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体验新版 GitCode,发现更多精彩内容 >>
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d24d8c20
编写于
11月 08, 2017
作者:
Y
Yang Yu
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差异文件
Add `lod_array_length` operator
上级
2a76b42e
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
101 addition
and
0 deletion
+101
-0
paddle/operators/lod_array_length_op.cc
paddle/operators/lod_array_length_op.cc
+71
-0
python/paddle/v2/framework/layers.py
python/paddle/v2/framework/layers.py
+9
-0
python/paddle/v2/framework/tests/test_lod_array_length_op.py
python/paddle/v2/framework/tests/test_lod_array_length_op.py
+21
-0
未找到文件。
paddle/operators/lod_array_length_op.cc
0 → 100644
浏览文件 @
d24d8c20
/* 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/framework/lod_tensor_array.h"
#include "paddle/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
LoDArrayLengthOp
:
public
framework
::
OperatorBase
{
public:
LoDArrayLengthOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
auto
&
x
=
scope
.
FindVar
(
Input
(
"X"
))
->
Get
<
framework
::
LoDTensorArray
>
();
auto
&
out
=
*
scope
.
FindVar
(
Output
(
"Out"
))
->
GetMutable
<
framework
::
LoDTensor
>
();
out
.
Resize
({
1
});
auto
cpu
=
platform
::
CPUPlace
();
*
out
.
mutable_data
<
int64_t
>
(
cpu
)
=
static_cast
<
int64_t
>
(
x
.
size
());
}
};
class
LoDArrayLengthProtoMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
LoDArrayLengthProtoMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"X"
,
"(LoDTensorArray) The input tensor array."
);
AddOutput
(
"Out"
,
"(Tensor) 1x1 CPU Tensor of length, int64_t"
);
AddComment
(
R"DOC(Get the length of lod tensor array
Out = len(X)
NOTE: The output is a CPU Tensor since the control variable should be only in
CPU and the length of LoDTensorArray should be used as control variables.
)DOC"
);
}
};
class
LoDArrayLengthInferShape
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
context
)
const
override
{
PADDLE_ENFORCE
(
context
->
HasInput
(
"X"
));
PADDLE_ENFORCE
(
context
->
HasOutput
(
"Out"
));
context
->
SetOutputDim
(
"Out"
,
{
1
});
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
lod_array_length
,
ops
::
LoDArrayLengthOp
,
ops
::
LoDArrayLengthInferShape
,
ops
::
LoDArrayLengthProtoMaker
,
paddle
::
framework
::
EmptyGradOpMaker
);
python/paddle/v2/framework/layers.py
浏览文件 @
d24d8c20
...
...
@@ -941,3 +941,12 @@ def shrink_memory(x, i, table, main_program=None):
outputs
=
{
'Out'
:
[
out
]},
attrs
=
{})
return
out
def
array_length
(
array
,
main_program
=
None
):
helper
=
LayerHelper
(
'array_length'
,
**
locals
())
tmp
=
helper
.
create_tmp_variable
(
dtype
=
'int64'
)
tmp
.
stop_gradient
=
True
helper
.
append_op
(
type
=
'lod_array_length'
,
inputs
=
{
'X'
:
[
array
]},
outputs
=
{
'Out'
:
[
tmp
]})
return
tmp
python/paddle/v2/framework/tests/test_lod_array_length_op.py
0 → 100644
浏览文件 @
d24d8c20
import
unittest
import
paddle.v2.framework.layers
as
layers
from
paddle.v2.framework.executor
import
Executor
import
paddle.v2.framework.core
as
core
import
numpy
class
TestLoDArrayLength
(
unittest
.
TestCase
):
def
test_array_length
(
self
):
tmp
=
layers
.
zeros
(
shape
=
[
10
],
dtype
=
'int32'
)
i
=
layers
.
fill_constant
(
shape
=
[
1
],
dtype
=
'int64'
,
value
=
10
)
arr
=
layers
.
array_write
(
tmp
,
i
=
i
)
arr_len
=
layers
.
array_length
(
arr
)
cpu
=
core
.
CPUPlace
()
exe
=
Executor
(
cpu
)
result
=
numpy
.
array
(
exe
.
run
(
fetch_list
=
[
arr_len
])[
0
])
self
.
assertEqual
(
11
,
result
[
0
])
if
__name__
==
'__main__'
:
unittest
.
main
()
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