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3e13b912
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3e13b912
编写于
9月 05, 2017
作者:
C
caoying03
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差异文件
add softmax_with_cost_op.
上级
843a8b1e
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4
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4 changed file
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and
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+145
-0
paddle/operators/softmax_with_cost_op.cc
paddle/operators/softmax_with_cost_op.cc
+82
-0
paddle/operators/softmax_with_cost_op.h
paddle/operators/softmax_with_cost_op.h
+40
-0
paddle/pybind/pybind.cc
paddle/pybind/pybind.cc
+1
-0
python/paddle/v2/framework/tests/test_softmax_with_cost_op.py
...on/paddle/v2/framework/tests/test_softmax_with_cost_op.py
+22
-0
未找到文件。
paddle/operators/softmax_with_cost_op.cc
0 → 100644
浏览文件 @
3e13b912
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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
:A
limitations under the License. */
#include "paddle/operators/softmax_op.h"
namespace
paddle
{
namespace
operators
{
class
SoftmaxWithLossOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
auto
logits
=
ctx
.
Input
<
Tensor
>
(
"logits"
);
PADDLE_ENFORCE
(
logits
->
dims
().
size
()
==
2UL
,
"The input of softmax_with_loss_op should be a 2-d tensor."
);
PADDLE_ENFORCE
(
ctx
.
Input
<
Tensor
>
(
"lables"
)
->
dims
().
size
()
==
1UL
,
"The label should be a 1-d tensor."
);
ctx
.
Output
<
Tensor
>
(
"loss"
)
->
Resize
({
logits
->
dims
()[
0
]});
}
};
class
SoftmaxWithLossOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
SoftmaxWithLossOpMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"logits"
,
"The unscaled log probabilities which is a 2-D tensor<float> with"
"shape [N x K]. N is the batch_size, and K is the class number."
);
AddInput
(
"label"
,
"The ground truth. A 1-D tensor<int> with shape N."
);
AddOutput
(
"loss"
,
"A 1-D tensor<float> with shape N."
);
AddComment
(
R"DOC(
Cross entropy loss with softmax are used as the output layer extensively. This
operator computes the softmax normalized values for each row of the input
tensor, after which cross-entropy loss is then computed. This provides a more
numerically stable gradient.
Because this operators performs a softmax on logits internally, it expects
unscaled logits. Please do not call this op with the output of softmax operator,
which will produce incorrect results.
This operators expects mutually exclusive hard labels, each sample in a batch
is in exactly one class with probabilities 1. Each sample in the batch with one
and only one label.
)DOC"
);
}
};
class
SoftmaxWithLossOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP
(
softmax
,
ops
::
SoftmaxWithLossOp
,
ops
::
SoftmaxWithLossOpMaker
,
softmax_grad
,
ops
::
SoftmaxWithLossOpGrad
);
REGISTER_OP_CPU_KERNEL
(
softmax
,
ops
::
SoftmaxWithLossKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
REGISTER_OP_CPU_KERNEL
(
softmax_grad
,
ops
::
SoftmaxWithLossGradKernel
<
paddle
::
platform
::
CPUPlace
,
float
>
);
paddle/operators/softmax_with_cost_op.h
0 → 100644
浏览文件 @
3e13b912
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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/framework/eigen.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenMatrix
=
framework
::
EigenMatrix
<
T
,
MajorType
,
IndexType
>
;
template
<
typename
Place
,
typename
T
>
class
SoftmaxWithLossKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{}
};
template
<
typename
Place
,
typename
T
>
class
SoftmaxWithLossGradKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{}
};
}
// namespace operators
}
// namespace paddle
paddle/pybind/pybind.cc
浏览文件 @
3e13b912
...
...
@@ -37,6 +37,7 @@ USE_OP(mul);
USE_OP
(
mean
);
USE_OP
(
sigmoid
);
USE_OP
(
softmax
);
USE_OP
(
softmax_with_loss
);
USE_OP
(
rowwise_add
);
USE_OP
(
fill_zeros_like
);
USE_NO_KERNEL_OP
(
recurrent
);
...
...
python/paddle/v2/framework/tests/test_softmax_with_cost_op.py
0 → 100644
浏览文件 @
3e13b912
import
unittest
import
numpy
as
np
from
gradient_checker
import
GradientChecker
,
create_op
from
op_test_util
import
OpTestMeta
class
TestSoftmaxWithLossOp
(
unittest
.
TestCase
):
__metaclass__
=
OpTestMeta
def
setUp
(
self
):
pass
class
SoftmaxWithLossGradOpTest
(
GradientChecker
):
def
test_softmax
(
self
):
pass
if
__name__
==
'__main__'
:
unittest
.
main
()
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