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a481c5e9
编写于
8月 27, 2018
作者:
T
tensor-tang
浏览文件
操作
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差异文件
Merge remote-tracking branch 'ups/develop' into feature/op/fusion_expand_concat_fc
上级
49c31feb
ef7bd03a
变更
19
隐藏空白更改
内联
并排
Showing
19 changed file
with
578 addition
and
101 deletion
+578
-101
paddle/fluid/API.spec
paddle/fluid/API.spec
+1
-1
paddle/fluid/framework/data_type.cc
paddle/fluid/framework/data_type.cc
+1
-0
paddle/fluid/framework/data_type.h
paddle/fluid/framework/data_type.h
+3
-0
paddle/fluid/framework/framework.proto
paddle/fluid/framework/framework.proto
+1
-0
paddle/fluid/operators/math/concat.cu
paddle/fluid/operators/math/concat.cu
+6
-0
paddle/fluid/operators/math/math_function.cc
paddle/fluid/operators/math/math_function.cc
+2
-1
paddle/fluid/operators/math/math_function.cu
paddle/fluid/operators/math/math_function.cu
+5
-4
paddle/fluid/operators/math/padding.h
paddle/fluid/operators/math/padding.h
+124
-0
paddle/fluid/operators/pad_constant_like_op.cc
paddle/fluid/operators/pad_constant_like_op.cc
+196
-0
paddle/fluid/operators/pad_constant_like_op.cu
paddle/fluid/operators/pad_constant_like_op.cu
+27
-0
paddle/fluid/operators/pad_constant_like_op.h
paddle/fluid/operators/pad_constant_like_op.h
+93
-0
paddle/fluid/operators/pad_op.h
paddle/fluid/operators/pad_op.h
+20
-93
paddle/fluid/pybind/protobuf.cc
paddle/fluid/pybind/protobuf.cc
+1
-0
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+3
-0
paddle/fluid/pybind/tensor_py.h
paddle/fluid/pybind/tensor_py.h
+1
-1
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+2
-0
python/paddle/fluid/tests/unittests/test_pad_constant_like.py
...on/paddle/fluid/tests/unittests/test_pad_constant_like.py
+69
-0
python/paddle/fluid/tests/unittests/test_tensor.py
python/paddle/fluid/tests/unittests/test_tensor.py
+21
-0
python/paddle/fluid/tests/unittests/test_variable.py
python/paddle/fluid/tests/unittests/test_variable.py
+2
-1
未找到文件。
paddle/fluid/API.spec
浏览文件 @
a481c5e9
...
...
@@ -378,7 +378,7 @@ paddle.fluid.LoDTensor.__init__ 1. __init__(self: paddle.fluid.core.LoDTensor, a
paddle.fluid.LoDTensor.has_valid_recursive_sequence_lengths has_valid_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> bool
paddle.fluid.LoDTensor.lod lod(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.recursive_sequence_lengths recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor) -> List[List[int]]
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[
float32], arg1: paddle::platform::CUDAPlace) -> None 9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None 10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None 11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None 12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None 13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None 14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None 15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None 16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None 17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None 18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None 19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None 20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None 21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[u
int8], arg1: paddle::platform::CUDAPinnedPlace) -> None
paddle.fluid.LoDTensor.set 1. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CPUPlace) -> None 2. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CPUPlace) -> None 3. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CPUPlace) -> None 4. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CPUPlace) -> None 5. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CPUPlace) -> None 6. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CPUPlace) -> None 7. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CPUPlace) -> None 8. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[
int8], arg1: paddle::platform::CPUPlace) -> None 9. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPlace) -> None 10. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPlace) -> None 11. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPlace) -> None 12. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPlace) -> None 13. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPlace) -> None 14. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPlace) -> None 15. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPlace) -> None 16. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int8], arg1: paddle::platform::CUDAPlace) -> None 17. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float32], arg1: paddle::platform::CUDAPinnedPlace) -> None 18. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int32], arg1: paddle::platform::CUDAPinnedPlace) -> None 19. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[float64], arg1: paddle::platform::CUDAPinnedPlace) -> None 20. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[int64], arg1: paddle::platform::CUDAPinnedPlace) -> None 21. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[bool], arg1: paddle::platform::CUDAPinnedPlace) -> None 22. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint16], arg1: paddle::platform::CUDAPinnedPlace) -> None 23. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[uint8], arg1: paddle::platform::CUDAPinnedPlace) -> None 24. set(self: paddle.fluid.core.Tensor, arg0: numpy.ndarray[
int8], arg1: paddle::platform::CUDAPinnedPlace) -> None
paddle.fluid.LoDTensor.set_lod set_lod(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
paddle.fluid.LoDTensor.set_recursive_sequence_lengths set_recursive_sequence_lengths(self: paddle.fluid.core.LoDTensor, arg0: List[List[int]]) -> None
paddle.fluid.LoDTensor.shape shape(self: paddle.fluid.core.Tensor) -> List[int]
...
...
paddle/fluid/framework/data_type.cc
浏览文件 @
a481c5e9
...
...
@@ -64,6 +64,7 @@ static DataTypeMap* InitDataTypeMap() {
RegType
(
size_t
,
proto
::
VarType
::
SIZE_T
);
RegType
(
int16_t
,
proto
::
VarType
::
INT16
);
RegType
(
uint8_t
,
proto
::
VarType
::
UINT8
);
RegType
(
int8_t
,
proto
::
VarType
::
INT8
);
#undef RegType
return
retv
;
...
...
paddle/fluid/framework/data_type.h
浏览文件 @
a481c5e9
...
...
@@ -54,6 +54,9 @@ inline void VisitDataType(proto::VarType::Type type, Visitor visitor) {
case
proto
::
VarType
::
INT16
:
visitor
.
template
operator
()
<
int16_t
>();
break
;
case
proto
::
VarType
::
INT8
:
visitor
.
template
operator
()
<
int8_t
>();
break
;
default:
PADDLE_THROW
(
"Not supported %d"
,
type
);
}
...
...
paddle/fluid/framework/framework.proto
浏览文件 @
a481c5e9
...
...
@@ -107,6 +107,7 @@ message VarType {
// Tensor<size_t> is used in C++.
SIZE_T
=
19
;
UINT8
=
20
;
INT8
=
21
;
// Other types that may need additional descriptions
LOD_TENSOR
=
7
;
...
...
paddle/fluid/operators/math/concat.cu
浏览文件 @
a481c5e9
...
...
@@ -177,6 +177,9 @@ class ConcatFunctor<platform::CUDADeviceContext, T> {
dev_ins_data
,
dev_ins_col_data
,
static_cast
<
int
>
(
inputs_col
.
size
()),
out_row
,
out_col
,
output
->
data
<
T
>
());
}
// Wait() must be called because `inputs_data` may be destructed before
// kernel ends
context
.
Wait
();
}
};
...
...
@@ -252,6 +255,9 @@ class ConcatGradFunctor<platform::CUDADeviceContext, T> {
input
.
data
<
T
>
(),
in_row
,
in_col
,
dev_outs_col_data
,
static_cast
<
int
>
(
outputs_cols
.
size
()),
dev_out_gpu_data
);
}
// Wait() must be called because `outputs_data` may be destructed before
// kernel ends
context
.
Wait
();
}
};
...
...
paddle/fluid/operators/math/math_function.cc
浏览文件 @
a481c5e9
...
...
@@ -41,7 +41,8 @@ template struct SetConstant<platform::CPUDeviceContext, uint8_t>;
template struct Transpose<platform::CPUDeviceContext, int64_t, RANK>; \
template struct Transpose<platform::CPUDeviceContext, bool, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int16_t, RANK>; \
template struct Transpose<platform::CPUDeviceContext, uint8_t, RANK>;
template struct Transpose<platform::CPUDeviceContext, uint8_t, RANK>; \
template struct Transpose<platform::CPUDeviceContext, int8_t, RANK>;
DEFINE_CPU_TRANS
(
1
);
DEFINE_CPU_TRANS
(
2
);
...
...
paddle/fluid/operators/math/math_function.cu
浏览文件 @
a481c5e9
...
...
@@ -33,10 +33,11 @@ template struct SetConstant<platform::CUDADeviceContext, int>;
template
struct
SetConstant
<
platform
::
CUDADeviceContext
,
int64_t
>;
template
struct
SetConstant
<
platform
::
CUDADeviceContext
,
bool
>;
#define DEFINE_GPU_TRANS(RANK) \
template struct Transpose<platform::CUDADeviceContext, float, RANK>; \
template struct Transpose<platform::CUDADeviceContext, double, RANK>; \
template struct Transpose<platform::CUDADeviceContext, float16, RANK>;
#define DEFINE_GPU_TRANS(RANK) \
template struct Transpose<platform::CUDADeviceContext, float, RANK>; \
template struct Transpose<platform::CUDADeviceContext, double, RANK>; \
template struct Transpose<platform::CUDADeviceContext, float16, RANK>; \
template struct Transpose<platform::CUDADeviceContext, int8_t, RANK>;
DEFINE_GPU_TRANS
(
1
);
DEFINE_GPU_TRANS
(
2
);
...
...
paddle/fluid/operators/math/padding.h
0 → 100644
浏览文件 @
a481c5e9
/* Copyright (c) 2018 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 <utility>
#include <vector>
#include "paddle/fluid/framework/tensor.h"
namespace
paddle
{
namespace
operators
{
namespace
math
{
template
<
typename
T
,
size_t
D
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
template
<
typename
DeviceContext
,
typename
T
,
size_t
D
>
void
PadFunction
(
const
framework
::
ExecutionContext
&
context
,
const
std
::
vector
<
int
>&
pads
,
const
framework
::
Tensor
&
src
,
T
pad_value
,
framework
::
Tensor
*
out
)
{
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
pads
[
i
*
2
];
paddings
[
i
].
second
=
pads
[
i
*
2
+
1
];
}
auto
src_tensor
=
EigenTensor
<
T
,
D
>::
From
(
src
);
auto
out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
out
);
auto
&
place
=
*
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
out_tensor
.
device
(
place
)
=
src_tensor
.
pad
(
paddings
,
pad_value
);
}
template
<
typename
DeviceContext
,
typename
T
,
size_t
D
>
void
PadGradFunction
(
const
framework
::
ExecutionContext
&
context
,
const
std
::
vector
<
int
>&
pads
,
const
framework
::
Tensor
&
src
,
framework
::
Tensor
*
d_out
)
{
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
-
pads
[
i
*
2
];
paddings
[
i
].
second
=
-
pads
[
i
*
2
+
1
];
}
auto
d_out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
d_out
);
auto
src_tensor
=
EigenTensor
<
T
,
D
>::
From
(
src
);
auto
&
place
=
*
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
d_out_tensor
.
device
(
place
)
=
src_tensor
.
pad
(
paddings
,
0
);
}
template
<
typename
DeviceContext
,
typename
T
>
void
PaddingFunctor
(
int
rank
,
const
framework
::
ExecutionContext
&
context
,
const
std
::
vector
<
int
>&
pads
,
T
pad_value
,
const
framework
::
Tensor
&
src
,
framework
::
Tensor
*
out
)
{
switch
(
rank
)
{
case
1
:
PadFunction
<
DeviceContext
,
T
,
1
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
case
2
:
PadFunction
<
DeviceContext
,
T
,
2
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
case
3
:
PadFunction
<
DeviceContext
,
T
,
3
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
case
4
:
PadFunction
<
DeviceContext
,
T
,
4
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
case
5
:
PadFunction
<
DeviceContext
,
T
,
5
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
case
6
:
PadFunction
<
DeviceContext
,
T
,
6
>
(
context
,
pads
,
src
,
pad_value
,
out
);
break
;
default:
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
}
}
template
<
typename
DeviceContext
,
typename
T
>
void
PaddingGradFunctor
(
int
rank
,
const
framework
::
ExecutionContext
&
context
,
const
std
::
vector
<
int
>&
pads
,
const
framework
::
Tensor
&
src
,
framework
::
Tensor
*
out
)
{
switch
(
rank
)
{
case
1
:
PadGradFunction
<
DeviceContext
,
T
,
1
>
(
context
,
pads
,
src
,
out
);
break
;
case
2
:
PadGradFunction
<
DeviceContext
,
T
,
2
>
(
context
,
pads
,
src
,
out
);
break
;
case
3
:
PadGradFunction
<
DeviceContext
,
T
,
3
>
(
context
,
pads
,
src
,
out
);
break
;
case
4
:
PadGradFunction
<
DeviceContext
,
T
,
4
>
(
context
,
pads
,
src
,
out
);
break
;
case
5
:
PadGradFunction
<
DeviceContext
,
T
,
5
>
(
context
,
pads
,
src
,
out
);
break
;
case
6
:
PadGradFunction
<
DeviceContext
,
T
,
6
>
(
context
,
pads
,
src
,
out
);
break
;
default:
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
}
}
}
// namespace math
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/pad_constant_like_op.cc
0 → 100644
浏览文件 @
a481c5e9
/* Copyright (c) 2018 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/pad_constant_like_op.h"
namespace
paddle
{
namespace
operators
{
using
framework
::
Tensor
;
class
PadConstantLikeOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of PadConstantLikeOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
),
"Input(Y) of PadConstantLikeOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of PadConstantLikeOp should not be null."
);
auto
x_dim
=
ctx
->
GetInputDim
(
"X"
);
auto
y_dim
=
ctx
->
GetInputDim
(
"Y"
);
PADDLE_ENFORCE_EQ
(
x_dim
.
size
(),
y_dim
.
size
(),
"The dimention of X and Y should be the same."
);
for
(
int
i
=
0
;
i
<
x_dim
.
size
();
++
i
)
{
PADDLE_ENFORCE_GE
(
x_dim
[
i
],
y_dim
[
i
]);
}
ctx
->
SetOutputDim
(
"Out"
,
x_dim
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
}
};
class
PadConstantLikeOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"The input of pad_constant_like op. "
"The input should be a k-D tensor(k > 0 and k < 7)"
);
AddInput
(
"Y"
,
"The input of pad_constant_like op. "
"The input should be a k-D tensor(k > 0 and k < 7)"
);
AddOutput
(
"Out"
,
"The output of pad_constant_like op. "
"A tensor with the same shape as X."
);
AddAttr
<
float
>
(
"pad_value"
,
"(float, default 0.0) "
"The value to fill the padded areas."
)
.
SetDefault
(
0.0
f
);
AddComment
(
R"DOC(
PadConstantLikeOp Operator.
Pad input(Y) with a pad_value, the number of values padded to the edges of each
axis is specified by the difference of the shape of X and Y.
((0, shape_x_0 - shape_y_0), … (0, shape_x_n - shape_y_n)) unique pad widths for
each axis.
The input should be a k-D tensor(k > 0 and k < 7). As an example:
case1:
Given:
X = [[1, 2],
[3, 4],
[1, 2],
[3, 4]]],
X.shape = (4, 2)
Y = [[5, 6],
[7, 8]],
Y.shape = (2, 2)
And
pad_value = 0,
Return:
Out = [[5, 6],
[7, 8],
[0, 0],
[0, 0]]
Out.shape = (4, 2)
case2:
Given:
X = [[[[ 0, 1, 2],
[ 3, 4, 5]],
[[ 6, 7, 8],
[ 9, 10, 11]],
[[12, 13, 14],
[15, 16, 17]]],
[[[18, 19, 20],
[21, 22, 23]],
[[24, 25, 26],
[27, 28, 29]],
[[30, 31, 32],
[33, 34, 35]]]]
X.shape = (2, 3, 2, 3)
Y = [[[[35, 36, 37]],
[[38, 39, 40]],
[[41, 42, 43]]]]
Y.shape = (1, 3, 1, 3)
And
pad_value = -1,
Return:
Out = [[[[35, 36, 37],
[-1, -1, -1]],
[[38, 39, 40],
[-1, -1, -1]],
[[41, 42, 43],
[-1, -1, -1]]],
[[[-1, -1, -1],
[-1, -1, -1]],
[[-1, -1, -1],
[-1, -1, -1]],
[[-1, -1, -1],
[-1, -1, -1]]]]
Out.shape = (2, 3, 2, 3)
)DOC"
);
}
};
class
PadConstantLikeOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Y"
),
"Input(Y) should not be null"
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null"
);
auto
y_dim
=
ctx
->
GetInputDim
(
"Y"
);
auto
dout_dim
=
ctx
->
GetInputDim
(
framework
::
GradVarName
(
"Out"
));
PADDLE_ENFORCE_EQ
(
dout_dim
.
size
(),
y_dim
.
size
(),
"The dimention of X and Y should be the same."
);
auto
y_grad_name
=
framework
::
GradVarName
(
"Y"
);
if
(
ctx
->
HasOutput
(
y_grad_name
))
{
ctx
->
SetOutputDim
(
y_grad_name
,
y_dim
);
ctx
->
ShareLoD
(
"Y"
,
/*->*/
y_grad_name
);
for
(
int
i
=
0
;
i
<
y_dim
.
size
();
++
i
)
{
PADDLE_ENFORCE_GE
(
dout_dim
[
i
],
y_dim
[
i
]);
}
}
}
};
class
PadConstantLikeOpGradMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
std
::
unique_ptr
<
framework
::
OpDesc
>
Apply
()
const
override
{
auto
*
bind
=
new
framework
::
OpDesc
();
bind
->
SetType
(
"pad_constant_like_grad"
);
bind
->
SetInput
(
"Y"
,
Input
(
"Y"
));
bind
->
SetInput
(
framework
::
GradVarName
(
"Out"
),
OutputGrad
(
"Out"
));
bind
->
SetOutput
(
framework
::
GradVarName
(
"Y"
),
InputGrad
(
"Y"
));
bind
->
SetAttrMap
(
Attrs
());
return
std
::
unique_ptr
<
framework
::
OpDesc
>
(
bind
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
pad_constant_like
,
ops
::
PadConstantLikeOp
,
ops
::
PadConstantLikeOpMaker
,
ops
::
PadConstantLikeOpGradMaker
);
REGISTER_OPERATOR
(
pad_constant_like_grad
,
ops
::
PadConstantLikeOpGrad
);
REGISTER_OP_CPU_KERNEL
(
pad_constant_like
,
ops
::
PadConstantLikeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
PadConstantLikeKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
REGISTER_OP_CPU_KERNEL
(
pad_constant_like_grad
,
ops
::
PadConstantLikeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
PadConstantLikeGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
);
paddle/fluid/operators/pad_constant_like_op.cu
0 → 100644
浏览文件 @
a481c5e9
/* Copyright (c) 2018 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. */
#define EIGEN_USE_GPU
#include "paddle/fluid/operators/pad_constant_like_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
pad_constant_like
,
ops
::
PadConstantLikeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
PadConstantLikeKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
REGISTER_OP_CUDA_KERNEL
(
pad_constant_like_grad
,
ops
::
PadConstantLikeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
PadConstantLikeGradKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
);
paddle/fluid/operators/pad_constant_like_op.h
0 → 100644
浏览文件 @
a481c5e9
/* Copyright (c) 2018 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 <utility>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/tensor.h"
#include "paddle/fluid/framework/tensor_util.h"
#include "paddle/fluid/operators/math/padding.h"
namespace
paddle
{
namespace
operators
{
template
<
typename
DeviceContext
,
typename
T
>
class
PadConstantLikeKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
in_x
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
in_y
=
context
.
Input
<
framework
::
Tensor
>
(
"Y"
);
auto
*
out
=
context
.
Output
<
framework
::
Tensor
>
(
"Out"
);
if
(
in_x
->
dims
()
==
in_y
->
dims
())
{
// TensorCopy(in_y, context.GetPlace(), context, out);
out
->
ShareDataWith
(
*
in_y
);
return
;
}
T
pad_value
=
context
.
Attr
<
T
>
(
"pad_value"
);
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
rank
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
)
->
dims
().
size
();
std
::
vector
<
int
>
pads
(
rank
*
2
,
0
);
for
(
int
j
=
0
;
j
<
rank
;
++
j
)
{
pads
[
j
*
2
]
=
0
;
pads
[
j
*
2
+
1
]
=
static_cast
<
int
>
(
in_x
->
dims
()[
j
]
-
in_y
->
dims
()[
j
]);
}
math
::
PaddingFunctor
<
DeviceContext
,
T
>
(
rank
,
context
,
pads
,
pad_value
,
*
in_y
,
out
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
PadConstantLikeGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
in_y
=
context
.
Input
<
framework
::
Tensor
>
(
"Y"
);
auto
in_dout
=
context
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_y
=
context
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
if
(
d_y
==
nullptr
)
{
return
;
}
if
(
in_dout
->
dims
()
==
in_y
->
dims
())
{
// TensorCopy(in_dout, context.GetPlace(), context, d_y);
d_y
->
ShareDataWith
(
*
in_dout
);
return
;
}
d_y
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
rank
=
in_dout
->
dims
().
size
();
std
::
vector
<
int
>
pads
(
static_cast
<
size_t
>
(
rank
)
*
2
,
0
);
for
(
int
j
=
0
;
j
<
rank
;
++
j
)
{
pads
[
j
*
2
]
=
0
;
pads
[
j
*
2
+
1
]
=
static_cast
<
int
>
(
in_dout
->
dims
()[
j
]
-
in_y
->
dims
()[
j
]);
}
math
::
PaddingGradFunctor
<
DeviceContext
,
T
>
(
rank
,
context
,
pads
,
*
in_dout
,
d_y
);
}
};
}
// namespace operators
}
// namespace paddle
paddle/fluid/operators/pad_op.h
浏览文件 @
a481c5e9
...
...
@@ -18,117 +18,44 @@ limitations under the License. */
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/operators/math/padding.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
,
size_t
D
,
int
MajorType
=
Eigen
::
RowMajor
,
typename
IndexType
=
Eigen
::
DenseIndex
>
using
EigenTensor
=
framework
::
EigenTensor
<
T
,
D
,
MajorType
,
IndexType
>
;
template
<
typename
DeviceContext
,
typename
T
,
size_t
D
>
void
PadFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
pads
[
i
*
2
];
paddings
[
i
].
second
=
pads
[
i
*
2
+
1
];
}
T
pad_value
=
context
.
Attr
<
T
>
(
"pad_value"
);
auto
*
x
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
x_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
x
);
auto
out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
out
);
auto
&
place
=
*
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
out_tensor
.
device
(
place
)
=
x_tensor
.
pad
(
paddings
,
pad_value
);
}
template
<
typename
DeviceContext
,
typename
T
>
class
PadKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
int
rank
=
context
.
Input
<
Tensor
>
(
"X"
)
->
dims
().
size
();
switch
(
rank
)
{
case
1
:
PadFunction
<
DeviceContext
,
T
,
1
>
(
context
);
break
;
case
2
:
PadFunction
<
DeviceContext
,
T
,
2
>
(
context
);
break
;
case
3
:
PadFunction
<
DeviceContext
,
T
,
3
>
(
context
);
break
;
case
4
:
PadFunction
<
DeviceContext
,
T
,
4
>
(
context
);
break
;
case
5
:
PadFunction
<
DeviceContext
,
T
,
5
>
(
context
);
break
;
case
6
:
PadFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
}
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
T
pad_value
=
context
.
Attr
<
T
>
(
"pad_value"
);
auto
*
x
=
context
.
Input
<
Tensor
>
(
"X"
);
auto
*
out
=
context
.
Output
<
Tensor
>
(
"Out"
);
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
rank
=
x
->
dims
().
size
();
math
::
PaddingFunctor
<
DeviceContext
,
T
>
(
rank
,
context
,
pads
,
pad_value
,
*
x
,
out
);
}
};
template
<
typename
DeviceContext
,
typename
T
,
size_t
D
>
void
PadGradFunction
(
const
framework
::
ExecutionContext
&
context
)
{
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
Eigen
::
array
<
std
::
pair
<
int
,
int
>
,
D
>
paddings
;
for
(
size_t
i
=
0
;
i
<
paddings
.
size
();
++
i
)
{
paddings
[
i
].
first
=
-
pads
[
i
*
2
];
paddings
[
i
].
second
=
-
pads
[
i
*
2
+
1
];
}
auto
*
d_out
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
if
(
d_x
!=
nullptr
)
{
d_x
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
d_x_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
d_x
);
auto
d_out_tensor
=
EigenTensor
<
T
,
D
>::
From
(
*
d_out
);
auto
&
place
=
*
context
.
template
device_context
<
DeviceContext
>().
eigen_device
();
d_x_tensor
.
device
(
place
)
=
d_out_tensor
.
pad
(
paddings
,
0
);
}
}
template
<
typename
DeviceContext
,
typename
T
>
class
PadGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
size_t
rank
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
().
size
();
switch
(
rank
)
{
case
1
:
PadGradFunction
<
DeviceContext
,
T
,
1
>
(
context
);
break
;
case
2
:
PadGradFunction
<
DeviceContext
,
T
,
2
>
(
context
);
break
;
case
3
:
PadGradFunction
<
DeviceContext
,
T
,
3
>
(
context
);
break
;
case
4
:
PadGradFunction
<
DeviceContext
,
T
,
4
>
(
context
);
break
;
case
5
:
PadGradFunction
<
DeviceContext
,
T
,
5
>
(
context
);
break
;
case
6
:
PadGradFunction
<
DeviceContext
,
T
,
6
>
(
context
);
break
;
default:
PADDLE_THROW
(
"PadOp only support tensors with no more than 6 dimensions."
);
auto
pads
=
context
.
Attr
<
std
::
vector
<
int
>>
(
"paddings"
);
auto
*
d_out
=
context
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
));
auto
*
d_x
=
context
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
if
(
d_x
==
nullptr
)
{
return
;
}
d_x
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
rank
=
d_out
->
dims
().
size
();
math
::
PaddingGradFunctor
<
DeviceContext
,
T
>
(
rank
,
context
,
pads
,
*
d_out
,
d_x
);
}
};
...
...
paddle/fluid/pybind/protobuf.cc
浏览文件 @
a481c5e9
...
...
@@ -234,6 +234,7 @@ void BindVarDsec(pybind11::module *m) {
pybind11
::
enum_
<
pd
::
proto
::
VarType
::
Type
>
(
var_desc
,
"VarType"
,
""
)
.
value
(
"BOOL"
,
pd
::
proto
::
VarType
::
BOOL
)
.
value
(
"UINT8"
,
pd
::
proto
::
VarType
::
UINT8
)
.
value
(
"INT8"
,
pd
::
proto
::
VarType
::
INT8
)
.
value
(
"INT16"
,
pd
::
proto
::
VarType
::
INT16
)
.
value
(
"INT32"
,
pd
::
proto
::
VarType
::
INT32
)
.
value
(
"INT64"
,
pd
::
proto
::
VarType
::
INT64
)
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
a481c5e9
...
...
@@ -130,6 +130,7 @@ PYBIND11_PLUGIN(core) {
.
def
(
"set"
,
PyCPUTensorSetFromArray
<
bool
>
)
.
def
(
"set"
,
PyCPUTensorSetFromArray
<
uint16_t
>
)
.
def
(
"set"
,
PyCPUTensorSetFromArray
<
uint8_t
>
)
.
def
(
"set"
,
PyCPUTensorSetFromArray
<
int8_t
>
)
#ifdef PADDLE_WITH_CUDA
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
float
>
)
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
int
>
)
...
...
@@ -138,6 +139,7 @@ PYBIND11_PLUGIN(core) {
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
bool
>
)
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
uint16_t
>
)
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
uint8_t
>
)
.
def
(
"set"
,
PyCUDATensorSetFromArray
<
int8_t
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
float
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
int
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
double
>
)
...
...
@@ -145,6 +147,7 @@ PYBIND11_PLUGIN(core) {
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
bool
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
uint16_t
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
uint8_t
>
)
.
def
(
"set"
,
PyCUDAPinnedTensorSetFromArray
<
int8_t
>
)
#endif
.
def
(
"shape"
,
[](
Tensor
&
self
)
{
return
vectorize
(
self
.
dims
());
})
.
def
(
"_set_float_element"
,
TensorSetElement
<
float
>
)
...
...
paddle/fluid/pybind/tensor_py.h
浏览文件 @
a481c5e9
...
...
@@ -97,7 +97,7 @@ struct CastToPyBufferImpl<true, I, ARGS...> {
inline
pybind11
::
buffer_info
CastToPyBuffer
(
const
framework
::
Tensor
&
tensor
)
{
auto
buffer_info
=
details
::
CastToPyBufferImpl
<
true
,
0
,
float
,
int
,
double
,
int64_t
,
bool
,
uint8_t
,
platform
::
float16
>
()(
tensor
);
uint8_t
,
int8_t
,
platform
::
float16
>
()(
tensor
);
return
buffer_info
;
}
...
...
python/paddle/fluid/framework.py
浏览文件 @
a481c5e9
...
...
@@ -95,6 +95,8 @@ def convert_np_dtype_to_dtype_(np_dtype):
return
core
.
VarDesc
.
VarType
.
INT16
elif
dtype
==
np
.
uint8
:
return
core
.
VarDesc
.
VarType
.
UINT8
elif
dtype
==
np
.
int8
:
return
core
.
VarDesc
.
VarType
.
INT8
else
:
raise
ValueError
(
"Not supported numpy dtype %s"
%
dtype
)
...
...
python/paddle/fluid/tests/unittests/test_pad_constant_like.py
0 → 100644
浏览文件 @
a481c5e9
# Copyright (c) 2018 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
__future__
import
print_function
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
class
TestPadOp
(
OpTest
):
def
setUp
(
self
):
self
.
initTestCase
()
self
.
op_type
=
"pad_constant_like"
self
.
inputs
=
{
'X'
:
np
.
random
.
random
(
self
.
x_shape
).
astype
(
"float32"
),
'Y'
:
np
.
random
.
random
(
self
.
y_shape
).
astype
(
"float32"
)
}
self
.
attrs
=
{}
self
.
attrs
[
'pad_value'
]
=
self
.
pad_value
self
.
outputs
=
{
'Out'
:
np
.
pad
(
self
.
inputs
[
'Y'
],
self
.
paddings
,
mode
=
'constant'
,
constant_values
=
self
.
pad_value
)
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad_normal
(
self
):
self
.
check_grad
([
'Y'
],
'Out'
,
max_relative_error
=
0.006
)
def
initTestCase
(
self
):
self
.
x_shape
=
(
16
,
16
)
self
.
y_shape
=
(
3
,
16
)
self
.
pad_value
=
0.1
self
.
paddings
=
[(
0
,
13
),
(
0
,
0
)]
class
TestCase1
(
TestPadOp
):
def
initTestCase
(
self
):
self
.
x_shape
=
(
4
,
3
,
4
,
4
)
self
.
y_shape
=
(
2
,
3
,
4
,
4
)
self
.
paddings
=
[(
0
,
2
),
(
0
,
0
),
(
0
,
0
),
(
0
,
0
)]
self
.
pad_value
=
0.5
class
TestCase2
(
TestPadOp
):
def
initTestCase
(
self
):
self
.
x_shape
=
(
4
,
3
,
4
,
4
)
self
.
y_shape
=
(
2
,
3
,
2
,
4
)
self
.
paddings
=
[(
0
,
2
),
(
0
,
0
),
(
0
,
2
),
(
0
,
0
)]
self
.
pad_value
=
0.5
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/fluid/tests/unittests/test_tensor.py
浏览文件 @
a481c5e9
...
...
@@ -59,6 +59,27 @@ class TestTensor(unittest.TestCase):
self
.
assertAlmostEqual
(
1.0
,
tensor_array_2
[
3
,
9
])
self
.
assertAlmostEqual
(
2.0
,
tensor_array_2
[
19
,
11
])
def
test_int8_tensor
(
self
):
scope
=
core
.
Scope
()
var
=
scope
.
var
(
"int8_tensor"
)
cpu_tensor
=
var
.
get_tensor
()
tensor_array
=
numpy
.
random
.
randint
(
-
127
,
high
=
128
,
size
=
[
100
,
200
],
dtype
=
numpy
.
int8
)
place
=
core
.
CPUPlace
()
cpu_tensor
.
set
(
tensor_array
,
place
)
cpu_tensor_array_2
=
numpy
.
array
(
cpu_tensor
)
self
.
assertAlmostEqual
(
cpu_tensor_array_2
.
all
(),
tensor_array
.
all
())
if
core
.
is_compiled_with_cuda
():
cuda_tensor
=
var
.
get_tensor
()
tensor_array
=
numpy
.
random
.
randint
(
-
127
,
high
=
128
,
size
=
[
100
,
200
],
dtype
=
numpy
.
int8
)
place
=
core
.
CUDAPlace
(
0
)
cuda_tensor
.
set
(
tensor_array
,
place
)
cuda_tensor_array_2
=
numpy
.
array
(
cuda_tensor
)
self
.
assertAlmostEqual
(
cuda_tensor_array_2
.
all
(),
tensor_array
.
all
())
def
test_int_lod_tensor
(
self
):
place
=
core
.
CPUPlace
()
scope
=
core
.
Scope
()
...
...
python/paddle/fluid/tests/unittests/test_variable.py
浏览文件 @
a481c5e9
...
...
@@ -31,7 +31,8 @@ class TestVariable(unittest.TestCase):
self
.
assertEqual
(
DT
.
INT16
,
convert
(
"int16"
))
self
.
assertEqual
(
DT
.
INT64
,
convert
(
"int64"
))
self
.
assertEqual
(
DT
.
BOOL
,
convert
(
"bool"
))
self
.
assertRaises
(
ValueError
,
lambda
:
convert
(
"int8"
))
self
.
assertEqual
(
DT
.
INT8
,
convert
(
"int8"
))
self
.
assertEqual
(
DT
.
UINT8
,
convert
(
"uint8"
))
def
test_var
(
self
):
b
=
default_main_program
().
current_block
()
...
...
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