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体验新版 GitCode,发现更多精彩内容 >>
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f1c3ecb2
编写于
3月 10, 2018
作者:
C
chengduoZH
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add concat rows
上级
1509ce66
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
136 addition
and
19 deletion
+136
-19
paddle/fluid/operators/lookup_table_op.cc
paddle/fluid/operators/lookup_table_op.cc
+46
-2
paddle/fluid/operators/lookup_table_op.cu
paddle/fluid/operators/lookup_table_op.cu
+10
-10
paddle/fluid/operators/lookup_table_op.h
paddle/fluid/operators/lookup_table_op.h
+4
-7
python/paddle/fluid/tests/unittests/test_concat_rows_op.py
python/paddle/fluid/tests/unittests/test_concat_rows_op.py
+76
-0
未找到文件。
paddle/fluid/operators/lookup_table_op.cc
浏览文件 @
f1c3ecb2
...
...
@@ -34,8 +34,9 @@ class LookupTableOp : public framework::OperatorWithKernel {
auto
ids_dims
=
ctx
->
GetInputDim
(
"Ids"
);
auto
ids_var_type
=
ctx
->
GetInputsVarType
(
"Ids"
).
front
();
// ids_var_types also can be LOD_TENSOR_ARRAY, it's used as concat_rows.
// Maybe near future we will add concat_rows op.
// lookup_table and concat_rows use the same InferShape, for lookup_table,
// ids_var_type should be LoDTensor, for concat_rows, it should be
// SelectedRows.
if
(
ids_var_type
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
PADDLE_ENFORCE_EQ
(
ids_dims
.
size
(),
2
);
PADDLE_ENFORCE_EQ
(
ids_dims
[
1
],
1
);
...
...
@@ -90,6 +91,44 @@ or not. And the output only shares the LoD information with input Ids.
}
};
class
ConcatRowsOpMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ConcatRowsOpMaker
(
OpProto
*
proto
,
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
"W"
,
"(Tensor) The input tensor of concat_rows operator. "
"The rank of this tensor is 2."
);
AddInput
(
"Ids"
,
"(SelectedRows) The rows of Ids contains the index to be looked up "
"in W."
);
AddOutput
(
"Out"
,
"(SelectedRows or Tensor) The result of concatenating, which "
"have the same type as W."
);
AddAttr
<
bool
>
(
"is_sparse"
,
"(boolean, default true) This attribution is invalid, it's "
"only used by `Lookup Table Operator`."
)
.
SetDefault
(
true
);
AddAttr
<
int64_t
>
(
"padding_idx"
,
"(int64, default -1) "
"If the value is -1, it makes no effect to lookup. "
"Otherwise the given value indicates padding the output "
"with zeros whenever lookup encounters it in Ids."
)
.
SetDefault
(
-
1
);
AddComment
(
R"DOC(
ConcatRows Operator.
This operator is used to perform lookups on the W(dense tensor) according to
rows contained by Idx(sparse tensor), then concatenates them into a sparse
tensor or dense tensor.
The type of Ids(Input) is SelectedRows.
)DOC"
);
}
};
class
LookupTableOpGradDescMaker
:
public
framework
::
DefaultGradOpDescMaker
<
true
>
{
using
::
paddle
::
framework
::
DefaultGradOpDescMaker
<
...
...
@@ -150,3 +189,8 @@ REGISTER_OP_CPU_KERNEL(lookup_table, ops::LookupTableKernel<float>,
ops
::
LookupTableKernel
<
double
>
);
REGISTER_OP_CPU_KERNEL
(
lookup_table_grad
,
ops
::
LookupTableGradKernel
<
float
>
,
ops
::
LookupTableGradKernel
<
double
>
);
// concat_rows is used by regularization and it doesn't have gradient operation.
REGISTER_OPERATOR
(
concat_rows
,
ops
::
LookupTableOp
,
ops
::
ConcatRowsOpMaker
);
REGISTER_OP_CPU_KERNEL
(
concat_rows
,
ops
::
LookupTableKernel
<
float
>
,
ops
::
LookupTableKernel
<
double
>
);
paddle/fluid/operators/lookup_table_op.cu
浏览文件 @
f1c3ecb2
...
...
@@ -79,20 +79,17 @@ class LookupTableCUDAKernel : public framework::OpKernel<T> {
int64_t
*
ids
;
int64_t
K
;
framework
::
Tensor
*
output_t
;
auto
*
output_t
=
context
.
Output
<
Tensor
>
(
"Out"
);
// float tensor
;
// ids_var_types also can be LOD_TENSOR_ARRAY, it's used as concat_rows.
// Maybe near future we will add concat_rows op.
if
(
ids_var
->
IsType
<
framework
::
LoDTensor
>
())
{
// lookup_table and concat_rows use the same kernel, for lookup_table,
// ids_var_type should be LoDTensor, for concat_rows, ids_var_type and
// out_var_type should be SelectedRows.
if
(
ids_var
->
IsType
<
LoDTensor
>
())
{
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
output_t
=
context
.
Output
<
LoDTensor
>
(
"Out"
);
// float tensor
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
data
<
int64_t
>
());
K
=
ids_t
->
numel
();
}
else
if
(
ids_var
->
IsType
<
framework
::
SelectedRows
>
())
{
auto
*
ids_t
=
context
.
Input
<
framework
::
SelectedRows
>
(
"Ids"
);
output_t
=
const_cast
<
framework
::
Tensor
*>
(
&
(
context
.
Output
<
framework
::
SelectedRows
>
(
"Out"
)
->
value
()));
// float tensor
}
else
if
(
ids_var
->
IsType
<
SelectedRows
>
())
{
auto
*
ids_t
=
context
.
Input
<
SelectedRows
>
(
"Ids"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
rows
().
CUDAData
(
context
.
GetPlace
()));
K
=
ids_t
->
rows
().
size
();
output_t
->
Resize
({
K
,
table_t
->
dims
()[
1
]});
...
...
@@ -194,3 +191,6 @@ REGISTER_OP_CUDA_KERNEL(lookup_table, ops::LookupTableCUDAKernel<float>,
REGISTER_OP_CUDA_KERNEL
(
lookup_table_grad
,
ops
::
LookupTableGradCUDAKernel
<
float
>
,
ops
::
LookupTableGradCUDAKernel
<
double
>
);
REGISTER_OP_CUDA_KERNEL
(
concat_rows
,
ops
::
LookupTableCUDAKernel
<
float
>
,
ops
::
LookupTableCUDAKernel
<
double
>
);
paddle/fluid/operators/lookup_table_op.h
浏览文件 @
f1c3ecb2
...
...
@@ -35,19 +35,16 @@ class LookupTableKernel : public framework::OpKernel<T> {
int64_t
*
ids
;
int64_t
ids_numel
;
Tensor
*
output_t
;
// ids_var_type
s also can be LOD_TENSOR_ARRAY, it's used as concat_rows.
//
Maybe near future we will add concat_rows op
.
auto
*
output_t
=
context
.
Output
<
Tensor
>
(
"Out"
)
;
// lookup_table and concat_rows use the same kernel, for lookup_table,
// ids_var_type
should be LoDTensor, for concat_rows, ids_var_type and
//
out_var_type should be SelectedRows
.
if
(
ids_var
->
IsType
<
LoDTensor
>
())
{
auto
*
ids_t
=
context
.
Input
<
LoDTensor
>
(
"Ids"
);
output_t
=
context
.
Output
<
LoDTensor
>
(
"Out"
);
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
data
<
int64_t
>
());
ids_numel
=
ids_t
->
numel
();
}
else
if
(
ids_var
->
IsType
<
SelectedRows
>
())
{
auto
*
ids_t
=
context
.
Input
<
SelectedRows
>
(
"Ids"
);
output_t
=
const_cast
<
Tensor
*>
(
&
(
context
.
Output
<
SelectedRows
>
(
"Out"
)
->
value
()));
ids
=
const_cast
<
int64_t
*>
(
ids_t
->
rows
().
data
());
ids_numel
=
ids_t
->
rows
().
size
();
output_t
->
Resize
({
ids_numel
,
table_t
->
dims
()[
1
]});
...
...
python/paddle/fluid/tests/unittests/test_concat_rows_op.py
0 → 100644
浏览文件 @
f1c3ecb2
# 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
import
paddle.fluid.core
as
core
from
paddle.fluid.op
import
Operator
from
op_test
import
OpTest
class
TestConcatRowsOp
(
OpTest
):
def
check_with_place
(
self
,
place
):
scope
=
core
.
Scope
()
# create and initialize Grad Variable
height
=
10
rows
=
[
0
,
4
,
4
,
7
]
row_numel
=
12
ids_selected_rows
=
scope
.
var
(
'Ids'
).
get_selected_rows
()
ids_selected_rows
.
set_height
(
height
)
ids_selected_rows
.
set_rows
(
rows
)
np_array
=
np
.
ones
((
len
(
rows
),
row_numel
)).
astype
(
"float32"
)
ids_tensor
=
ids_selected_rows
.
get_tensor
()
ids_tensor
.
set
(
np_array
,
place
)
# create and initialize W Variable
W
=
scope
.
var
(
'W'
).
get_tensor
()
W_array
=
np
.
full
((
height
,
row_numel
),
1.0
).
astype
(
"float32"
)
for
i
in
range
(
height
):
W_array
[
i
]
*=
i
W
.
set
(
W_array
,
place
)
Out
=
scope
.
var
(
'Out'
).
get_selected_rows
()
Out_array
=
np
.
full
((
len
(
rows
),
row_numel
),
-
1.0
).
astype
(
"float32"
)
Out
.
set_height
(
height
)
Out
.
set_rows
(
rows
)
Out_tensor
=
Out
.
get_tensor
()
Out_tensor
.
set
(
Out_array
,
place
)
# create and run concat_rows_op operator
concat_rows_op
=
Operator
(
"concat_rows"
,
W
=
'W'
,
Ids
=
'Ids'
,
Out
=
'Out'
,
attrs
=
{
'is_sparse'
:
True
})
concat_rows_op
.
run
(
scope
,
place
)
# get and compare result
result_array
=
np
.
array
(
Out_tensor
)
for
idx
,
row
in
enumerate
(
rows
):
assert
(
row
==
result_array
[
idx
]).
all
()
def
test_concat_rows
(
self
):
places
=
[
core
.
CPUPlace
()]
if
core
.
is_compiled_with_cuda
():
places
.
append
(
core
.
CUDAPlace
(
0
))
for
place
in
places
:
self
.
check_with_place
(
place
)
if
__name__
==
"__main__"
:
unittest
.
main
()
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