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8f8ea005
编写于
9月 15, 2017
作者:
C
caoying03
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
fix implementations.
上级
1fb5f12f
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
151 addition
and
35 deletion
+151
-35
paddle/operators/math/utils.h
paddle/operators/math/utils.h
+42
-0
paddle/operators/onehot_cross_entropy_op.cu
paddle/operators/onehot_cross_entropy_op.cu
+4
-16
paddle/operators/softmax_with_cross_entropy_op.cc
paddle/operators/softmax_with_cross_entropy_op.cc
+6
-6
paddle/operators/softmax_with_cross_entropy_op.cu
paddle/operators/softmax_with_cross_entropy_op.cu
+93
-4
paddle/operators/softmax_with_cross_entropy_op.h
paddle/operators/softmax_with_cross_entropy_op.h
+3
-4
python/paddle/v2/framework/tests/test_cross_entropy_op.py
python/paddle/v2/framework/tests/test_cross_entropy_op.py
+0
-1
python/paddle/v2/framework/tests/test_softmax_with_cross_entropy_op.py
.../v2/framework/tests/test_softmax_with_cross_entropy_op.py
+3
-4
未找到文件。
paddle/operators/math/utils.h
0 → 100644
浏览文件 @
8f8ea005
/* 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/platform/assert.h"
#include "paddle/platform/hostdevice.h"
namespace
paddle
{
namespace
operators
{
namespace
math
{
template
<
typename
T
>
T
HOSTDEVICE
tolerable_value
(
const
T
x
)
{
PADDLE_ASSERT
(
std
::
is_floating_point
<
T
>::
value
);
const
T
kApproInf
=
1e20
;
if
(
x
==
INFINITY
)
{
return
kApproInf
;
}
if
(
x
==
-
INFINITY
)
{
return
-
kApproInf
;
}
return
x
;
}
}
// namespace math
}
// namespace operators
}
// namespace paddle
paddle/operators/onehot_cross_entropy_op.cu
浏览文件 @
8f8ea005
...
@@ -13,6 +13,7 @@
...
@@ -13,6 +13,7 @@
limitations under the License. */
limitations under the License. */
#include "paddle/framework/op_registry.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/math/utils.h"
#include "paddle/platform/assert.h"
#include "paddle/platform/assert.h"
namespace
paddle
{
namespace
paddle
{
...
@@ -20,20 +21,6 @@ namespace operators {
...
@@ -20,20 +21,6 @@ namespace operators {
using
Tensor
=
framework
::
Tensor
;
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
>
__host__
__device__
T
clipping_log
(
const
T
x
)
{
PADDLE_ASSERT
(
std
::
is_floating_point
<
T
>::
value
);
const
T
kApproInf
=
1e20
;
T
v
=
log
(
x
);
if
(
v
==
INFINITY
)
{
return
kApproInf
;
}
if
(
v
==
-
INFINITY
)
{
return
-
kApproInf
;
}
return
v
;
}
template
<
typename
T
>
template
<
typename
T
>
__global__
void
CrossEntropyKernel
(
T
*
Y
,
const
T
*
X
,
const
int
*
label
,
__global__
void
CrossEntropyKernel
(
T
*
Y
,
const
T
*
X
,
const
int
*
label
,
const
int
N
,
const
int
D
)
{
const
int
N
,
const
int
D
)
{
...
@@ -42,7 +29,7 @@ __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label,
...
@@ -42,7 +29,7 @@ __global__ void CrossEntropyKernel(T* Y, const T* X, const int* label,
for
(
int
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
i
<
N
;
for
(
int
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
i
<
N
;
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
i
+=
blockDim
.
x
*
gridDim
.
x
)
{
PADDLE_ASSERT
(
label
[
i
]
>=
0
&&
label
[
i
]
<
D
);
PADDLE_ASSERT
(
label
[
i
]
>=
0
&&
label
[
i
]
<
D
);
Y
[
i
]
=
-
clipping_log
(
X
[
i
*
D
+
label
[
i
]]
);
Y
[
i
]
=
-
math
::
tolerable_value
(
log
(
X
[
i
*
D
+
label
[
i
]])
);
}
}
}
}
...
@@ -73,7 +60,7 @@ class OnehotCrossEntropyOpCUDAKernel : public framework::OpKernel {
...
@@ -73,7 +60,7 @@ class OnehotCrossEntropyOpCUDAKernel : public framework::OpKernel {
public:
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()),
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()),
"
It must use GPUPla
ce."
);
"
This kernel only runs on GPU devi
ce."
);
auto
X
=
ctx
.
Input
<
Tensor
>
(
"X"
);
auto
X
=
ctx
.
Input
<
Tensor
>
(
"X"
);
const
T
*
Xdata
=
X
->
data
<
T
>
();
const
T
*
Xdata
=
X
->
data
<
T
>
();
...
@@ -86,6 +73,7 @@ class OnehotCrossEntropyOpCUDAKernel : public framework::OpKernel {
...
@@ -86,6 +73,7 @@ class OnehotCrossEntropyOpCUDAKernel : public framework::OpKernel {
int
D
=
X
->
dims
()[
1
];
int
D
=
X
->
dims
()[
1
];
int
block
=
512
;
int
block
=
512
;
int
grid
=
(
N
+
block
-
1
)
/
block
;
int
grid
=
(
N
+
block
-
1
)
/
block
;
// TODO(qingqing) launch kernel on specified stream
// TODO(qingqing) launch kernel on specified stream
// base on ExecutionContext.
// base on ExecutionContext.
CrossEntropyKernel
<
T
><<<
grid
,
block
>>>
(
Ydata
,
Xdata
,
label_data
,
N
,
D
);
CrossEntropyKernel
<
T
><<<
grid
,
block
>>>
(
Ydata
,
Xdata
,
label_data
,
N
,
D
);
...
...
paddle/operators/softmax_with_cross_entropy_op.cc
浏览文件 @
8f8ea005
...
@@ -32,7 +32,7 @@ class SoftmaxWithCrossEntropyOpMaker
...
@@ -32,7 +32,7 @@ class SoftmaxWithCrossEntropyOpMaker
"Store the outputs of softmax function, "
"Store the outputs of softmax function, "
"which will be used in backward calculation."
)
"which will be used in backward calculation."
)
.
AsIntermediate
();
.
AsIntermediate
();
AddOutput
(
"
Loss
"
,
"A 1-D tensor<float> with shape N."
);
AddOutput
(
"
Out
"
,
"A 1-D tensor<float> with shape N."
);
AddComment
(
R"DOC(
AddComment
(
R"DOC(
Cross entropy loss with softmax are used as the output layer extensively. This
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
operator computes the softmax normalized values for each row of the input
...
@@ -56,14 +56,14 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
...
@@ -56,14 +56,14 @@ class SoftmaxWithCrossEntropyOpGrad : public framework::OperatorWithKernel {
protected:
protected:
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
void
InferShape
(
const
framework
::
InferShapeContext
&
ctx
)
const
override
{
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"
Loss
"
)),
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"
Out
"
)),
"Input(
Loss
@Grad) should not be null"
);
"Input(
Out
@Grad) should not be null"
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Softmax"
),
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Softmax"
),
"Input(Softmax) should be not null."
);
"Input(Softmax) should be not null."
);
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Label"
),
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
"Label"
),
"Input(Lable) should be not null."
);
"Input(Lable) should be not null."
);
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Logits"
))
ctx
.
Output
<
framework
::
LoD
Tensor
>
(
framework
::
GradVarName
(
"Logits"
))
->
Resize
(
ctx
.
Input
<
Tensor
>
(
"Softmax"
)
->
dims
());
->
Resize
(
ctx
.
Input
<
Tensor
>
(
"Softmax"
)
->
dims
());
}
}
};
};
...
@@ -81,8 +81,8 @@ class SoftmaxWithCrossEntropyOp : public framework::OperatorWithKernel {
...
@@ -81,8 +81,8 @@ class SoftmaxWithCrossEntropyOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
()
==
1UL
,
PADDLE_ENFORCE
(
ctx
.
Input
<
Tensor
>
(
"Label"
)
->
dims
().
size
()
==
1UL
,
"The label should be a 1-d tensor."
);
"The label should be a 1-d tensor."
);
ctx
.
Output
<
Tensor
>
(
"Softmax"
)
->
Resize
(
logits
->
dims
());
ctx
.
Output
<
framework
::
LoD
Tensor
>
(
"Softmax"
)
->
Resize
(
logits
->
dims
());
ctx
.
Output
<
Tensor
>
(
"Loss
"
)
->
Resize
({
logits
->
dims
()[
0
],
1
});
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out
"
)
->
Resize
({
logits
->
dims
()[
0
],
1
});
}
}
};
};
...
...
paddle/operators/softmax_with_cross_entropy_op.cu
浏览文件 @
8f8ea005
/* Copyright (c) 2016 PaddlePaddle Authors All Rights Reserve.
/* Copyright (c) 2016 PaddlePaddle Authors
.
All Rights Reserve.
Licensed under the Apache License, Version 2.0 (the "License");
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
you may not use this file except in compliance with the License.
...
@@ -13,8 +13,97 @@
...
@@ -13,8 +13,97 @@
limitations under the License. */
limitations under the License. */
#define EIGEN_USE_GPU
#define EIGEN_USE_GPU
#include "softmax_with_cross_entropy_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/operators/math/softmax_function.h"
#include "paddle/operators/math/utils.h"
namespace
ops
=
paddle
::
operators
;
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
>
__global__
void
CrossEntropyKernel
(
T
*
out
,
const
T
*
softmax_out
,
const
int
*
label
,
const
int
batch_size
,
const
int
class_num
)
{
int
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
i
>=
batch_size
)
return
;
PADDLE_ASSERT
(
label
[
i
]
>=
0
&&
label
[
i
]
<
class_num
);
out
[
i
]
=
-
math
::
tolerable_value
(
log
(
softmax_out
[
i
*
class_num
+
label
[
i
]]));
}
template
<
typename
T
>
__global__
void
CrossEntropyWithSoftmaxGradKernel
(
T
*
softmax_out
,
const
int
*
label
,
const
int
batch_size
,
const
int
class_num
)
{
int
i
=
blockIdx
.
x
*
blockDim
.
x
+
threadIdx
.
x
;
if
(
i
>=
batch_size
)
return
;
PADDLE_ASSERT
(
label
[
i
]
>=
0
&&
label
[
i
]
<
class_num
);
softmax_out
[
i
*
class_num
+
label
[
i
]]
-=
1.
;
}
template
<
typename
T
>
class
SoftmaxWithCrossEntropyCUDAKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
context
.
GetPlace
()),
"This kernel only runs on GPU device."
);
// Calculate ths softmax outputs.
const
Tensor
*
logits
=
context
.
Input
<
Tensor
>
(
"Logits"
);
Tensor
*
softmax
=
context
.
Output
<
Tensor
>
(
"Softmax"
);
softmax
->
mutable_data
<
T
>
(
context
.
GetPlace
());
math
::
SoftmaxFunctor
<
platform
::
GPUPlace
,
T
>
()(
logits
,
softmax
,
context
);
T
*
softmax_out
=
softmax
->
data
<
T
>
();
// Calculate the cross entropy loss based on hard labels.
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
Tensor
*
loss
=
context
.
Output
<
Tensor
>
(
"Out"
);
loss
->
mutable_data
<
T
>
(
context
.
GetPlace
());
T
*
loss_data
=
loss
->
data
<
T
>
();
const
int
batch_size
=
logits
->
dims
()[
0
];
const
int
class_num
=
logits
->
dims
()[
1
];
int
block
=
512
;
int
grid
=
(
batch_size
+
block
-
1
)
/
block
;
// TODO(caoying) add GPU kernel
CrossEntropyKernel
<
T
><<<
grid
,
block
>>>
(
loss_data
,
softmax_out
,
label_data
,
batch_size
,
class_num
);
}
};
template
<
typename
T
>
class
SoftmaxWithCrossEntropyGradCUDAKernel
:
public
framework
::
OpKernel
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
PADDLE_ENFORCE
(
platform
::
is_gpu_place
(
context
.
GetPlace
()),
"This kernel only runs on GPU device."
);
Tensor
*
logit_grad
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Logits"
));
logit_grad
->
ShareDataWith
<
T
>
(
*
context
.
Input
<
Tensor
>
(
"Softmax"
));
T
*
logit_grad_data
=
logit_grad
->
data
<
T
>
();
const
int
batch_size
=
logit_grad
->
dims
()[
0
];
const
int
class_num
=
logit_grad
->
dims
()[
1
];
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
const
int
block
=
512
;
const
int
grid
=
(
batch_size
+
block
-
1
)
/
block
;
CrossEntropyWithSoftmaxGradKernel
<
T
><<<
grid
,
block
>>>
(
logit_grad_data
,
label_data
,
batch_size
,
class_num
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_GPU_KERNEL
(
softmax_with_cross_entropy
,
ops
::
SoftmaxWithCrossEntropyCUDAKernel
<
float
>
);
REGISTER_OP_GPU_KERNEL
(
softmax_with_cross_entropy_grad
,
ops
::
SoftmaxWithCrossEntropyGradCUDAKernel
<
float
>
);
paddle/operators/softmax_with_cross_entropy_op.h
浏览文件 @
8f8ea005
...
@@ -30,8 +30,7 @@ template <typename T>
...
@@ -30,8 +30,7 @@ template <typename T>
class
SoftmaxWithCrossEntropyKernel
:
public
framework
::
OpKernel
{
class
SoftmaxWithCrossEntropyKernel
:
public
framework
::
OpKernel
{
public:
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
place
=
context
.
GetPlace
();
PADDLE_ENFORCE
(
platform
::
is_cpu_place
(
context
.
GetPlace
()),
PADDLE_ENFORCE
(
platform
::
is_cpu_place
(
place
),
"This kernel only runs on CPU."
);
"This kernel only runs on CPU."
);
// Calculate ths softmax outputs.
// Calculate ths softmax outputs.
...
@@ -45,7 +44,7 @@ class SoftmaxWithCrossEntropyKernel : public framework::OpKernel {
...
@@ -45,7 +44,7 @@ class SoftmaxWithCrossEntropyKernel : public framework::OpKernel {
T
*
softmax_out
=
softmax
->
data
<
T
>
();
T
*
softmax_out
=
softmax
->
data
<
T
>
();
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
Tensor
*
loss
=
context
.
Output
<
Tensor
>
(
"
Loss
"
);
Tensor
*
loss
=
context
.
Output
<
Tensor
>
(
"
Out
"
);
loss
->
mutable_data
<
T
>
(
context
.
GetPlace
());
loss
->
mutable_data
<
T
>
(
context
.
GetPlace
());
T
*
loss_data
=
loss
->
data
<
T
>
();
T
*
loss_data
=
loss
->
data
<
T
>
();
...
@@ -74,7 +73,7 @@ class SoftmaxWithCrossEntropyGradKernel : public framework::OpKernel {
...
@@ -74,7 +73,7 @@ class SoftmaxWithCrossEntropyGradKernel : public framework::OpKernel {
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
const
int
*
label_data
=
context
.
Input
<
Tensor
>
(
"Label"
)
->
data
<
int
>
();
for
(
int
i
=
0
;
i
<
batch_size
;
++
i
)
{
for
(
int
i
=
0
;
i
<
batch_size
;
++
i
)
{
int
index
=
i
*
class_num
+
label_data
[
i
];
int
index
=
i
*
class_num
+
label_data
[
i
];
logit_grad_data
[
index
]
-=
.1
;
logit_grad_data
[
index
]
-=
1.
;
}
}
}
}
};
};
...
...
python/paddle/v2/framework/tests/test_cross_entropy_op.py
浏览文件 @
8f8ea005
import
unittest
import
unittest
import
numpy
import
numpy
from
op_test
import
OpTest
from
op_test
import
OpTest
import
pdb
class
TestCrossEntropy
(
OpTest
):
class
TestCrossEntropy
(
OpTest
):
...
...
python/paddle/v2/framework/tests/test_softmax_with_cross_entropy_op.py
浏览文件 @
8f8ea005
import
unittest
import
unittest
import
numpy
as
np
import
numpy
as
np
import
pdb
from
op_test
import
OpTest
from
op_test
import
OpTest
from
test_softmax_op
import
stable_softmax
from
test_softmax_op
import
stable_softmax
...
@@ -11,7 +10,7 @@ class TestSoftmaxWithCrossEntropyOp(OpTest):
...
@@ -11,7 +10,7 @@ class TestSoftmaxWithCrossEntropyOp(OpTest):
self
.
op_type
=
"softmax_with_cross_entropy"
self
.
op_type
=
"softmax_with_cross_entropy"
MAX_BATCH_SIZE
=
23
MAX_BATCH_SIZE
=
23
MAX_CLASS_NUM
=
1
0
MAX_CLASS_NUM
=
1
7
batch_size
=
np
.
random
.
randint
(
1
,
MAX_BATCH_SIZE
,
1
)[
0
]
batch_size
=
np
.
random
.
randint
(
1
,
MAX_BATCH_SIZE
,
1
)[
0
]
class_num
=
np
.
random
.
randint
(
2
,
MAX_CLASS_NUM
,
1
)[
0
]
class_num
=
np
.
random
.
randint
(
2
,
MAX_CLASS_NUM
,
1
)[
0
]
...
@@ -26,13 +25,13 @@ class TestSoftmaxWithCrossEntropyOp(OpTest):
...
@@ -26,13 +25,13 @@ class TestSoftmaxWithCrossEntropyOp(OpTest):
dtype
=
"float32"
)
dtype
=
"float32"
)
self
.
inputs
=
{
"Logits"
:
logits
,
"Label"
:
labels
}
self
.
inputs
=
{
"Logits"
:
logits
,
"Label"
:
labels
}
self
.
outputs
=
{
"Softmax"
:
softmax
,
"
Loss
"
:
cross_entropy
}
self
.
outputs
=
{
"Softmax"
:
softmax
,
"
Out
"
:
cross_entropy
}
def
test_check_output
(
self
):
def
test_check_output
(
self
):
self
.
check_output
()
self
.
check_output
()
def
test_check_grad
(
self
):
def
test_check_grad
(
self
):
self
.
check_grad
([
"Logits"
],
"
Loss"
)
self
.
check_grad
([
"Logits"
],
"
Out"
,
max_relative_error
=
0.05
)
if
__name__
==
"__main__"
:
if
__name__
==
"__main__"
:
...
...
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