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体验新版 GitCode,发现更多精彩内容 >>
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提交
0b49e43d
编写于
3月 14, 2019
作者:
Z
Zeng Jinle
提交者:
GitHub
3月 14, 2019
浏览文件
操作
浏览文件
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差异文件
Merge pull request #16144 from sneaxiy/rnn_mem_opt
PaddingRNN model memory optimize
上级
84c00546
487624e1
变更
12
隐藏空白更改
内联
并排
Showing
12 changed file
with
419 addition
and
53 deletion
+419
-53
paddle/fluid/operators/cross_entropy_op.cc
paddle/fluid/operators/cross_entropy_op.cc
+158
-19
paddle/fluid/operators/cross_entropy_op.cu
paddle/fluid/operators/cross_entropy_op.cu
+10
-0
paddle/fluid/operators/cross_entropy_op.h
paddle/fluid/operators/cross_entropy_op.h
+81
-0
paddle/fluid/operators/expand_op.cc
paddle/fluid/operators/expand_op.cc
+18
-1
paddle/fluid/operators/math.h
paddle/fluid/operators/math.h
+42
-0
paddle/fluid/operators/math/cross_entropy.cu
paddle/fluid/operators/math/cross_entropy.cu
+1
-12
paddle/fluid/operators/selu_op.h
paddle/fluid/operators/selu_op.h
+2
-3
paddle/fluid/operators/sequence_ops/sequence_softmax_op.cu
paddle/fluid/operators/sequence_ops/sequence_softmax_op.cu
+1
-3
paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cu
...e/fluid/operators/sigmoid_cross_entropy_with_logits_op.cu
+1
-5
python/paddle/fluid/layers/nn.py
python/paddle/fluid/layers/nn.py
+16
-0
python/paddle/fluid/tests/unittests/test_cross_entropy2_op.py
...on/paddle/fluid/tests/unittests/test_cross_entropy2_op.py
+79
-0
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
+10
-10
未找到文件。
paddle/fluid/operators/cross_entropy_op.cc
浏览文件 @
0b49e43d
...
...
@@ -13,18 +13,21 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/cross_entropy_op.h"
#include <memory>
#include <string>
#include <unordered_map>
namespace
paddle
{
namespace
operators
{
class
CrossEntropyOp
:
public
framework
::
OperatorWithKernel
{
class
CrossEntropyOp
Base
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should be not null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
"Input(Label) should be not null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Y"
),
"Output(Y) should be not null."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
...
...
@@ -43,7 +46,8 @@ class CrossEntropyOp : public framework::OperatorWithKernel {
"Input(X) and Input(Label) shall have the same shape "
"except the last dimension."
);
}
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"soft_label"
))
{
if
(
IsSoftLabel
(
ctx
))
{
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
x_dims
[
rank
-
1
],
label_dims
[
rank
-
1
],
"If Attr(soft_label) == true, the last dimension of "
...
...
@@ -69,21 +73,24 @@ class CrossEntropyOp : public framework::OperatorWithKernel {
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
(),
ctx
.
device_context
());
}
virtual
bool
IsSoftLabel
(
framework
::
InferShapeContext
*
ctx
)
const
{
return
ctx
->
Attrs
().
Get
<
bool
>
(
"soft_label"
);
}
};
class
CrossEntropyGradientOp
:
public
framework
::
OperatorWithKernel
{
class
CrossEntropyGradientOp
Base
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should be not null."
);
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Label"
),
"Input(Label) should be not null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Y"
)),
"Input(Y@GRAD) shoudl be not null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)),
"Output(X@GRAD) should be not null."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
x_dims
=
GetXDim
(
ctx
);
auto
label_dims
=
ctx
->
GetInputDim
(
"Label"
);
auto
dy_dims
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Y"
));
int
rank
=
x_dims
.
size
();
...
...
@@ -108,9 +115,7 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
"The Input(X) and Input(Y@Grad) should have the same "
"shape except the last dimension."
);
}
PADDLE_ENFORCE_EQ
(
dy_dims
[
rank
-
1
],
1
,
"The last dimension of Input(Y@Grad) should be 1."
);
if
(
ctx
->
Attrs
().
Get
<
bool
>
(
"soft_label"
))
{
if
(
IsSoftLabel
(
ctx
))
{
if
(
check
)
{
PADDLE_ENFORCE_EQ
(
x_dims
[
rank
-
1
],
label_dims
[
rank
-
1
],
...
...
@@ -123,7 +128,10 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
"Input(Label) should be 1."
);
}
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
x_dims
);
ctx
->
ShareLoD
(
"X"
,
framework
::
GradVarName
(
"X"
));
PADDLE_ENFORCE_EQ
(
dy_dims
[
rank
-
1
],
1
,
"The last dimension of Input(Y@Grad) should be 1."
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
x_dims
);
ctx
->
ShareLoD
(
VarNameWithXLoD
(),
framework
::
GradVarName
(
"X"
));
}
protected:
...
...
@@ -131,8 +139,28 @@ class CrossEntropyGradientOp : public framework::OperatorWithKernel {
// is determined by its input "X".
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
"X"
)
->
type
(),
ctx
.
device_context
());
return
framework
::
OpKernelType
(
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
))
->
type
(),
ctx
.
device_context
());
}
virtual
framework
::
DDim
GetXDim
(
framework
::
InferShapeContext
*
ctx
)
const
{
return
ctx
->
GetInputDim
(
"X"
);
}
virtual
const
char
*
VarNameWithXLoD
()
const
{
return
"X"
;
}
virtual
bool
IsSoftLabel
(
framework
::
InferShapeContext
*
ctx
)
const
{
return
ctx
->
Attrs
().
Get
<
bool
>
(
"soft_label"
);
}
};
class
CrossEntropyOpInferVarType
:
public
framework
::
PassInDtypeAndVarTypeToOutput
{
protected:
std
::
unordered_map
<
std
::
string
,
std
::
string
>
GetInputOutputWithSameType
()
const
override
{
return
std
::
unordered_map
<
std
::
string
,
std
::
string
>
{{
"X"
,
/*->*/
"Y"
}};
}
};
...
...
@@ -200,22 +228,122 @@ or not. But the output only shares the LoD information with input X.
}
};
class
CrossEntropyOpInferVarType
:
public
framework
::
PassInDtypeAndVarTypeToOutput
{
class
CrossEntropyGradientOp
:
public
CrossEntropyGradientOpBase
{
public:
using
CrossEntropyGradientOpBase
::
CrossEntropyGradientOpBase
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) should be not null."
);
CrossEntropyGradientOpBase
::
InferShape
(
ctx
);
}
};
class
CrossEntropyOp2
:
public
CrossEntropyOpBase
{
public:
using
CrossEntropyOpBase
::
CrossEntropyOpBase
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
CrossEntropyOpBase
::
InferShape
(
ctx
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"XShape"
),
"Output(XShape) should be not null."
);
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
x_dims_vec
=
framework
::
vectorize
(
x_dims
);
x_dims_vec
.
push_back
(
0
);
ctx
->
SetOutputDim
(
"XShape"
,
framework
::
make_ddim
(
x_dims_vec
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
"XShape"
);
}
protected:
std
::
unordered_map
<
std
::
string
,
std
::
string
>
GetInputOutputWithSameType
()
const
override
{
return
std
::
unordered_map
<
std
::
string
,
std
::
string
>
{{
"X"
,
/*->*/
"Y"
}};
bool
IsSoftLabel
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
return
false
;
}
};
class
CrossEntropyGradientOp2
:
public
CrossEntropyGradientOpBase
{
public:
using
CrossEntropyGradientOpBase
::
CrossEntropyGradientOpBase
;
protected:
virtual
framework
::
DDim
GetXDim
(
framework
::
InferShapeContext
*
ctx
)
const
{
auto
x_shape
=
ctx
->
GetInputDim
(
"XShape"
);
return
framework
::
DDim
(
x_shape
.
Get
(),
x_shape
.
size
()
-
1
);
}
virtual
const
char
*
VarNameWithXLoD
()
const
{
return
"XShape"
;
}
virtual
bool
IsSoftLabel
(
framework
::
InferShapeContext
*
ctx
)
const
{
return
false
;
}
};
class
CrossEntropyOpMaker2
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"(Tensor, default Tensor<float>), a tensor whose last dimension "
"size is equal to the number of classes. This input is a "
"probability computed by the previous operator, which is almost "
"always the result of a softmax operator."
);
AddInput
(
"Label"
,
"(Tensor), the tensor which represents the ground truth. It has the "
"same shape with 'X' except the last dimension. One hot Tensor."
);
AddOutput
(
"Y"
,
"(Tensor, default Tensor<float>), a tensor whose shape is same "
"with 'X' except that the last dimension size is 1. It "
"represents the cross entropy loss."
);
AddOutput
(
"XShape"
,
"Temporaily variable to save shape and LoD of X."
);
AddAttr
<
int
>
(
"ignore_index"
,
"(int, default -100), Specifies a target value that is"
"ignored and does not contribute to the input gradient."
"Only valid if soft_label is set to False"
)
.
SetDefault
(
-
100
);
AddComment
(
R"DOC(
Hard-label CrossEntropy Operator.
The input 'X' and 'Label' will first be logically flattened to 2-D matrixs.
The matrix's second dimension(row length) is as same as the original last
dimension, and the first dimension(column length) is the product of all other
original dimensions. Then the softmax computation will take palce on each raw
of flattened matrixs.
Only support hard label.
Both the input X and Label can carry the LoD (Level of Details) information,
or not. But the output only shares the LoD information with input X.
)DOC"
);
}
};
class
CrossEntropyGradOpDescMaker2
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"cross_entropy_grad2"
);
op
->
SetInput
(
"Label"
,
Input
(
"Label"
));
op
->
SetInput
(
"Y"
,
Output
(
"Y"
));
op
->
SetInput
(
"XShape"
,
Output
(
"XShape"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Y"
),
OutputGrad
(
"Y"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
using
CPUCtx
=
paddle
::
platform
::
CPUDeviceContext
;
REGISTER_OPERATOR
(
cross_entropy
,
ops
::
CrossEntropyOp
,
ops
::
CrossEntropyOpMaker
,
ops
::
CrossEntropyOpInferVarType
,
REGISTER_OPERATOR
(
cross_entropy
,
ops
::
CrossEntropyOp
Base
,
ops
::
CrossEntropyOp
Maker
,
ops
::
CrossEntropyOp
InferVarType
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
REGISTER_OPERATOR
(
cross_entropy_grad
,
ops
::
CrossEntropyGradientOp
);
REGISTER_OP_CPU_KERNEL
(
cross_entropy
,
ops
::
CrossEntropyOpKernel
<
CPUCtx
,
float
>
,
...
...
@@ -223,3 +351,14 @@ REGISTER_OP_CPU_KERNEL(cross_entropy, ops::CrossEntropyOpKernel<CPUCtx, float>,
REGISTER_OP_CPU_KERNEL
(
cross_entropy_grad
,
ops
::
CrossEntropyGradientOpKernel
<
CPUCtx
,
float
>
,
ops
::
CrossEntropyGradientOpKernel
<
CPUCtx
,
double
>
);
REGISTER_OPERATOR
(
cross_entropy2
,
ops
::
CrossEntropyOp2
,
ops
::
CrossEntropyOpMaker2
,
ops
::
CrossEntropyOpInferVarType
,
ops
::
CrossEntropyGradOpDescMaker2
);
REGISTER_OPERATOR
(
cross_entropy_grad2
,
ops
::
CrossEntropyGradientOp2
);
REGISTER_OP_CPU_KERNEL
(
cross_entropy2
,
ops
::
CrossEntropyOpKernel2
<
CPUCtx
,
float
>
,
ops
::
CrossEntropyOpKernel2
<
CPUCtx
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
cross_entropy_grad2
,
ops
::
CrossEntropyGradientOpKernel2
<
CPUCtx
,
float
>
,
ops
::
CrossEntropyGradientOpKernel2
<
CPUCtx
,
double
>
);
paddle/fluid/operators/cross_entropy_op.cu
浏览文件 @
0b49e43d
...
...
@@ -27,3 +27,13 @@ REGISTER_OP_CUDA_KERNEL(
cross_entropy_grad
,
ops
::
CrossEntropyGradientOpKernel
<
CUDACtx
,
float
>
,
ops
::
CrossEntropyGradientOpKernel
<
CUDACtx
,
double
>
,
ops
::
CrossEntropyGradientOpKernel
<
CUDACtx
,
plat
::
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
cross_entropy2
,
ops
::
CrossEntropyOpKernel2
<
CUDACtx
,
float
>
,
ops
::
CrossEntropyOpKernel2
<
CUDACtx
,
double
>
,
ops
::
CrossEntropyOpKernel2
<
CUDACtx
,
plat
::
float16
>
);
REGISTER_OP_CUDA_KERNEL
(
cross_entropy_grad2
,
ops
::
CrossEntropyGradientOpKernel2
<
CUDACtx
,
float
>
,
ops
::
CrossEntropyGradientOpKernel2
<
CUDACtx
,
double
>
,
ops
::
CrossEntropyGradientOpKernel2
<
CUDACtx
,
plat
::
float16
>
);
paddle/fluid/operators/cross_entropy_op.h
浏览文件 @
0b49e43d
...
...
@@ -15,6 +15,7 @@ limitations under the License. */
#pragma once
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/operators/math/cross_entropy.h"
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/for_range.h"
...
...
@@ -137,5 +138,85 @@ class CrossEntropyGradientOpKernel : public framework::OpKernel<T> {
}
};
template
<
typename
T
>
struct
HardLabelCrossEntropyBackwardFunctor
{
HardLabelCrossEntropyBackwardFunctor
(
T
*
dx
,
const
T
*
y
,
const
T
*
dy
,
const
int64_t
*
label
,
int64_t
ignore_index
,
int64_t
feature_size
)
:
dx_
(
dx
),
y_
(
y
),
dy_
(
dy
),
label_
(
label
),
ignore_index_
(
ignore_index
),
feature_size_
(
feature_size
)
{}
HOSTDEVICE
void
operator
()(
int64_t
idx
)
const
{
auto
row_idx
=
idx
/
feature_size_
;
auto
col_idx
=
idx
%
feature_size_
;
auto
label
=
label_
[
row_idx
];
if
(
label
==
col_idx
&&
label
!=
ignore_index_
)
{
dx_
[
idx
]
=
-
dy_
[
row_idx
]
*
real_exp
(
y_
[
row_idx
]);
}
else
{
dx_
[
idx
]
=
0
;
}
}
T
*
dx_
;
const
T
*
y_
;
const
T
*
dy_
;
const
int64_t
*
label_
;
int64_t
ignore_index_
;
int64_t
feature_size_
;
};
template
<
typename
DeviceContext
,
typename
T
>
class
CrossEntropyOpKernel2
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
x_original
=
ctx
.
Input
<
Tensor
>
(
"X"
);
int
rank
=
x_original
->
dims
().
size
();
auto
x
=
framework
::
ReshapeToMatrix
(
*
x_original
,
rank
-
1
);
auto
label
=
framework
::
ReshapeToMatrix
(
*
ctx
.
Input
<
Tensor
>
(
"Label"
),
rank
-
1
);
auto
*
y
=
ctx
.
Output
<
Tensor
>
(
"Y"
);
y
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
ignore_index
=
ctx
.
Attr
<
int
>
(
"ignore_index"
);
math
::
CrossEntropyFunctor
<
DeviceContext
,
T
>
()(
ctx
.
template
device_context
<
DeviceContext
>(),
y
,
&
x
,
&
label
,
false
,
ignore_index
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
CrossEntropyGradientOpKernel2
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
*
dx
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y
=
ctx
.
Input
<
Tensor
>
(
"Y"
);
auto
*
dy
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
label
=
ctx
.
Input
<
Tensor
>
(
"Label"
);
auto
*
p_dx
=
dx
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
*
p_y
=
y
->
data
<
T
>
();
auto
*
p_dy
=
dy
->
data
<
T
>
();
auto
*
p_label
=
label
->
data
<
int64_t
>
();
int64_t
ignore_index
=
ctx
.
Attr
<
int
>
(
"ignore_index"
);
int
rank
=
dx
->
dims
().
size
();
int64_t
feature_size
=
dx
->
dims
()[
rank
-
1
];
int64_t
batch_size
=
framework
::
product
(
dx
->
dims
())
/
feature_size
;
platform
::
ForRange
<
DeviceContext
>
for_range
(
ctx
.
template
device_context
<
DeviceContext
>(),
batch_size
*
feature_size
);
for_range
(
HardLabelCrossEntropyBackwardFunctor
<
T
>
(
p_dx
,
p_y
,
p_dy
,
p_label
,
ignore_index
,
feature_size
));
}
};
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/expand_op.cc
浏览文件 @
0b49e43d
...
...
@@ -13,6 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/operators/expand_op.h"
#include <memory>
#include <vector>
namespace
paddle
{
...
...
@@ -138,12 +139,28 @@ class ExpandGradOp : public framework::OperatorWithKernel {
}
};
class
ExpandGradOpDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
std
::
unique_ptr
<
framework
::
OpDesc
>
op
(
new
framework
::
OpDesc
());
op
->
SetType
(
"expand_grad"
);
op
->
SetInput
(
"X"
,
Input
(
"X"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
InputGrad
(
"X"
));
op
->
SetAttrMap
(
Attrs
());
return
op
;
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
expand
,
ops
::
ExpandOp
,
ops
::
ExpandOpMaker
,
paddle
::
framework
::
DefaultGradOpDescMaker
<
true
>
);
ops
::
ExpandGradOpDescMaker
);
REGISTER_OPERATOR
(
expand_grad
,
ops
::
ExpandGradOp
);
REGISTER_OP_CPU_KERNEL
(
expand
,
ops
::
ExpandKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
...
...
paddle/fluid/operators/math.h
0 → 100644
浏览文件 @
0b49e43d
// Copyright (c) 2019 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/platform/float16.h"
#include "paddle/fluid/platform/hostdevice.h"
#include "math.h" // NOLINT
namespace
paddle
{
namespace
operators
{
inline
HOSTDEVICE
platform
::
float16
real_exp
(
platform
::
float16
x
)
{
return
static_cast
<
platform
::
float16
>
(
::
expf
(
static_cast
<
float
>
(
x
)));
}
inline
HOSTDEVICE
float
real_exp
(
float
x
)
{
return
::
expf
(
x
);
}
inline
HOSTDEVICE
double
real_exp
(
double
x
)
{
return
::
exp
(
x
);
}
inline
HOSTDEVICE
platform
::
float16
real_log
(
platform
::
float16
x
)
{
return
static_cast
<
platform
::
float16
>
(
::
logf
(
static_cast
<
float
>
(
x
)));
}
inline
HOSTDEVICE
float
real_log
(
float
x
)
{
return
::
logf
(
x
);
}
inline
HOSTDEVICE
double
real_log
(
double
x
)
{
return
::
log
(
x
);
}
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/math/cross_entropy.cu
浏览文件 @
0b49e43d
...
...
@@ -12,6 +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/math.h"
#include "paddle/fluid/operators/math/cross_entropy.h"
#include "paddle/fluid/platform/cuda_device_function.h"
#include "paddle/fluid/platform/cuda_primitives.h"
...
...
@@ -20,17 +21,6 @@ namespace paddle {
namespace
operators
{
namespace
math
{
namespace
{
__device__
__forceinline__
float
real_log
(
float
x
)
{
return
logf
(
x
);
}
__device__
__forceinline__
double
real_log
(
double
x
)
{
return
log
(
x
);
}
__device__
__forceinline__
platform
::
float16
real_log
(
const
platform
::
float16
&
val
)
{
return
static_cast
<
platform
::
float16
>
(
logf
(
static_cast
<
float
>
(
val
)));
}
template
<
typename
T
>
__global__
void
CrossEntropyKernel
(
T
*
Y
,
const
T
*
X
,
const
int64_t
*
label
,
const
int
N
,
const
int
D
,
...
...
@@ -61,7 +51,6 @@ __global__ void SoftCrossEntropyKernel(T* Y, const T* X, const T* label,
Y
[
blockIdx
.
x
]
=
-
val
;
}
}
}
// namespace
template
<
typename
T
>
class
CrossEntropyFunctor
<
platform
::
CUDADeviceContext
,
T
>
{
...
...
paddle/fluid/operators/selu_op.h
浏览文件 @
0b49e43d
...
...
@@ -15,13 +15,12 @@ limitations under the License. */
#pragma once
#include <string>
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/platform/for_range.h"
namespace
paddle
{
namespace
operators
{
static
HOSTDEVICE
float
real_exp
(
float
x
)
{
return
expf
(
x
);
}
static
HOSTDEVICE
float
real_exp
(
double
x
)
{
return
exp
(
x
);
}
template
<
typename
T
>
struct
SeluFunctor
{
SeluFunctor
(
const
T
*
x_data_ptr
,
float
alpha
,
float
scale
,
T
*
y_data_ptr
)
...
...
paddle/fluid/operators/sequence_ops/sequence_softmax_op.cu
浏览文件 @
0b49e43d
...
...
@@ -14,6 +14,7 @@ limitations under the License. */
#include <algorithm>
#include <cub/cub.cuh> // NOLINT
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/operators/sequence_ops/sequence_softmax_op.h"
namespace
paddle
{
...
...
@@ -21,9 +22,6 @@ namespace operators {
using
LoDTensor
=
framework
::
LoDTensor
;
__device__
__forceinline__
float
real_exp
(
float
x
)
{
return
expf
(
x
);
}
__device__
__forceinline__
double
real_exp
(
double
x
)
{
return
exp
(
x
);
}
template
<
typename
T
,
int
BlockDim
>
using
BlockReduce
=
cub
::
BlockReduce
<
T
,
BlockDim
>
;
...
...
paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.cu
浏览文件 @
0b49e43d
...
...
@@ -12,6 +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 "cub/cub.cuh"
#include "paddle/fluid/operators/math.h"
#include "paddle/fluid/operators/sigmoid_cross_entropy_with_logits_op.h"
#include "paddle/fluid/platform/cuda_primitives.h"
#include "paddle/fluid/platform/hostdevice.h"
...
...
@@ -21,11 +22,6 @@ namespace operators {
using
Tensor
=
framework
::
Tensor
;
static
HOSTDEVICE
float
real_exp
(
float
x
)
{
return
expf
(
x
);
}
static
HOSTDEVICE
float
real_exp
(
double
x
)
{
return
exp
(
x
);
}
static
HOSTDEVICE
float
real_log
(
float
x
)
{
return
logf
(
x
);
}
static
HOSTDEVICE
float
real_log
(
double
x
)
{
return
log
(
x
);
}
static
constexpr
int
kNumCUDAThreads
=
512
;
static
constexpr
int
kNumMaxinumNumBlocks
=
4096
;
...
...
python/paddle/fluid/layers/nn.py
浏览文件 @
0b49e43d
...
...
@@ -1432,6 +1432,8 @@ def cross_entropy(input, label, soft_label=False, ignore_index=kIgnoreIndex):
predict = fluid.layers.fc(input=net, size=classdim, act='softmax')
cost = fluid.layers.cross_entropy(input=predict, label=label)
"""
if
not
soft_label
:
return
cross_entropy2
(
input
,
label
,
ignore_index
)
helper
=
LayerHelper
(
'cross_entropy'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
input
.
dtype
)
helper
.
append_op
(
...
...
@@ -1444,6 +1446,20 @@ def cross_entropy(input, label, soft_label=False, ignore_index=kIgnoreIndex):
return
out
def
cross_entropy2
(
input
,
label
,
ignore_index
=
kIgnoreIndex
):
helper
=
LayerHelper
(
'cross_entropy2'
,
**
locals
())
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
input
.
dtype
)
xshape
=
helper
.
create_variable_for_type_inference
(
dtype
=
input
.
dtype
)
helper
.
append_op
(
type
=
'cross_entropy2'
,
inputs
=
{
'X'
:
[
input
],
'Label'
:
[
label
]},
outputs
=
{
'Y'
:
[
out
],
'XShape'
:
[
xshape
]},
attrs
=
{
'ignore_index'
:
ignore_index
})
return
out
def
bpr_loss
(
input
,
label
,
name
=
None
):
"""
Bayesian Personalized Ranking Loss Operator.
...
...
python/paddle/fluid/tests/unittests/test_cross_entropy2_op.py
0 → 100644
浏览文件 @
0b49e43d
# Copyright (c) 2019 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.
from
op_test
import
OpTest
import
unittest
import
numpy
as
np
import
six
class
CrossEntropy2OpTestBase
(
OpTest
):
def
initParameters
(
self
):
return
[
32
,
64
],
'float32'
,
-
100
def
calc_output
(
self
,
logits
,
label
,
ignore_index
):
ret
=
np
.
zeros
(
shape
=
label
.
shape
,
dtype
=
logits
.
dtype
)
for
idx
in
six
.
moves
.
range
(
label
.
shape
[
0
]):
if
label
[
idx
]
==
ignore_index
:
continue
ret
[
idx
]
=
-
np
.
log
(
logits
[
idx
][
label
[
idx
]])
return
ret
def
setUp
(
self
):
self
.
shape
,
self
.
dtype
,
self
.
ignore_index
=
self
.
initParameters
()
self
.
op_type
=
'cross_entropy2'
feature_size
=
int
(
self
.
shape
[
-
1
])
batch_size
=
int
(
np
.
prod
(
self
.
shape
)
/
feature_size
)
logits
=
(
np
.
random
.
random
(
size
=
self
.
shape
)
+
1
).
astype
(
self
.
dtype
)
label
=
np
.
random
.
random_integers
(
low
=
0
,
high
=
feature_size
-
1
,
size
=
self
.
shape
[
0
:
-
1
]
+
[
1
]).
astype
(
'int64'
)
outputs
=
self
.
calc_output
(
np
.
reshape
(
logits
,
[
batch_size
,
feature_size
]),
np
.
reshape
(
label
,
[
batch_size
,
1
]),
self
.
ignore_index
)
self
.
inputs
=
{
'X'
:
logits
,
'Label'
:
label
}
self
.
outputs
=
{
'Y'
:
np
.
reshape
(
outputs
,
label
.
shape
),
'XShape'
:
np
.
zeros
(
shape
=
logits
.
shape
,
dtype
=
logits
.
dtype
)
}
self
.
attrs
=
{
'ignore_index'
:
self
.
ignore_index
}
def
test_check_output
(
self
):
self
.
check_output
(
no_check_set
=
[
'XShape'
])
def
test_check_grad
(
self
):
self
.
check_grad
(
inputs_to_check
=
[
'X'
],
output_names
=
[
'Y'
],
no_grad_set
=
[
'XShape'
,
'Label'
])
class
CrossEntropy2OpTest2
(
CrossEntropy2OpTestBase
):
def
initParameters
(
self
):
return
[
32
,
64
],
'float64'
,
3
class
CrossEntropy2OpTest3
(
CrossEntropy2OpTestBase
):
def
initParameters
(
self
):
return
[
4
,
8
,
16
,
32
],
'float32'
,
-
100
class
CrossEntropy2OpTest4
(
CrossEntropy2OpTestBase
):
def
initParameters
(
self
):
return
[
4
,
8
,
16
,
32
],
'float32'
,
3
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_dist_transpiler.py
浏览文件 @
0b49e43d
...
...
@@ -524,8 +524,8 @@ class TestLocalLookupTable(TestDistLookupTableBase):
ops
=
[
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'cross_entropy
2
'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad
2
'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'split_selected_rows'
,
'send'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
...
...
@@ -564,8 +564,8 @@ class TestDistLookupTable(TestDistLookupTableBase):
ops
=
[
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'elementwise_add'
,
'cross_entropy
2
'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad
2
'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'split_selected_rows'
,
'send'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
...
...
@@ -612,8 +612,8 @@ class TestAsyncLocalLookupTable(TestDistLookupTableBase):
ops
=
[
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'cross_entropy
2
'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad
2
'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'split_selected_rows'
,
'send'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
...
...
@@ -652,8 +652,8 @@ class TestAsyncDistLookupTable(TestDistLookupTableBase):
ops
=
[
'split_ids'
,
'prefetch'
,
'merge_ids'
,
'sequence_pool'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'elementwise_add'
,
'cross_entropy
2
'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad
2
'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'split_selected_rows'
,
'send'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
...
...
@@ -841,8 +841,8 @@ class TestRemoteLookupTable(TestDistLookupTableBase):
ops
=
[
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'lookup_table'
,
'sequence_pool'
,
'concat'
,
'mul'
,
'elementwise_add'
,
'cross_entropy'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'cross_entropy
2
'
,
'mean'
,
'fill_constant'
,
'mean_grad'
,
'cross_entropy_grad
2
'
,
'elementwise_add_grad'
,
'send'
,
'mul_grad'
,
'send'
,
'concat_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'split_selected_rows'
,
'send'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
'sequence_pool_grad'
,
'lookup_table_grad'
,
...
...
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