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e167e879
编写于
8月 21, 2020
作者:
W
wangchaochaohu
提交者:
GitHub
8月 21, 2020
浏览文件
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电子邮件补丁
差异文件
【API2.0】add masked_select Op for API2.0 (#26374)
上级
c09de13e
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
575 addition
and
3 deletion
+575
-3
paddle/fluid/operators/masked_select_op.cc
paddle/fluid/operators/masked_select_op.cc
+120
-0
paddle/fluid/operators/masked_select_op.cu
paddle/fluid/operators/masked_select_op.cu
+179
-0
paddle/fluid/operators/masked_select_op.h
paddle/fluid/operators/masked_select_op.h
+94
-0
python/paddle/__init__.py
python/paddle/__init__.py
+1
-1
python/paddle/fluid/tests/unittests/test_masked_select_op.py
python/paddle/fluid/tests/unittests/test_masked_select_op.py
+124
-0
python/paddle/tensor/__init__.py
python/paddle/tensor/__init__.py
+1
-0
python/paddle/tensor/search.py
python/paddle/tensor/search.py
+56
-2
未找到文件。
paddle/fluid/operators/masked_select_op.cc
0 → 100644
浏览文件 @
e167e879
/* Copyright (c) 2020 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/masked_select_op.h"
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
class
MaskedSelectOp
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"X"
),
"Input"
,
"Input"
,
"MaskedSelect"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"Mask"
),
"Input"
,
"Mask"
,
"MaskedSelect"
);
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
"Y"
),
"Output"
,
"Out"
,
"MaskedSelect"
);
framework
::
DDim
output_dims
(
ctx
->
GetInputDim
(
"X"
));
ctx
->
SetOutputDim
(
"Y"
,
output_dims
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Y"
);
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
auto
data_type
=
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
"X"
);
return
framework
::
OpKernelType
(
data_type
,
ctx
.
device_context
());
}
};
class
MaskedSelectOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
void
Make
()
override
{
AddInput
(
"X"
,
"The input tensor."
);
AddInput
(
"Mask"
,
"The mask of Input Tensor to be selected which is a bool Tensor."
);
AddOutput
(
"Y"
,
"The returned tensor, the data type "
"is same as input, will be on the same device with the input Tensor."
);
AddComment
(
R"DOC(
Size Operator.
Return a new 0-D tensor which indexes the indexed tensor according
the mask which is a tensor withe data type bool.
)DOC"
);
}
};
class
MaskedSelectOpGrad
:
public
framework
::
OperatorWithKernel
{
public:
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
OP_INOUT_CHECK
(
ctx
->
HasOutput
(
framework
::
GradVarName
(
"X"
)),
"Input"
,
"Input"
,
"MaskedSelect"
);
OP_INOUT_CHECK
(
ctx
->
HasInput
(
"Mask"
),
"Input"
,
"Mask"
,
"MaskedSelect"
);
ctx
->
SetOutputDim
(
framework
::
GradVarName
(
"X"
),
ctx
->
GetInputDim
(
"X"
));
ctx
->
ShareLoD
(
"X"
,
/*-->*/
framework
::
GradVarName
(
"X"
));
}
protected:
framework
::
OpKernelType
GetExpectedKernelType
(
const
framework
::
ExecutionContext
&
ctx
)
const
override
{
return
framework
::
OpKernelType
(
OperatorWithKernel
::
IndicateVarDataType
(
ctx
,
framework
::
GradVarName
(
"Y"
)),
ctx
.
device_context
());
}
};
template
<
typename
T
>
class
MaskedSelectGradOpMaker
:
public
framework
::
SingleGradOpMaker
<
T
>
{
public:
using
framework
::
SingleGradOpMaker
<
T
>::
SingleGradOpMaker
;
protected:
void
Apply
(
GradOpPtr
<
T
>
op
)
const
override
{
op
->
SetType
(
"masked_select_grad"
);
op
->
SetInput
(
"X"
,
this
->
Input
(
"X"
));
op
->
SetInput
(
"Mask"
,
this
->
Input
(
"Mask"
));
op
->
SetInput
(
framework
::
GradVarName
(
"Y"
),
this
->
OutputGrad
(
"Y"
));
op
->
SetOutput
(
framework
::
GradVarName
(
"X"
),
this
->
InputGrad
(
"X"
));
}
};
DECLARE_NO_NEED_BUFFER_VARS_INFERER
(
MaskedSelectedGradNoNeedBufferVarsInferer
,
"X"
);
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
masked_select
,
ops
::
MaskedSelectOp
,
ops
::
MaskedSelectOpMaker
,
ops
::
MaskedSelectGradOpMaker
<
paddle
::
framework
::
OpDesc
>
,
ops
::
MaskedSelectGradOpMaker
<
paddle
::
imperative
::
OpBase
>
);
REGISTER_OPERATOR
(
masked_select_grad
,
ops
::
MaskedSelectOpGrad
,
ops
::
MaskedSelectedGradNoNeedBufferVarsInferer
);
REGISTER_OP_CPU_KERNEL
(
masked_select
,
ops
::
MaskedSelectKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
MaskedSelectKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
,
ops
::
MaskedSelectKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
,
ops
::
MaskedSelectKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
>
);
REGISTER_OP_CPU_KERNEL
(
masked_select_grad
,
ops
::
MaskedSelectGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
float
>
,
ops
::
MaskedSelectGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
double
>
,
ops
::
MaskedSelectGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int
>
,
ops
::
MaskedSelectGradKernel
<
paddle
::
platform
::
CPUDeviceContext
,
int64_t
>
);
paddle/fluid/operators/masked_select_op.cu
0 → 100644
浏览文件 @
e167e879
/* Copyright (c) 2020 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 <thrust/device_ptr.h>
#include <thrust/device_vector.h>
#include <thrust/reverse.h>
#include <thrust/scan.h>
#include "paddle/fluid/operators/masked_select_op.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
using
DDim
=
framework
::
DDim
;
__global__
void
SetMaskArray
(
const
bool
*
mask
,
int32_t
*
mask_array
,
int
size
)
{
int
idx
=
blockDim
.
x
*
blockIdx
.
x
+
threadIdx
.
x
;
for
(;
idx
<
size
;
idx
+=
blockDim
.
x
*
gridDim
.
x
)
{
if
(
mask
[
idx
])
mask_array
[
idx
]
=
1
;
else
mask_array
[
idx
]
=
0
;
}
}
template
<
typename
T
>
__global__
void
SelectWithPrefixMask
(
const
int32_t
*
mask_prefix_sum
,
const
bool
*
mask
,
const
T
*
input
,
T
*
out
,
int
size
)
{
int
idx
=
blockDim
.
x
*
blockIdx
.
x
+
threadIdx
.
x
;
for
(;
idx
<
size
;
idx
+=
blockDim
.
x
*
gridDim
.
x
)
{
if
(
mask
[
idx
])
{
int
index
=
mask_prefix_sum
[
idx
];
out
[
index
]
=
input
[
idx
];
}
}
}
template
<
typename
T
>
__global__
void
SelectGradWithPrefixMask
(
const
int32_t
*
mask_prefix_sum
,
const
bool
*
mask
,
const
T
*
input
,
T
*
out
,
int
size
)
{
int
idx
=
blockDim
.
x
*
blockIdx
.
x
+
threadIdx
.
x
;
for
(;
idx
<
size
;
idx
+=
blockDim
.
x
*
gridDim
.
x
)
{
if
(
mask
[
idx
])
{
int
index
=
mask_prefix_sum
[
idx
];
out
[
idx
]
=
input
[
index
];
}
else
{
out
[
idx
]
=
0
;
}
}
}
template
<
typename
DeviceContext
,
typename
T
>
class
MaskedSelectCUDAKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
input
=
ctx
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
mask
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
out
=
ctx
.
Output
<
framework
::
Tensor
>
(
"Y"
);
auto
*
mask_data
=
mask
->
data
<
bool
>
();
auto
input_data
=
input
->
data
<
T
>
();
auto
mask_size
=
mask
->
numel
();
auto
input_dim
=
input
->
dims
();
auto
mask_dim
=
mask
->
dims
();
PADDLE_ENFORCE_EQ
(
input_dim
,
mask_dim
,
platform
::
errors
::
InvalidArgument
(
"The dim size of input and mask in OP(masked_selected) "
"must be equal, but got input dim:(%ld), mask dim: "
"(%ld). Please check input "
"value."
,
input_dim
,
mask_dim
));
thrust
::
device_ptr
<
const
bool
>
mask_dev_ptr
=
thrust
::
device_pointer_cast
(
mask_data
);
thrust
::
device_vector
<
T
>
mask_vec
(
mask_dev_ptr
,
mask_dev_ptr
+
mask_size
);
auto
out_size
=
thrust
::
count
(
mask_vec
.
begin
(),
mask_vec
.
end
(),
true
);
framework
::
DDim
out_dim
{
out_size
};
out
->
Resize
(
out_dim
);
auto
out_data
=
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
Tensor
mask_array
;
Tensor
mask_prefix_sum
;
mask_array
.
Resize
(
mask_dim
);
mask_prefix_sum
.
Resize
(
mask_dim
);
int32_t
*
mask_array_data
=
mask_array
.
mutable_data
<
int32_t
>
(
ctx
.
GetPlace
());
int32_t
*
mask_prefix_sum_data
=
mask_prefix_sum
.
mutable_data
<
int32_t
>
(
ctx
.
GetPlace
());
int
threads
=
512
;
int
grid
=
(
mask_size
+
threads
-
1
)
/
threads
;
auto
stream
=
ctx
.
cuda_device_context
().
stream
();
SetMaskArray
<<<
grid
,
threads
,
0
,
stream
>>>
(
mask_data
,
mask_array_data
,
mask_size
);
thrust
::
device_ptr
<
int32_t
>
mask_array_dev_ptr
=
thrust
::
device_pointer_cast
(
mask_array_data
);
thrust
::
device_vector
<
int32_t
>
mask_array_vec
(
mask_array_dev_ptr
,
mask_array_dev_ptr
+
mask_size
);
thrust
::
exclusive_scan
(
thrust
::
device
,
mask_array_vec
.
begin
(),
mask_array_vec
.
end
(),
mask_prefix_sum_data
);
SelectWithPrefixMask
<
T
><<<
grid
,
threads
,
0
,
stream
>>>
(
mask_prefix_sum_data
,
mask_data
,
input_data
,
out_data
,
mask_size
);
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
MaskedSelectGradCUDAKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
ctx
)
const
{
auto
input
=
ctx
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
mask
=
ctx
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
out
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
mask_data
=
mask
->
data
<
bool
>
();
auto
*
input_data
=
input
->
data
<
T
>
();
auto
*
out_data
=
out
->
mutable_data
<
T
>
(
ctx
.
GetPlace
());
auto
input_size
=
input
->
numel
();
auto
mask_size
=
mask
->
numel
();
auto
mask_dim
=
mask
->
dims
();
auto
out_size
=
mask_size
;
Tensor
mask_array
;
Tensor
mask_prefix_sum
;
mask_array
.
Resize
(
mask_dim
);
mask_prefix_sum
.
Resize
(
mask_dim
);
int32_t
*
mask_array_data
=
mask_array
.
mutable_data
<
int32_t
>
(
ctx
.
GetPlace
());
int32_t
*
mask_prefix_sum_data
=
mask_prefix_sum
.
mutable_data
<
int32_t
>
(
ctx
.
GetPlace
());
int
threads
=
512
;
int
grid
=
(
mask_size
+
threads
-
1
)
/
threads
;
auto
stream
=
ctx
.
cuda_device_context
().
stream
();
SetMaskArray
<<<
grid
,
threads
,
0
,
stream
>>>
(
mask_data
,
mask_array_data
,
mask_size
);
thrust
::
device_ptr
<
int32_t
>
mask_array_dev_ptr
=
thrust
::
device_pointer_cast
(
mask_array_data
);
thrust
::
device_vector
<
int32_t
>
mask_array_vec
(
mask_array_dev_ptr
,
mask_array_dev_ptr
+
mask_size
);
thrust
::
exclusive_scan
(
thrust
::
device
,
mask_array_vec
.
begin
(),
mask_array_vec
.
end
(),
mask_prefix_sum_data
);
SelectGradWithPrefixMask
<
T
><<<
grid
,
threads
,
0
,
stream
>>>
(
mask_prefix_sum_data
,
mask_data
,
input_data
,
out_data
,
mask_size
);
}
};
}
// namespace operators
}
// namespace paddle
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_CUDA_KERNEL
(
masked_select
,
ops
::
MaskedSelectCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
MaskedSelectCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
,
ops
::
MaskedSelectCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int
>
,
ops
::
MaskedSelectCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int64_t
>
);
REGISTER_OP_CUDA_KERNEL
(
masked_select_grad
,
ops
::
MaskedSelectGradCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
float
>
,
ops
::
MaskedSelectGradCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
double
>
,
ops
::
MaskedSelectGradCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int
>
,
ops
::
MaskedSelectGradCUDAKernel
<
paddle
::
platform
::
CUDADeviceContext
,
int64_t
>
);
paddle/fluid/operators/masked_select_op.h
0 → 100644
浏览文件 @
e167e879
// Copyright (c) 2020 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 <vector>
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
operators
{
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
using
DDim
=
framework
::
DDim
;
template
<
typename
DeviceContext
,
typename
T
>
class
MaskedSelectKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
input
=
context
.
Input
<
framework
::
Tensor
>
(
"X"
);
auto
mask
=
context
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
out
=
context
.
Output
<
framework
::
Tensor
>
(
"Y"
);
auto
*
mask_data
=
mask
->
data
<
bool
>
();
auto
input_data
=
input
->
data
<
T
>
();
auto
mask_size
=
mask
->
numel
();
auto
input_dim
=
input
->
dims
();
auto
mask_dim
=
mask
->
dims
();
PADDLE_ENFORCE_EQ
(
input_dim
,
mask_dim
,
platform
::
errors
::
InvalidArgument
(
"The dim size of input and mask in OP(masked_selected) "
"must be equal, but got input dim:(%ld), mask dim: "
"(%ld). Please check input "
"value."
,
input_dim
,
mask_dim
));
int
out_size
=
0
;
for
(
int
i
=
0
;
i
<
mask_size
;
i
++
)
{
if
(
mask_data
[
i
])
out_size
++
;
}
framework
::
DDim
out_dim
{
out_size
};
out
->
Resize
(
out_dim
);
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
index
=
0
;
for
(
int
i
=
0
;
i
<
mask_size
;
i
++
)
{
if
(
mask_data
[
i
])
{
out_data
[
index
]
=
input_data
[
i
];
index
++
;
}
}
}
};
template
<
typename
DeviceContext
,
typename
T
>
class
MaskedSelectGradKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
override
{
auto
out
=
context
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
mask
=
context
.
Input
<
framework
::
Tensor
>
(
"Mask"
);
auto
input
=
context
.
Input
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
mask_data
=
mask
->
data
<
bool
>
();
auto
*
input_data
=
input
->
data
<
T
>
();
auto
*
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
int
mask_size
=
mask
->
numel
();
int
index
=
0
;
for
(
int
i
=
0
;
i
<
mask_size
;
i
++
)
{
if
(
mask_data
[
i
])
{
out_data
[
i
]
=
input_data
[
index
];
index
++
;
}
else
{
out_data
[
i
]
=
0
;
}
}
}
};
}
// namespace operators
}
// namespace paddle
python/paddle/__init__.py
浏览文件 @
e167e879
...
...
@@ -201,7 +201,7 @@ from .tensor.search import argmin #DEFINE_ALIAS
from
.tensor.search
import
argsort
#DEFINE_ALIAS
from
.tensor.search
import
has_inf
#DEFINE_ALIAS
from
.tensor.search
import
has_nan
#DEFINE_ALIAS
# from .tensor.search import masked_select
#DEFINE_ALIAS
from
.tensor.search
import
masked_select
#DEFINE_ALIAS
from
.tensor.search
import
topk
#DEFINE_ALIAS
from
.tensor.search
import
where
#DEFINE_ALIAS
from
.tensor.search
import
index_select
#DEFINE_ALIAS
...
...
python/paddle/fluid/tests/unittests/test_masked_select_op.py
0 → 100644
浏览文件 @
e167e879
# Copyright (c) 2020 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
import
paddle.fluid
as
fluid
import
paddle
def
np_masked_select
(
x
,
mask
):
result
=
np
.
empty
(
shape
=
(
0
),
dtype
=
x
.
dtype
)
for
ele
,
ma
in
zip
(
np
.
nditer
(
x
),
np
.
nditer
(
mask
)):
if
ma
:
result
=
np
.
append
(
result
,
ele
)
return
result
.
flatten
()
class
TestMaskedSelectOp
(
OpTest
):
def
setUp
(
self
):
self
.
init
()
self
.
op_type
=
"masked_select"
x
=
np
.
random
.
random
(
self
.
shape
).
astype
(
"float64"
)
mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
self
.
shape
,
dtype
=
bool
))
out
=
np_masked_select
(
x
,
mask
)
self
.
inputs
=
{
'X'
:
x
,
'Mask'
:
mask
}
self
.
outputs
=
{
'Y'
:
out
}
def
test_check_output
(
self
):
self
.
check_output
()
def
test_check_grad
(
self
):
self
.
check_grad
([
'X'
],
'Y'
)
def
init
(
self
):
self
.
shape
=
(
50
,
3
)
class
TestMaskedSelectOp1
(
TestMaskedSelectOp
):
def
init
(
self
):
self
.
shape
=
(
6
,
8
,
9
,
18
)
class
TestMaskedSelectOp2
(
TestMaskedSelectOp
):
def
init
(
self
):
self
.
shape
=
(
168
,
)
class
TestMaskedSelectAPI
(
unittest
.
TestCase
):
def
test_imperative_mode
(
self
):
paddle
.
disable_static
()
shape
=
(
88
,
6
,
8
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
x
=
paddle
.
to_tensor
(
np_x
)
mask
=
paddle
.
to_tensor
(
np_mask
)
out
=
paddle
.
masked_select
(
x
,
mask
)
np_out
=
np_masked_select
(
np_x
,
np_mask
)
self
.
assertEqual
(
np
.
allclose
(
out
.
numpy
(),
np_out
),
True
)
paddle
.
enable_static
()
def
test_static_mode
(
self
):
shape
=
[
8
,
9
,
6
]
x
=
paddle
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'x'
)
mask
=
paddle
.
data
(
shape
=
shape
,
dtype
=
'bool'
,
name
=
'mask'
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
out
=
paddle
.
masked_select
(
x
,
mask
)
np_out
=
np_masked_select
(
np_x
,
np_mask
)
exe
=
paddle
.
static
.
Executor
(
place
=
paddle
.
CPUPlace
())
res
=
exe
.
run
(
paddle
.
static
.
default_main_program
(),
feed
=
{
"x"
:
np_x
,
"mask"
:
np_mask
},
fetch_list
=
[
out
])
self
.
assertEqual
(
np
.
allclose
(
res
,
np_out
),
True
)
class
TestMaskedSelectError
(
unittest
.
TestCase
):
def
test_error
(
self
):
with
paddle
.
static
.
program_guard
(
paddle
.
static
.
Program
(),
paddle
.
static
.
Program
()):
shape
=
[
8
,
9
,
6
]
x
=
paddle
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'x'
)
mask
=
paddle
.
data
(
shape
=
shape
,
dtype
=
'bool'
,
name
=
'mask'
)
mask_float
=
paddle
.
data
(
shape
=
shape
,
dtype
=
'float32'
,
name
=
'mask_float'
)
np_x
=
np
.
random
.
random
(
shape
).
astype
(
'float32'
)
np_mask
=
np
.
array
(
np
.
random
.
randint
(
2
,
size
=
shape
,
dtype
=
bool
))
def
test_x_type
():
paddle
.
masked_select
(
np_x
,
mask
)
self
.
assertRaises
(
TypeError
,
test_x_type
)
def
test_mask_type
():
paddle
.
masked_select
(
x
,
np_mask
)
self
.
assertRaises
(
TypeError
,
test_mask_type
)
def
test_mask_dtype
():
paddle
.
masked_select
(
x
,
mask_float
)
self
.
assertRaises
(
TypeError
,
test_mask_dtype
)
if
__name__
==
'__main__'
:
unittest
.
main
()
python/paddle/tensor/__init__.py
浏览文件 @
e167e879
...
...
@@ -177,6 +177,7 @@ from .search import index_select #DEFINE_ALIAS
from
.search
import
nonzero
#DEFINE_ALIAS
from
.search
import
sort
#DEFINE_ALIAS
from
.search
import
index_sample
#DEFINE_ALIAS
from
.search
import
masked_select
#DEFINE_ALIAS
from
.stat
import
mean
#DEFINE_ALIAS
from
.stat
import
reduce_mean
#DEFINE_ALIAS
from
.stat
import
std
#DEFINE_ALIAS
...
...
python/paddle/tensor/search.py
浏览文件 @
e167e879
...
...
@@ -29,13 +29,13 @@ __all__ = [
'argsort'
,
'has_inf'
,
'has_nan'
,
#
'masked_select',
'masked_select'
,
'topk'
,
'where'
,
'index_select'
,
'nonzero'
,
'sort'
,
'index_sample'
'index_sample'
,
]
from
paddle.common_ops_import
import
*
...
...
@@ -629,3 +629,57 @@ def index_sample(x, index):
'Index'
:
index
},
outputs
=
{
'Out'
:
out
})
return
out
def
masked_select
(
x
,
mask
,
name
=
None
):
"""
This OP Returns a new 1-D tensor which indexes the input tensor according to the ``mask``
which is a tensor with data type of bool.
Args:
x (Tensor): The input Tensor, the data type can be int32, int64, float32, float64.
mask (Tensor): The Tensor containing the binary mask to index with, it's data type is bool.
name(str, optional): The default value is None. Normally there is no
need for user to set this property. For more information, please
refer to :ref:`api_guide_Name`.
Returns: A 1-D Tensor which is the same data type as ``x``.
Raises:
TypeError: ``x`` must be a Tensor and the data type of ``x`` must be one of float32, float64, int32 and int64.
TypeError: ``mask`` must be a Tensor and the data type of ``mask`` must be bool.
Examples:
.. code-block:: python
import paddle
import numpy as np
paddle.disable_static()
data = np.array([[1.0, 2.0, 3.0, 4.0],
[5.0, 6.0, 7.0, 8.0],
[9.0, 10.0, 11.0, 12.0]]).astype('float32')
mask_data = np.array([[True, False, False, False],
[True, True, False, False],
[True, False, False, False]]).astype('bool')
x = paddle.to_tensor(data)
mask = paddle.to_tensor(mask_data)
out = paddle.masked_select(x, mask)
#[1.0 5.0 6.0 9.0]
"""
if
in_dygraph_mode
():
return
core
.
ops
.
masked_select
(
x
,
mask
)
helper
=
LayerHelper
(
"masked_select"
,
**
locals
())
check_variable_and_dtype
(
x
,
'x'
,
[
'float32'
,
'float64'
,
'int32'
,
'int64'
],
'paddle.tensor.search.mask_select'
)
check_variable_and_dtype
(
mask
,
'mask'
,
[
'bool'
],
'paddle.tensor.search.masked_select'
)
out
=
helper
.
create_variable_for_type_inference
(
dtype
=
x
.
dtype
)
helper
.
append_op
(
type
=
'masked_select'
,
inputs
=
{
'X'
:
x
,
'Mask'
:
mask
},
outputs
=
{
'Y'
:
out
})
return
out
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