu/squared_l2_norm_grad_kernel.cu
+26
-0
paddle/phi/kernels/gpu/squared_l2_norm_kernel.cu
paddle/phi/kernels/gpu/squared_l2_norm_kernel.cu
+23
-0
paddle/phi/kernels/impl/squared_l2_norm_grad_kernel_impl.h
paddle/phi/kernels/impl/squared_l2_norm_grad_kernel_impl.h
+41
-0
paddle/phi/kernels/impl/squared_l2_norm_kernel_impl.h
paddle/phi/kernels/impl/squared_l2_norm_kernel_impl.h
+32
-0
paddle/phi/kernels/squared_l2_norm_grad_kernel.h
paddle/phi/kernels/squared_l2_norm_grad_kernel.h
+26
-0
paddle/phi/kernels/squared_l2_norm_kernel.h
paddle/phi/kernels/squared_l2_norm_kernel.h
+25
-0
paddle/phi/ops/compat/squared_l2_norm_sig.cc
paddle/phi/ops/compat/squared_l2_norm_sig.cc
+35
-0
python/paddle/fluid/clip.py
python/paddle/fluid/clip.py
+2
-2
python/paddle/fluid/tests/unittests/test_squared_l2_norm_op.py
...n/paddle/fluid/tests/unittests/test_squared_l2_norm_op.py
+10
-1
未找到文件。
paddle/fluid/framework/new_executor/standalone_executor_test.cc
浏览文件 @
3e170163
...
...
@@ -57,7 +57,7 @@ USE_OP_ITSELF(sqrt);
USE_OP_ITSELF
(
elementwise_max
);
USE_OP_ITSELF
(
elementwise_div
);
USE_OP_ITSELF
(
sgd
);
USE_OP
(
squared_l2_norm
);
USE_OP
_ITSELF
(
squared_l2_norm
);
USE_OP_ITSELF
(
memcpy_h2d
);
USE_OP_ITSELF
(
memcpy_d2h
);
USE_OP_ITSELF
(
fetch_v2
);
...
...
@@ -87,6 +87,7 @@ PD_DECLARE_KERNEL(mean, GPU, ALL_LAYOUT);
PD_DECLARE_KERNEL
(
mean_grad
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
sigmoid
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
sigmoid_grad
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
squared_l2_norm
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
reshape_grad
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
add_grad
,
GPU
,
ALL_LAYOUT
);
PD_DECLARE_KERNEL
(
matmul_grad
,
GPU
,
ALL_LAYOUT
);
...
...
paddle/fluid/operators/inplace_abn_op.cu
浏览文件 @
3e170163
...
...
@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/inplace_abn_op.h"
#include <iostream>
#include "paddle/fluid/operators/batch_norm_op.h"
#include "paddle/phi/kernels/batch_norm_grad_kernel.h"
#include "paddle/phi/kernels/batch_norm_kernel.h"
...
...
paddle/fluid/operators/optimizers/lamb_op.h
浏览文件 @
3e170163
...
...
@@ -22,11 +22,11 @@ limitations under the License. */
#include "paddle/fluid/memory/buffer.h"
#include "paddle/fluid/operators/amp/fp16_type_traits.h"
#include "paddle/fluid/operators/math/selected_rows_functor.h"
#include "paddle/fluid/operators/math/squared_l2_norm.h"
#include "paddle/fluid/operators/tensor_to_string.h"
#include "paddle/fluid/platform/for_range.h"
#include "paddle/phi/kernels/funcs/algorithm.h"
#include "paddle/phi/kernels/funcs/eigen/extensions.h"
#include "paddle/phi/kernels/funcs/squared_l2_norm.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -756,13 +756,14 @@ class LambOpKernel : public framework::OpKernel<T> {
// TODO(zengjinle): remove the following Eigen operations when
// *skip_update == true.
memory
::
Buffer
buffer
(
dev_ctx
.
GetPlace
());
math
::
SquaredL2Norm
(
dev_ctx
,
reinterpret_cast
<
const
MT
*>
(
IsMultiPrecision
?
master_param_ptr
:
param_ptr
),
p_norm_ptr
,
numel
,
&
buffer
);
math
::
SquaredL2Norm
(
phi
::
funcs
::
SquaredL2Norm
(
dev_ctx
,
reinterpret_cast
<
const
MT
*>
(
IsMultiPrecision
?
master_param_ptr
:
param_ptr
),
p_norm_ptr
,
numel
,
&
buffer
);
phi
::
funcs
::
SquaredL2Norm
(
dev_ctx
,
trust_ratio_div_ptr
,
trust_ratio_div_norm_ptr
,
numel
,
&
buffer
);
if
(
VLOG_IS_ON
(
1
))
{
...
...
paddle/fluid/operators/squared_l2_norm_op.cc
浏览文件 @
3e170163
...
...
@@ -12,9 +12,10 @@ 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/squared_l2_norm_op.h"
#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
{
...
...
@@ -24,13 +25,6 @@ using framework::Tensor;
class
SquaredL2NormOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"SquaredL2NormOp"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Out"
),
"Output"
,
"Out"
,
"SquaredL2NormOp"
);
ctx
->
SetOutputDim
(
"Out"
,
{
1
});
}
};
template
<
typename
T
>
...
...
@@ -54,20 +48,6 @@ class SquaredL2NormGradOpMaker : public framework::SingleGradOpMaker<T> {
class
SquaredL2NormGradOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"X"
,
"SquaredL2NormGradOp"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input"
,
"Out@GRAD"
,
"SquaredL2NormGradOp"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)),
"Output"
,
"X@GRAD"
,
"SquaredL2NormGradOp"
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
}
};
class
SquaredL2NormOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -90,15 +70,22 @@ $$Out = \sum_{i} X_{i}^2$$
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
DECLARE_INFER_SHAPE_FUNCTOR
(
squared_l2_norm
,
SquaredL2NormInferShapeFunctor
,
PD_INFER_META
(
phi
::
SquaredL2NormInferMeta
));
DECLARE_INFER_SHAPE_FUNCTOR
(
squared_l2_norm_grad
,
SquaredL2NormGradInferShapeFunctor
,
PD_INFER_META
(
phi
::
UnchangedInferMeta
));
REGISTER_OPERATOR
(
squared_l2_norm
,
ops
::
SquaredL2NormOp
,
ops
::
SquaredL2NormOpMaker
,
ops
::
SquaredL2NormGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
SquaredL2NormGradOpMaker
<
paddle
::
imperative
::
OpBase
>
);
REGISTER_OPERATOR
(
squared_l2_norm_grad
,
ops
::
SquaredL2NormGradOp
);
REGISTER_OP_CPU_KERNEL
(
squared_l2_norm
,
ops
::
SquaredL2NormKernel
<
phi
::
CPUContext
,
float
>
,
ops
::
SquaredL2NormKernel
<
phi
::
CPUContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
squared_l2_norm_grad
,
ops
::
SquaredL2NormGradKernel
<
phi
::
CPUContext
,
float
>
,
ops
::
SquaredL2NormGradKernel
<
phi
::
CPUContext
,
double
>
);
ops
::
SquaredL2NormGradOpMaker
<
paddle
::
imperative
::
OpBase
>
,
SquaredL2NormInferShapeFunctor
);
REGISTER_OPERATOR
(
squared_l2_norm_grad
,
ops
::
SquaredL2NormGradOp
,
SquaredL2NormGradInferShapeFunctor
);
paddle/fluid/operators/squared_l2_norm_op.cu
已删除
100644 → 0
浏览文件 @
c0a29d2f
/* 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 "paddle/fluid/operators/squared_l2_norm_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
squared_l2_norm
,
ops
::
SquaredL2NormKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
SquaredL2NormKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
squared_l2_norm_grad
,
ops
::
SquaredL2NormGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
SquaredL2NormGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
paddle/fluid/operators/squared_l2_norm_op.h
已删除
100644 → 0
浏览文件 @
c0a29d2f
/* 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. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/squared_l2_norm.h"
namespace
paddle
{
namespace
operators
{
// Out = sum(square(X))
template
<
typename
DeviceContext
,
typename
T
>
class
SquaredL2NormKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
framework
::
Tensor
*
x
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
const
auto
*
x_ptr
=
x
->
data
<
T
>
();
auto
numel
=
x
->
numel
();
framework
::
Tensor
*
out
=
context
.
Output
<
framework
::
Tensor
>
(
"Out"
);
auto
*
out_ptr
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
math
::
SquaredL2Norm
(
context
.
template
device_context
<
DeviceContext
>(),
x_ptr
,
out_ptr
,
numel
);
}
};
// dX = X
template
<
typename
DeviceContext
,
typename
T
>
class
SquaredL2NormGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
framework
::
Tensor
*
X
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
const
framework
::
Tensor
*
dOut
=
context
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
PADDLE_ENFORCE_EQ
(
dOut
->
numel
(),
1
,
platform
::
errors
::
InvalidArgument
(
"Input(GRAD@Out) of SquaredL2NormGradOP should be a scalar."
));
framework
::
Tensor
*
dX
=
context
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
dX
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
X
);
auto
dout
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dOut
);
auto
dx
=
framework
::
EigenVector
<
T
>::
Flatten
(
*
dX
);
auto
*
place
=
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
Eigen
::
DSizes
<
int
,
1
>
x_dsize
(
X
->
numel
());
dx
.
device
(
*
place
)
=
(
dout
.
broadcast
(
x_dsize
)
*
x
)
*
static_cast
<
T
>
(
2.0
);
}
};
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/squared_l2_norm_op_mlu.cc
浏览文件 @
3e170163
...
...
@@ -13,7 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/squared_l2_norm_op.h"
// #include "paddle/fluid/platform/device/npu/npu_op_runner.h"
#include "paddle/fluid/operators/mlu/mlu_baseop.h"
...
...
paddle/fluid/operators/squared_l2_norm_op_npu.cc
浏览文件 @
3e170163
...
...
@@ -12,7 +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/
operators/squared_l2_norm_op
.h"
#include "paddle/fluid/
framework/op_registry
.h"
#include "paddle/fluid/platform/device/npu/npu_op_runner.h"
namespace
paddle
{
...
...
paddle/phi/api/yaml/legacy_api.yaml
浏览文件 @
3e170163
...
...
@@ -2062,6 +2062,15 @@
func
:
square
backward
:
square_grad
-
api
:
squared_l2_norm
args
:
(Tensor x)
output
:
Tensor
infer_meta
:
func
:
SquaredL2NormInferMeta
kernel
:
func
:
squared_l2_norm
backward
:
squared_l2_norm_grad
-
api
:
squeeze
args
:
(Tensor x, int[] axes)
output
:
Tensor(out), Tensor(xshape)
...
...
paddle/phi/api/yaml/legacy_backward.yaml
浏览文件 @
3e170163
...
...
@@ -2009,6 +2009,16 @@
backward
:
square_double_grad
inplace
:
(out_grad -> x_grad)
-
backward_api
:
squared_l2_norm_grad
forward
:
squared_l2_norm(Tensor x) -> Tensor(out)
args
:
(Tensor x, Tensor out_grad)
output
:
Tensor(x_grad)
infer_meta
:
func
:
UnchangedInferMeta
param
:
[
x
]
kernel
:
func
:
squared_l2_norm_grad
-
backward_api
:
squeeze_double_grad
forward
:
squeeze_grad(Tensor xshape, Tensor grad_out, int[] axes) -> Tensor(grad_x)
args
:
(Tensor grad_x_grad, int[] axes)
...
...
paddle/phi/infermeta/unary.cc
浏览文件 @
3e170163
...
...
@@ -2489,6 +2489,10 @@ void SplitInferMeta(const MetaTensor& x,
}
}
void
SquaredL2NormInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
)
{
out
->
set_dims
({
1
});
}
void
SqueezeInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
axes
,
MetaTensor
*
out
)
{
...
...
paddle/phi/infermeta/unary.h
浏览文件 @
3e170163
...
...
@@ -345,6 +345,8 @@ void SplitInferMeta(const MetaTensor& x_meta,
std
::
vector
<
MetaTensor
*>
out
,
MetaConfig
config
=
MetaConfig
());
void
SquaredL2NormInferMeta
(
const
MetaTensor
&
x
,
MetaTensor
*
out
);
void
SqueezeInferMeta
(
const
MetaTensor
&
x
,
const
std
::
vector
<
int
>&
axes
,
MetaTensor
*
out
);
...
...
paddle/phi/kernels/cpu/squared_l2_norm_grad_kernel.cc
0 → 100644
浏览文件 @
3e170163
// 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/kernels/squared_l2_norm_grad_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/squared_l2_norm_grad_kernel_impl.h"
PD_REGISTER_KERNEL
(
squared_l2_norm_grad
,
CPU
,
ALL_LAYOUT
,
phi
::
SquaredL2NormGradKernel
,
float
,
double
)
{}
paddle/phi/kernels/cpu/squared_l2_norm_kernel.cc
0 → 100644
浏览文件 @
3e170163
// 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/kernels/squared_l2_norm_kernel.h"
#include "paddle/phi/backends/cpu/cpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/squared_l2_norm_kernel_impl.h"
PD_REGISTER_KERNEL
(
squared_l2_norm
,
CPU
,
ALL_LAYOUT
,
phi
::
SquaredL2NormKernel
,
float
,
double
)
{
}
paddle/
fluid/operators/math
/squared_l2_norm.h
→
paddle/
phi/kernels/funcs
/squared_l2_norm.h
浏览文件 @
3e170163
...
...
@@ -14,13 +14,12 @@
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/memory/buffer.h"
#include "paddle/
fluid/platform
/device_context.h"
#include "paddle/
fluid/platform/enforce
.h"
#include "paddle/
phi/core
/device_context.h"
#include "paddle/
phi/kernels/funcs/eigen/common
.h"
#if defined(__NVCC__) || defined(__HIPCC__)
#include "paddle/
fluid/operators/kernel_primitives
/functor_primitives.h"
#include "paddle/
phi/kernels/primitive
/functor_primitives.h"
#ifdef __NVCC__
#include "cub/cub.cuh"
#else
...
...
@@ -29,20 +28,19 @@ namespace cub = hipcub;
#endif
#endif
namespace
paddle
{
namespace
operators
{
namespace
math
{
namespace
phi
{
namespace
funcs
{
template
<
typename
T1
,
typename
T2
=
T1
>
void
SquaredL2Norm
(
const
phi
::
CPUContext
&
ctx
,
const
T1
*
x
,
T2
*
y
,
size_t
numel
,
memory
::
Buffer
*
buffer
=
nullptr
)
{
paddle
::
memory
::
Buffer
*
buffer
=
nullptr
)
{
if
(
std
::
is_same
<
T1
,
T2
>::
value
)
{
using
EigenT
=
typename
framework
::
EigenTensor
<
T1
,
1
>::
Type
;
using
ConstEigenT
=
typename
framework
::
EigenTensor
<
T1
,
1
>::
ConstType
;
using
EigenDim
=
typename
framework
::
EigenDim
<
1
>::
Type
;
using
EigenT
=
typename
phi
::
EigenTensor
<
T1
,
1
>::
Type
;
using
ConstEigenT
=
typename
phi
::
EigenTensor
<
T1
,
1
>::
ConstType
;
using
EigenDim
=
typename
phi
::
EigenDim
<
1
>::
Type
;
ConstEigenT
input
(
x
,
EigenDim
(
numel
));
EigenT
output
(
reinterpret_cast
<
T1
*>
(
y
),
EigenDim
(
1
));
output
.
device
(
*
ctx
.
eigen_device
())
=
input
.
square
().
sum
();
...
...
@@ -58,17 +56,17 @@ void SquaredL2Norm(const phi::CPUContext& ctx,
#if defined(__NVCC__) || defined(__HIPCC__)
template
<
typename
T1
,
typename
T2
=
T1
>
void
SquaredL2Norm
(
const
p
latform
::
CUDADevice
Context
&
ctx
,
void
SquaredL2Norm
(
const
p
hi
::
GPU
Context
&
ctx
,
const
T1
*
x
,
T2
*
y
,
size_t
numel
,
memory
::
Buffer
*
buffer
=
nullptr
)
{
paddle
::
memory
::
Buffer
*
buffer
=
nullptr
)
{
if
(
UNLIKELY
(
buffer
==
nullptr
))
{
memory
::
Buffer
tmp_buffer
(
ctx
.
GetPlace
());
paddle
::
memory
::
Buffer
tmp_buffer
(
ctx
.
GetPlace
());
return
SquaredL2Norm
(
ctx
,
x
,
y
,
numel
,
&
tmp_buffer
);
}
using
FunctorT
=
kernel_primitive
s
::
SquareFunctor
<
T1
,
T2
>
;
using
FunctorT
=
phi
::
kp
s
::
SquareFunctor
<
T1
,
T2
>
;
cub
::
TransformInputIterator
<
T2
,
FunctorT
,
const
T1
*>
iter
(
x
,
FunctorT
());
size_t
temp_storage_bytes
=
0
;
void
*
d_temp_storage
=
nullptr
;
...
...
@@ -89,6 +87,5 @@ void SquaredL2Norm(const platform::CUDADeviceContext& ctx,
}
#endif
}
// namespace math
}
// namespace operators
}
// namespace paddle
}
// namespace funcs
}
// namespace phi
paddle/phi/kernels/gpu/squared_l2_norm_grad_kernel.cu
0 → 100644
浏览文件 @
3e170163
// 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/kernels/squared_l2_norm_grad_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/squared_l2_norm_grad_kernel_impl.h"
PD_REGISTER_KERNEL
(
squared_l2_norm_grad
,
GPU
,
ALL_LAYOUT
,
phi
::
SquaredL2NormGradKernel
,
float
,
double
)
{}
paddle/phi/kernels/gpu/squared_l2_norm_kernel.cu
0 → 100644
浏览文件 @
3e170163
// 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/kernels/squared_l2_norm_kernel.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/impl/squared_l2_norm_kernel_impl.h"
PD_REGISTER_KERNEL
(
squared_l2_norm
,
GPU
,
ALL_LAYOUT
,
phi
::
SquaredL2NormKernel
,
float
,
double
)
{
}
paddle/phi/kernels/impl/squared_l2_norm_grad_kernel_impl.h
0 → 100644
浏览文件 @
3e170163
// 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/kernels/funcs/eigen/common.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SquaredL2NormGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
dout
,
DenseTensor
*
dx
)
{
dev_ctx
.
template
Alloc
<
T
>(
dx
);
PADDLE_ENFORCE_EQ
(
dout
.
numel
(),
1
,
phi
::
errors
::
InvalidArgument
(
"Input(GRAD@Out) of SquaredL2NormGradOP should be a scalar."
));
auto
input
=
phi
::
EigenVector
<
T
>::
Flatten
(
x
);
auto
d_out
=
phi
::
EigenVector
<
T
>::
Flatten
(
dout
);
auto
d_x
=
phi
::
EigenVector
<
T
>::
Flatten
(
*
dx
);
auto
*
place
=
dev_ctx
.
eigen_device
();
Eigen
::
DSizes
<
int
,
1
>
x_dsize
(
x
.
numel
());
d_x
.
device
(
*
place
)
=
(
d_out
.
broadcast
(
x_dsize
)
*
input
)
*
static_cast
<
T
>
(
2.0
);
}
}
// namespace phi
paddle/phi/kernels/impl/squared_l2_norm_kernel_impl.h
0 → 100644
浏览文件 @
3e170163
// 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
#include "paddle/phi/kernels/funcs/squared_l2_norm.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SquaredL2NormKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
DenseTensor
*
out
)
{
dev_ctx
.
template
Alloc
<
T
>(
out
);
auto
x_ptr
=
x
.
template
data
<
T
>();
auto
numel
=
x
.
numel
();
return
phi
::
funcs
::
SquaredL2Norm
(
dev_ctx
,
x_ptr
,
out
->
data
<
T
>
(),
numel
);
}
}
// namespace phi
paddle/phi/kernels/squared_l2_norm_grad_kernel.h
0 → 100644
浏览文件 @
3e170163
// 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SquaredL2NormGradKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
const
DenseTensor
&
dout
,
DenseTensor
*
dx
);
}
// namespace phi
paddle/phi/kernels/squared_l2_norm_kernel.h
0 → 100644
浏览文件 @
3e170163
// 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.
#pragma once
#include "paddle/phi/core/dense_tensor.h"
namespace
phi
{
template
<
typename
T
,
typename
Context
>
void
SquaredL2NormKernel
(
const
Context
&
dev_ctx
,
const
DenseTensor
&
x
,
DenseTensor
*
out
);
}
// namespace phi
paddle/phi/ops/compat/squared_l2_norm_sig.cc
0 → 100644
浏览文件 @
3e170163
// 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
SquaredL2NormOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"squared_l2_norm"
,
{
"X"
},
{},
{
"Out"
});
}
KernelSignature
SquaredL2NormGradOpArgumentMapping
(
const
ArgumentMappingContext
&
ctx
)
{
return
KernelSignature
(
"squared_l2_norm_grad"
,
{
"X"
,
"Out@GRAD"
},
{},
{
"X@GRAD"
});
}
}
// namespace phi
PD_REGISTER_ARG_MAPPING_FN
(
squared_l2_norm
,
phi
::
SquaredL2NormOpArgumentMapping
);
PD_REGISTER_ARG_MAPPING_FN
(
squared_l2_norm_grad
,
phi
::
SquaredL2NormGradOpArgumentMapping
);
python/paddle/fluid/clip.py
浏览文件 @
3e170163
...
...
@@ -73,8 +73,8 @@ def _squared_l2_norm(x):
if
in_dygraph_mode
():
if
x
.
is_selected_rows
():
new_x
=
paddle
.
to_tensor
(
x
.
numpy
())
return
_C_ops
.
squared_l2_norm
(
new_x
)
return
_C_ops
.
squared_l2_norm
(
x
)
return
_C_ops
.
final_state_
squared_l2_norm
(
new_x
)
return
_C_ops
.
final_state_
squared_l2_norm
(
x
)
else
:
if
_in_legacy_dygraph
():
return
_C_ops
.
squared_l2_norm
(
x
)
...
...
python/paddle/fluid/tests/unittests/test_squared_l2_norm_op.py
浏览文件 @
3e170163
...
...
@@ -20,6 +20,14 @@ from numpy import linalg as LA
from
op_test
import
OpTest
import
paddle
from
paddle
import
_C_ops
from
paddle.framework
import
in_dygraph_mode
def
test_squared_l2_norm
(
x
):
if
in_dygraph_mode
():
return
_C_ops
.
final_state_squared_l2_norm
(
x
)
else
:
return
_C_ops
.
squared_l2_norm
(
x
)
class
TestL2LossOp
(
OpTest
):
...
...
@@ -27,6 +35,7 @@ class TestL2LossOp(OpTest):
"""
def
setUp
(
self
):
self
.
python_api
=
test_squared_l2_norm
self
.
op_type
=
"squared_l2_norm"
self
.
max_relative_error
=
0.05
...
...
@@ -36,7 +45,7 @@ class TestL2LossOp(OpTest):
self
.
outputs
=
{
'Out'
:
np
.
square
(
LA
.
norm
(
X
))}
def
test_check_output
(
self
):
self
.
check_output
()
self
.
check_output
(
check_eager
=
True
)
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
...
...
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