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0749c882
编写于
8月 16, 2018
作者:
T
tangwei12
提交者:
GitHub
8月 16, 2018
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Merge pull request #12556 from seiriosPlus/samplingIdOp
Sampling id op
上级
0abfbd1c
822496f6
变更
4
显示空白变更内容
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Showing
4 changed file
with
226 addition
and
0 deletion
+226
-0
paddle/fluid/operators/sampling_id_op.cc
paddle/fluid/operators/sampling_id_op.cc
+76
-0
paddle/fluid/operators/sampling_id_op.cu
paddle/fluid/operators/sampling_id_op.cu
+19
-0
paddle/fluid/operators/sampling_id_op.h
paddle/fluid/operators/sampling_id_op.h
+80
-0
python/paddle/fluid/tests/unittests/test_sampling_id_op.py
python/paddle/fluid/tests/unittests/test_sampling_id_op.py
+51
-0
未找到文件。
paddle/fluid/operators/sampling_id_op.cc
0 → 100644
浏览文件 @
0749c882
/* 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/sampling_id_op.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
class
SamplingIdOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of SamplingIdOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
"Output(Out) of SamplingIdOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
Attrs
().
Get
<
float
>
(
"min"
)
<
ctx
->
Attrs
().
Get
<
float
>
(
"max"
),
"min must less then max"
);
auto
input_dims
=
ctx
->
GetInputDim
(
"X"
);
PADDLE_ENFORCE
(
input_dims
.
size
()
==
2
,
"Input(X, Filter) should be 2-D tensor."
);
framework
::
DDim
dims
=
input_dims
;
ctx
->
SetOutputDim
(
"Out"
,
dims
);
ctx
->
ShareLoD
(
"X"
,
"Out"
);
}
};
class
SamplingIdOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"The input tensor of softmax. "
"2-D with shape [batch_size, input_feature_dimensions]."
);
AddOutput
(
"Out"
,
"SamplingId data tensor."
);
AddComment
(
R"DOC(
SamplingId Operator.
A layer for sampling id from multinomial distribution from the
input. Sampling one id for one sample.)DOC"
);
AddAttr
<
float
>
(
"min"
,
"Minimum value of random. [default 0.0]."
)
.
SetDefault
(
0.0
f
);
AddAttr
<
float
>
(
"max"
,
"Maximun value of random. [default 1.0]."
)
.
SetDefault
(
1.0
f
);
AddAttr
<
int
>
(
"seed"
,
"Random seed used for the random number engine. "
"0 means use a seed generated by the system."
"Note that if seed is not 0, this operator will always "
"generate the same random numbers every time. [default 0]."
)
.
SetDefault
(
0
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
sampling_id
,
ops
::
SamplingIdOp
,
ops
::
SamplingIdOpMaker
,
paddle
::
framework
::
EmptyGradOpMaker
);
REGISTER_OP_CPU_KERNEL
(
sampling_id
,
paddle
::
operators
::
SamplingIdKernel
<
float
>
,
paddle
::
operators
::
SamplingIdKernel
<
double
>
);
paddle/fluid/operators/sampling_id_op.cu
0 → 100644
浏览文件 @
0749c882
/* 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/sampling_id_op.h"
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
sampling_id
,
paddle
::
operators
::
SamplingIdKernel
<
float
>
,
paddle
::
operators
::
SamplingIdKernel
<
double
>
);
paddle/fluid/operators/sampling_id_op.h
0 → 100644
浏览文件 @
0749c882
/* 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 <algorithm>
#include <iostream>
#include <iterator>
#include <random>
#include <sstream>
#include <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
template
<
typename
T
>
class
SamplingIdKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
const
Tensor
*
input
=
context
.
Input
<
Tensor
>
(
"X"
);
const
int
batch_size
=
static_cast
<
int
>
(
input
->
dims
()[
0
]);
const
int
width
=
static_cast
<
int
>
(
input
->
dims
()[
1
]);
PADDLE_ENFORCE_GE
(
batch_size
,
0
,
"batch_size(dims[0]) must be nonnegative."
);
PADDLE_ENFORCE_GE
(
width
,
0
,
"width(dims[1]) must be nonnegative."
);
std
::
vector
<
T
>
ins_vector
;
framework
::
TensorToVector
(
*
input
,
context
.
device_context
(),
&
ins_vector
);
unsigned
int
seed
=
static_cast
<
unsigned
int
>
(
context
.
Attr
<
int
>
(
"seed"
));
std
::
minstd_rand
engine
;
if
(
seed
==
0
)
{
seed
=
std
::
random_device
()();
}
engine
.
seed
(
seed
);
std
::
uniform_real_distribution
<
T
>
dist
(
static_cast
<
T
>
(
context
.
Attr
<
float
>
(
"min"
)),
static_cast
<
T
>
(
context
.
Attr
<
float
>
(
"max"
)));
std
::
vector
<
T
>
ids
(
batch_size
);
for
(
size_t
i
=
0
;
i
<
batch_size
;
++
i
)
{
T
r
=
dist
(
engine
);
int
idx
=
width
-
1
;
for
(
int
j
=
0
;
j
<
width
;
++
j
)
{
if
((
r
-=
ins_vector
[
i
*
width
+
j
])
<
0
)
{
idx
=
j
;
break
;
}
}
ids
[
i
]
=
ins_vector
[
i
*
width
+
idx
];
}
std
::
vector
<
int64_t
>
out_dim
;
out_dim
.
push_back
(
static_cast
<
int64_t
>
(
batch_size
));
Tensor
*
output
=
context
.
Output
<
Tensor
>
(
"Out"
);
output
->
Resize
(
framework
::
make_ddim
(
out_dim
));
output
->
mutable_data
<
T
>
(
context
.
GetPlace
());
framework
::
TensorFromVector
(
ids
,
context
.
device_context
(),
output
);
}
};
}
// namespace operators
}
// namespace paddle
python/paddle/fluid/tests/unittests/test_sampling_id_op.py
0 → 100644
浏览文件 @
0749c882
# 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.
import
unittest
import
numpy
as
np
from
op_test
import
OpTest
import
paddle.fluid.core
as
core
from
paddle.fluid.op
import
Operator
class
TestSamplingIdOp
(
OpTest
):
def
setUp
(
self
):
self
.
op_type
=
"sampling_id"
self
.
use_mkldnn
=
False
self
.
init_kernel_type
()
self
.
X
=
np
.
random
.
random
((
8
,
4
)).
astype
(
'float32'
)
self
.
inputs
=
{
"X"
:
self
.
X
}
self
.
Y
=
np
.
random
.
random
(
8
).
astype
(
'float32'
)
self
.
outputs
=
{
'Out'
:
self
.
Y
}
self
.
attrs
=
{
'max'
:
1.0
,
'min'
:
0.0
,
'seed'
:
1
}
def
test_check_output
(
self
):
self
.
check_output_customized
(
self
.
verify_output
)
y1
=
self
.
out
self
.
check_output_customized
(
self
.
verify_output
)
y2
=
self
.
out
self
.
assertTrue
(
np
.
array_equal
(
y1
,
y2
))
self
.
assertEqual
(
len
(
y1
),
len
(
self
.
Y
))
def
verify_output
(
self
,
outs
):
out
=
np
.
array
(
outs
[
0
])
self
.
out
=
out
def
init_kernel_type
(
self
):
pass
if
__name__
==
"__main__"
:
unittest
.
main
()
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