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体验新版 GitCode,发现更多精彩内容 >>
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550ab8d7
编写于
7月 02, 2018
作者:
Y
yuyang18
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with
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and
208 deletion
+164
-208
paddle/fluid/operators/reshape_op.cc
paddle/fluid/operators/reshape_op.cc
+164
-52
paddle/fluid/operators/reshape_op.cu.cc
paddle/fluid/operators/reshape_op.cu.cc
+0
-24
paddle/fluid/operators/reshape_op.h
paddle/fluid/operators/reshape_op.h
+0
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未找到文件。
paddle/fluid/operators/reshape_op.cc
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550ab8d7
...
...
@@ -12,14 +12,108 @@ 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/reshape_op.h"
#include <string>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
ReshapeOp
:
public
framework
::
OperatorWithKernel
{
public:
ReshapeOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of ReshapeOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of ReshapeOp should not be null."
);
const
std
::
vector
<
int
>
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE
(
!
shape
.
empty
(),
"The shape information must be set by Attr(shape)."
);
if
(
ctx
->
HasInput
(
"Shape"
)
&&
ctx
->
IsRuntime
())
{
// If true, set the shape of Output(Out) according to Input(Shape) in
// ReshapeKernel with ExecutionContext. Also check LoD in ReshapeKernel.
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
return
;
}
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
out_dims
=
ValidateShape
(
shape
,
x_dims
);
ctx
->
SetOutputDim
(
"Out"
,
out_dims
);
if
(
x_dims
[
0
]
==
out_dims
[
0
])
{
// Only pass LoD when the first dimension of output and Input(X)
// are the same.
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
}
static
framework
::
DDim
ValidateShape
(
const
std
::
vector
<
int
>
shape
,
const
framework
::
DDim
&
in_dims
)
{
const
int64_t
in_size
=
framework
::
product
(
in_dims
);
// only one dimension can be set to -1, whose size will be automatically
// infered.
const
int64_t
unk_dim_val
=
-
1
;
const
int64_t
copy_dim_val
=
0
;
std
::
vector
<
int64_t
>
output_shape
(
shape
.
size
(),
0
);
int64_t
capacity
=
1
;
int
unk_dim_idx
=
-
1
;
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
if
(
shape
[
i
]
==
unk_dim_val
)
{
PADDLE_ENFORCE
(
unk_dim_idx
==
-
1
,
"Only one input dimension of Attr(shape) can be unknown."
);
unk_dim_idx
=
i
;
}
else
if
(
shape
[
i
]
==
copy_dim_val
)
{
PADDLE_ENFORCE
(
static_cast
<
int
>
(
i
)
<
in_dims
.
size
(),
"The index of dimension to copy from input shape must be less "
"than the size of input shape."
);
}
else
{
PADDLE_ENFORCE
(
shape
[
i
]
>
0
,
"Each input dimension of Attr(shape) must not be negtive except "
"one unknown dimension."
);
}
capacity
*=
(
shape
[
i
]
?
shape
[
i
]
:
in_dims
[
i
]);
output_shape
[
i
]
=
(
shape
[
i
]
?
static_cast
<
int64_t
>
(
shape
[
i
])
:
in_dims
[
i
]);
}
if
(
unk_dim_idx
!=
-
1
)
{
if
(
in_size
>
0
)
{
// in_size < 0 and is un-determinate in compile time, skip the check,
// for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8],
// capacity = -24, in_size = -8, output_shape[0] = 0
// the following check will fail.
output_shape
[
unk_dim_idx
]
=
-
in_size
/
capacity
;
PADDLE_ENFORCE_EQ
(
output_shape
[
unk_dim_idx
]
*
capacity
,
-
in_size
,
"Invalid shape is given."
);
}
else
{
output_shape
[
unk_dim_idx
]
=
-
1
;
}
}
else
{
PADDLE_ENFORCE_EQ
(
capacity
,
in_size
,
"Invalid shape is given."
);
}
return
framework
::
make_ddim
(
output_shape
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
)
->
type
()),
ctx
.
device_context
());
}
};
class
ReshapeOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
...
...
@@ -107,64 +201,72 @@ class ReshapeGradOp : public framework::OperatorWithKernel {
}
};
void
ReshapeKernel
::
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
auto
*
in
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
class
ReshapeKernel
{
public:
void
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
out
=
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
auto
*
in
=
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
auto
*
shape_tensor
=
ctx
.
HasInput
(
"Shape"
)
?
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Shape"
)
:
nullptr
;
auto
*
shape_tensor
=
ctx
.
HasInput
(
"Shape"
)
?
ctx
.
Input
<
framework
::
LoDTensor
>
(
"Shape"
)
:
nullptr
;
framework
::
DDim
out_dims
=
out
->
dims
();
framework
::
DDim
out_dims
=
out
->
dims
();
if
(
shape_tensor
)
{
auto
*
shape_data
=
shape_tensor
->
data
<
int
>
();
framework
::
Tensor
cpu_shape_tensor
;
if
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()))
{
TensorCopySync
(
*
shape_tensor
,
platform
::
CPUPlace
(),
&
cpu_shape_tensor
);
shape_data
=
cpu_shape_tensor
.
data
<
int
>
();
if
(
shape_tensor
)
{
auto
*
shape_data
=
shape_tensor
->
data
<
int
>
();
framework
::
Tensor
cpu_shape_tensor
;
if
(
platform
::
is_gpu_place
(
ctx
.
GetPlace
()))
{
TensorCopySync
(
*
shape_tensor
,
platform
::
CPUPlace
(),
&
cpu_shape_tensor
);
shape_data
=
cpu_shape_tensor
.
data
<
int
>
();
}
auto
shape
=
std
::
vector
<
int
>
(
shape_data
,
shape_data
+
shape_tensor
->
numel
());
out_dims
=
ReshapeOp
::
ValidateShape
(
shape
,
in
->
dims
());
}
if
(
!
in
->
lod
().
empty
())
{
PADDLE_ENFORCE_EQ
(
out_dims
[
0
],
in
->
dims
()[
0
],
"Reshape operator cannot reshape an input sequence batch "
"into an output sequence batch that has a different "
"number of time steps. Please consider using "
"sequence_reshape op."
);
}
auto
shape
=
std
::
vector
<
int
>
(
shape_data
,
shape_data
+
shape_tensor
->
numel
());
out_dims
=
ReshapeOp
::
ValidateShape
(
shape
,
in
->
dims
());
}
if
(
!
in
->
lod
().
empty
())
{
PADDLE_ENFORCE_EQ
(
out_dims
[
0
],
in
->
dims
()[
0
],
"Reshape operator cannot reshape an input sequence batch "
"into an output sequence batch that has a different "
"number of time steps. Please consider using "
"sequence_reshape op."
);
}
bool
inplace
=
ctx
.
Attr
<
bool
>
(
"inplace"
);
out
->
Resize
(
out_dims
);
if
(
!
inplace
)
{
out
->
mutable_data
(
ctx
.
GetPlace
(),
in
->
type
());
framework
::
TensorCopySync
(
*
in
,
ctx
.
GetPlace
(),
out
);
out
->
Resize
(
out_dims
);
}
else
{
out
->
ShareDataWith
(
*
in
);
bool
inplace
=
ctx
.
Attr
<
bool
>
(
"inplace"
);
out
->
Resize
(
out_dims
);
if
(
!
inplace
)
{
out
->
mutable_data
(
ctx
.
GetPlace
(),
in
->
type
());
framework
::
TensorCopySync
(
*
in
,
ctx
.
GetPlace
(),
out
);
out
->
Resize
(
out_dims
);
}
else
{
out
->
ShareDataWith
(
*
in
);
out
->
Resize
(
out_dims
);
}
}
}
void
ReshapeGradKernel
::
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
d_out
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
d_x
->
mutable_data
(
ctx
.
GetPlace
(),
d_out
->
type
());
bool
inplace
=
ctx
.
Attr
<
bool
>
(
"inplace"
);
auto
in_dims
=
d_x
->
dims
();
if
(
!
inplace
)
{
framework
::
TensorCopy
(
*
d_out
,
ctx
.
GetPlace
(),
ctx
.
device_context
(),
d_x
);
ctx
.
device_context
().
Wait
();
d_x
->
Resize
(
in_dims
);
}
else
{
d_x
->
ShareDataWith
(
*
d_out
);
d_x
->
Resize
(
in_dims
);
};
class
ReshapeGradKernel
{
public:
void
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
*
d_out
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
d_x
->
mutable_data
(
ctx
.
GetPlace
(),
d_out
->
type
());
bool
inplace
=
ctx
.
Attr
<
bool
>
(
"inplace"
);
auto
in_dims
=
d_x
->
dims
();
if
(
!
inplace
)
{
framework
::
TensorCopy
(
*
d_out
,
ctx
.
GetPlace
(),
ctx
.
device_context
(),
d_x
);
ctx
.
device_context
().
Wait
();
d_x
->
Resize
(
in_dims
);
}
else
{
d_x
->
ShareDataWith
(
*
d_out
);
d_x
->
Resize
(
in_dims
);
}
}
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
...
...
@@ -179,3 +281,13 @@ REGISTER_OP_CPU_KERNEL_FUNCTOR(reshape_grad, float, ops::ReshapeGradKernel,
double
,
ops
::
ReshapeGradKernel
,
int
,
ops
::
ReshapeGradKernel
,
int64_t
,
ops
::
ReshapeGradKernel
);
#ifdef PADDLE_WITH_CUDA
REGISTER_OP_CUDA_KERNEL_FUNCTOR
(
reshape
,
float
,
ops
::
ReshapeKernel
,
double
,
ops
::
ReshapeKernel
,
int
,
ops
::
ReshapeKernel
,
int64_t
,
ops
::
ReshapeKernel
);
REGISTER_OP_CUDA_KERNEL_FUNCTOR
(
reshape_grad
,
float
,
ops
::
ReshapeGradKernel
,
double
,
ops
::
ReshapeGradKernel
,
int
,
ops
::
ReshapeGradKernel
,
int64_t
,
ops
::
ReshapeGradKernel
);
#endif
paddle/fluid/operators/reshape_op.cu.cc
已删除
100644 → 0
浏览文件 @
6038a631
/* 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/reshape_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL_FUNCTOR
(
reshape
,
float
,
ops
::
ReshapeKernel
,
double
,
ops
::
ReshapeKernel
,
int
,
ops
::
ReshapeKernel
,
int64_t
,
ops
::
ReshapeKernel
);
REGISTER_OP_CUDA_KERNEL_FUNCTOR
(
reshape_grad
,
float
,
ops
::
ReshapeGradKernel
,
double
,
ops
::
ReshapeGradKernel
,
int
,
ops
::
ReshapeGradKernel
,
int64_t
,
ops
::
ReshapeGradKernel
);
paddle/fluid/operators/reshape_op.h
已删除
100644 → 0
浏览文件 @
6038a631
/* 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 <string>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
ReshapeOp
:
public
framework
::
OperatorWithKernel
{
public:
ReshapeOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of ReshapeOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of ReshapeOp should not be null."
);
const
std
::
vector
<
int
>
&
shape
=
ctx
->
Attrs
().
Get
<
std
::
vector
<
int
>>
(
"shape"
);
PADDLE_ENFORCE
(
!
shape
.
empty
(),
"The shape information must be set by Attr(shape)."
);
if
(
ctx
->
HasInput
(
"Shape"
)
&&
ctx
->
IsRuntime
())
{
// If true, set the shape of Output(Out) according to Input(Shape) in
// ReshapeKernel with ExecutionContext. Also check LoD in ReshapeKernel.
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
return
;
}
auto
x_dims
=
ctx
->
GetInputDim
(
"X"
);
auto
out_dims
=
ValidateShape
(
shape
,
x_dims
);
ctx
->
SetOutputDim
(
"Out"
,
out_dims
);
if
(
x_dims
[
0
]
==
out_dims
[
0
])
{
// Only pass LoD when the first dimension of output and Input(X)
// are the same.
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
}
static
framework
::
DDim
ValidateShape
(
const
std
::
vector
<
int
>
shape
,
const
framework
::
DDim
&
in_dims
)
{
const
int64_t
in_size
=
framework
::
product
(
in_dims
);
// only one dimension can be set to -1, whose size will be automatically
// infered.
const
int64_t
unk_dim_val
=
-
1
;
const
int64_t
copy_dim_val
=
0
;
std
::
vector
<
int64_t
>
output_shape
(
shape
.
size
(),
0
);
int64_t
capacity
=
1
;
int
unk_dim_idx
=
-
1
;
for
(
size_t
i
=
0
;
i
<
shape
.
size
();
++
i
)
{
if
(
shape
[
i
]
==
unk_dim_val
)
{
PADDLE_ENFORCE
(
unk_dim_idx
==
-
1
,
"Only one input dimension of Attr(shape) can be unknown."
);
unk_dim_idx
=
i
;
}
else
if
(
shape
[
i
]
==
copy_dim_val
)
{
PADDLE_ENFORCE
(
static_cast
<
int
>
(
i
)
<
in_dims
.
size
(),
"The index of dimension to copy from input shape must be less "
"than the size of input shape."
);
}
else
{
PADDLE_ENFORCE
(
shape
[
i
]
>
0
,
"Each input dimension of Attr(shape) must not be negtive except "
"one unknown dimension."
);
}
capacity
*=
(
shape
[
i
]
?
shape
[
i
]
:
in_dims
[
i
]);
output_shape
[
i
]
=
(
shape
[
i
]
?
static_cast
<
int64_t
>
(
shape
[
i
])
:
in_dims
[
i
]);
}
if
(
unk_dim_idx
!=
-
1
)
{
if
(
in_size
>
0
)
{
// in_size < 0 and is un-determinate in compile time, skip the check,
// for example, in_dims = [-1, 8, 1, 1], shape = [-1, 3, 8],
// capacity = -24, in_size = -8, output_shape[0] = 0
// the following check will fail.
output_shape
[
unk_dim_idx
]
=
-
in_size
/
capacity
;
PADDLE_ENFORCE_EQ
(
output_shape
[
unk_dim_idx
]
*
capacity
,
-
in_size
,
"Invalid shape is given."
);
}
else
{
output_shape
[
unk_dim_idx
]
=
-
1
;
}
}
else
{
PADDLE_ENFORCE_EQ
(
capacity
,
in_size
,
"Invalid shape is given."
);
}
return
framework
::
make_ddim
(
output_shape
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
framework
::
ToDataType
(
ctx
.
Input
<
framework
::
LoDTensor
>
(
"X"
)
->
type
()),
ctx
.
device_context
());
}
};
class
ReshapeKernel
{
public:
void
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
;
};
class
ReshapeGradKernel
{
public:
void
operator
()(
const
framework
::
ExecutionContext
&
ctx
)
const
;
};
}
// namespace operators
}
// namespace paddle
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