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体验新版 GitCode,发现更多精彩内容 >>
提交
34404f9c
编写于
2月 27, 2019
作者:
L
luotao1
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
refine infershape of sequence_enumerate, hash and fuse_emb_seq_pool
test=develop
上级
a63e2a0a
变更
7
隐藏空白更改
内联
并排
Showing
7 changed file
with
68 addition
and
45 deletion
+68
-45
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
+11
-29
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h
+20
-0
paddle/fluid/operators/hash_op.cc
paddle/fluid/operators/hash_op.cc
+5
-10
paddle/fluid/operators/hash_op.h
paddle/fluid/operators/hash_op.h
+22
-3
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
+6
-3
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
+2
-0
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
+2
-0
未找到文件。
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
浏览文件 @
34404f9c
...
@@ -23,6 +23,9 @@ class FusedEmbeddingSeqPoolOp : public framework::OperatorWithKernel {
...
@@ -23,6 +23,9 @@ class FusedEmbeddingSeqPoolOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
if
(
ctx
->
IsRuntime
())
{
return
;
}
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"W"
),
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"W"
),
"Input W of FusedEmbeddingSeqPoolOp should not be null."
);
"Input W of FusedEmbeddingSeqPoolOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Ids"
),
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"Ids"
),
...
@@ -42,36 +45,15 @@ class FusedEmbeddingSeqPoolOp : public framework::OperatorWithKernel {
...
@@ -42,36 +45,15 @@ class FusedEmbeddingSeqPoolOp : public framework::OperatorWithKernel {
// we only support sum now
// we only support sum now
PADDLE_ENFORCE_EQ
(
combiner
,
"sum"
);
PADDLE_ENFORCE_EQ
(
combiner
,
"sum"
);
int64_t
last_dim
=
table_dims
[
1
];
int64_t
last_dim
=
FusedEmbeddingSeqPoolLastDim
(
table_dims
,
ids_dims
);
for
(
int
i
=
1
;
i
!=
ids_dims
.
size
();
++
i
)
{
// in compile time, the lod level of ids must be 1
last_dim
*=
ids_dims
[
i
];
framework
::
VarDesc
*
ids_desc
=
}
boost
::
get
<
framework
::
VarDesc
*>
(
ctx
->
GetInputVarPtrs
(
"Ids"
)[
0
]);
PADDLE_ENFORCE_EQ
(
ids_desc
->
GetLoDLevel
(),
1
);
if
(
ctx
->
IsRuntime
())
{
framework
::
Variable
*
ids_var
=
boost
::
get
<
framework
::
Variable
*>
(
ctx
->
GetInputVarPtrs
(
"Ids"
)[
0
]);
const
auto
&
ids_lod
=
ids_var
->
Get
<
LoDTensor
>
().
lod
();
// in run time, the LoD of ids must be 1
// in compile time, the shape from Ids -> output
PADDLE_ENFORCE
(
ids_lod
.
size
(),
1u
,
// should be [-1, 1] -> [-1, embedding_size]
"The LoD level of Input(Ids) must be 1"
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
({
-
1
,
last_dim
}));
PADDLE_ENFORCE_GE
(
ids_lod
[
0
].
size
(),
1u
,
"The LoD could NOT be empty"
);
int64_t
batch_size
=
ids_lod
[
0
].
size
()
-
1
;
// in run time, the shape from Ids -> output
// should be [seq_length, 1] -> [batch_size, embedding_size]
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
({
batch_size
,
last_dim
}));
}
else
{
// in compile time, the lod level of ids must be 1
framework
::
VarDesc
*
ids_desc
=
boost
::
get
<
framework
::
VarDesc
*>
(
ctx
->
GetInputVarPtrs
(
"Ids"
)[
0
]);
PADDLE_ENFORCE_EQ
(
ids_desc
->
GetLoDLevel
(),
1
);
// in compile time, the shape from Ids -> output
// should be [-1, 1] -> [-1, embedding_size]
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
({
-
1
,
last_dim
}));
}
}
}
protected:
protected:
...
...
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.h
浏览文件 @
34404f9c
...
@@ -61,6 +61,15 @@ struct EmbeddingVSumFunctor {
...
@@ -61,6 +61,15 @@ struct EmbeddingVSumFunctor {
}
}
};
};
inline
int
FusedEmbeddingSeqPoolLastDim
(
const
framework
::
DDim
&
table_dims
,
const
framework
::
DDim
&
ids_dims
)
{
int64_t
last_dim
=
table_dims
[
1
];
for
(
int
i
=
1
;
i
!=
ids_dims
.
size
();
++
i
)
{
last_dim
*=
ids_dims
[
i
];
}
return
last_dim
;
}
template
<
typename
T
>
template
<
typename
T
>
class
FusedEmbeddingSeqPoolKernel
:
public
framework
::
OpKernel
<
T
>
{
class
FusedEmbeddingSeqPoolKernel
:
public
framework
::
OpKernel
<
T
>
{
public:
public:
...
@@ -70,6 +79,17 @@ class FusedEmbeddingSeqPoolKernel : public framework::OpKernel<T> {
...
@@ -70,6 +79,17 @@ class FusedEmbeddingSeqPoolKernel : public framework::OpKernel<T> {
const
LoDTensor
*
table_var
=
context
.
Input
<
LoDTensor
>
(
"W"
);
const
LoDTensor
*
table_var
=
context
.
Input
<
LoDTensor
>
(
"W"
);
const
std
::
string
&
combiner_type
=
context
.
Attr
<
std
::
string
>
(
"combiner"
);
const
std
::
string
&
combiner_type
=
context
.
Attr
<
std
::
string
>
(
"combiner"
);
int64_t
last_dim
=
FusedEmbeddingSeqPoolLastDim
(
table_var
->
dims
(),
ids_t
->
dims
());
const
auto
&
ids_lod
=
ids_t
->
lod
();
// in run time, the LoD of ids must be 1
PADDLE_ENFORCE
(
ids_lod
.
size
(),
1u
,
"The LoD level of Input(Ids) must be 1"
);
PADDLE_ENFORCE_GE
(
ids_lod
[
0
].
size
(),
1u
,
"The LoD could NOT be empty"
);
int64_t
batch_size
=
ids_lod
[
0
].
size
()
-
1
;
// in run time, the shape from Ids -> output
// should be [seq_length, 1] -> [batch_size, embedding_size]
output_t
->
Resize
({
batch_size
,
last_dim
});
if
(
combiner_type
==
"sum"
)
{
if
(
combiner_type
==
"sum"
)
{
EmbeddingVSumFunctor
<
T
>
functor
;
EmbeddingVSumFunctor
<
T
>
functor
;
functor
(
context
,
table_var
,
ids_t
,
output_t
);
functor
(
context
,
table_var
,
ids_t
,
output_t
);
...
...
paddle/fluid/operators/hash_op.cc
浏览文件 @
34404f9c
...
@@ -14,7 +14,6 @@ limitations under the License. */
...
@@ -14,7 +14,6 @@ limitations under the License. */
#include "paddle/fluid/operators/hash_op.h"
#include "paddle/fluid/operators/hash_op.h"
#include <string>
#include <string>
#include <vector>
namespace
paddle
{
namespace
paddle
{
namespace
operators
{
namespace
operators
{
...
@@ -27,6 +26,9 @@ class HashOp : public framework::OperatorWithKernel {
...
@@ -27,6 +26,9 @@ class HashOp : public framework::OperatorWithKernel {
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
:
OperatorWithKernel
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
if
(
ctx
->
IsRuntime
())
{
return
;
}
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
"Input(X) of HashOp should not be null."
);
"Input(X) of HashOp should not be null."
);
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
PADDLE_ENFORCE
(
ctx
->
HasOutput
(
"Out"
),
...
@@ -36,15 +38,8 @@ class HashOp : public framework::OperatorWithKernel {
...
@@ -36,15 +38,8 @@ class HashOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ
(
dims
.
size
(),
2UL
,
PADDLE_ENFORCE_EQ
(
dims
.
size
(),
2UL
,
"The input of hash_op's dimensions must be 2"
);
"The input of hash_op's dimensions must be 2"
);
std
::
vector
<
int64_t
>
out_dims
;
std
::
vector
<
int64_t
>
out_dims
;
out_dims
.
reserve
(
dims
.
size
()
+
1
);
// copy all dims except the last one
for
(
int
i
=
0u
;
i
!=
dims
.
size
()
-
1
;
++
i
)
{
out_dims
.
emplace_back
(
dims
[
i
]);
}
int
num_hash
=
ctx
->
Attrs
().
Get
<
int
>
(
"num_hash"
);
int
num_hash
=
ctx
->
Attrs
().
Get
<
int
>
(
"num_hash"
);
out_dims
.
emplace_back
(
num_hash
);
HashOutputSize
(
dims
,
out_dims
,
num_hash
);
// keep the last dim to 1
out_dims
.
emplace_back
(
1
);
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dims
));
ctx
->
SetOutputDim
(
"Out"
,
framework
::
make_ddim
(
out_dims
));
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
ctx
->
ShareLoD
(
"X"
,
/*->*/
"Out"
);
...
@@ -71,4 +66,4 @@ $$Out = scale * X$$
...
@@ -71,4 +66,4 @@ $$Out = scale * X$$
namespace
ops
=
paddle
::
operators
;
namespace
ops
=
paddle
::
operators
;
REGISTER_OP_WITHOUT_GRADIENT
(
hash
,
ops
::
HashOp
,
ops
::
HashOpMaker
);
REGISTER_OP_WITHOUT_GRADIENT
(
hash
,
ops
::
HashOp
,
ops
::
HashOpMaker
);
REGISTER_OP_CPU_KERNEL
(
hash
,
ops
::
HashKer
el
<
int
>
,
ops
::
HashKer
el
<
int64_t
>
);
REGISTER_OP_CPU_KERNEL
(
hash
,
ops
::
HashKer
nel
<
int
>
,
ops
::
HashKern
el
<
int64_t
>
);
paddle/fluid/operators/hash_op.h
浏览文件 @
34404f9c
...
@@ -17,21 +17,34 @@ limitations under the License. */
...
@@ -17,21 +17,34 @@ limitations under the License. */
extern
"C"
{
extern
"C"
{
#include <xxhash.h>
#include <xxhash.h>
}
}
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/framework/op_registry.h"
namespace
paddle
{
namespace
paddle
{
namespace
operators
{
namespace
operators
{
// template <typename DeviceContext, typename T>
inline
void
HashOutputSize
(
const
framework
::
DDim
&
in_dims
,
std
::
vector
<
int64_t
>&
out_dims
,
// NOLINT
int
num_hash
)
{
out_dims
.
reserve
(
in_dims
.
size
()
+
1
);
// copy all dims except the last one
for
(
int
i
=
0u
;
i
!=
in_dims
.
size
()
-
1
;
++
i
)
{
out_dims
.
emplace_back
(
in_dims
[
i
]);
}
out_dims
.
emplace_back
(
num_hash
);
// keep the last dim to 1
out_dims
.
emplace_back
(
1
);
}
template
<
typename
T
>
template
<
typename
T
>
class
HashKerel
:
public
framework
::
OpKernel
<
T
>
{
class
HashKer
n
el
:
public
framework
::
OpKernel
<
T
>
{
public:
public:
virtual
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
{
virtual
void
Compute
(
const
framework
::
ExecutionContext
&
context
)
const
{
auto
*
out_t
=
context
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
auto
*
out_t
=
context
.
Output
<
framework
::
LoDTensor
>
(
"Out"
);
auto
*
in_t
=
context
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
auto
*
in_t
=
context
.
Input
<
framework
::
LoDTensor
>
(
"X"
);
int
mod_by
=
context
.
Attr
<
int
>
(
"mod_by"
);
int
mod_by
=
context
.
Attr
<
int
>
(
"mod_by"
);
int
num_hash
=
context
.
Attr
<
int
>
(
"num_hash"
);
int
num_hash
=
context
.
Attr
<
int
>
(
"num_hash"
);
auto
*
output
=
out_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
in_dims
=
in_t
->
dims
();
auto
in_dims
=
in_t
->
dims
();
auto
in_lod
=
in_t
->
lod
();
auto
in_lod
=
in_t
->
lod
();
...
@@ -39,6 +52,11 @@ class HashKerel : public framework::OpKernel<T> {
...
@@ -39,6 +52,11 @@ class HashKerel : public framework::OpKernel<T> {
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
in_lod
[
0
].
back
(),
static_cast
<
uint64_t
>
(
in_dims
[
0
]),
in_lod
[
0
].
back
(),
"The actual input data's size mismatched with LoD information."
);
"The actual input data's size mismatched with LoD information."
);
std
::
vector
<
int64_t
>
out_dims
;
HashOutputSize
(
in_dims
,
out_dims
,
num_hash
);
out_t
->
Resize
(
framework
::
make_ddim
(
out_dims
));
auto
*
output
=
out_t
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
seq_length
=
in_dims
[
0
];
auto
seq_length
=
in_dims
[
0
];
auto
last_dim
=
in_dims
[
in_dims
.
size
()
-
1
];
auto
last_dim
=
in_dims
[
in_dims
.
size
()
-
1
];
auto
*
input
=
in_t
->
data
<
T
>
();
auto
*
input
=
in_t
->
data
<
T
>
();
...
@@ -49,6 +67,7 @@ class HashKerel : public framework::OpKernel<T> {
...
@@ -49,6 +67,7 @@ class HashKerel : public framework::OpKernel<T> {
}
}
input
+=
last_dim
;
input
+=
last_dim
;
}
}
out_t
->
set_lod
(
in_t
->
lod
());
}
}
};
};
...
...
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cc
浏览文件 @
34404f9c
...
@@ -22,6 +22,9 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel {
...
@@ -22,6 +22,9 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel {
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
using
framework
::
OperatorWithKernel
::
OperatorWithKernel
;
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
void
InferShape
(
framework
::
InferShapeContext
*
ctx
)
const
override
{
if
(
ctx
->
IsRuntime
())
{
return
;
}
PADDLE_ENFORCE
(
PADDLE_ENFORCE
(
ctx
->
HasInput
(
"X"
),
ctx
->
HasInput
(
"X"
),
"Input(X) of SequecceEnumerate operator should not be null."
);
"Input(X) of SequecceEnumerate operator should not be null."
);
...
@@ -33,9 +36,9 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel {
...
@@ -33,9 +36,9 @@ class SequenceEnumerateOp : public framework::OperatorWithKernel {
PADDLE_ENFORCE_EQ
(
PADDLE_ENFORCE_EQ
(
x_dims
.
size
(),
2
,
x_dims
.
size
(),
2
,
"Input(X) of SequenceEnumerate operator's rank should be 2."
);
"Input(X) of SequenceEnumerate operator's rank should be 2."
);
PADDLE_ENFORCE_EQ
(
PADDLE_ENFORCE_EQ
(
x_dims
[
1
],
1
,
x_dims
[
1
],
1
,
"Input(X) of SequenceEnumerate operator's 2nd "
"Input(X) of SequenceEnumerate operator's 2nd
dimension should be 1."
);
"
dimension should be 1."
);
const
auto
win_size
=
ctx
->
Attrs
().
Get
<
int
>
(
"win_size"
);
const
auto
win_size
=
ctx
->
Attrs
().
Get
<
int
>
(
"win_size"
);
ctx
->
SetOutputDim
(
"Out"
,
{
x_dims
[
0
],
win_size
});
ctx
->
SetOutputDim
(
"Out"
,
{
x_dims
[
0
],
win_size
});
...
...
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.cu
浏览文件 @
34404f9c
...
@@ -65,6 +65,7 @@ class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
...
@@ -65,6 +65,7 @@ class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
auto
lod0
=
in_lod
[
0
];
auto
lod0
=
in_lod
[
0
];
auto
in_len
=
in
->
numel
();
auto
in_len
=
in
->
numel
();
auto
in_data
=
in
->
data
<
T
>
();
auto
in_data
=
in
->
data
<
T
>
();
out
->
Resize
({
in_dims
[
0
],
win_size
});
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
// Copy LoD to GPU
// Copy LoD to GPU
const
size_t
*
dev_in_lod_ptr
=
lod0
.
CUDAData
(
context
.
GetPlace
());
const
size_t
*
dev_in_lod_ptr
=
lod0
.
CUDAData
(
context
.
GetPlace
());
...
@@ -72,6 +73,7 @@ class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
...
@@ -72,6 +73,7 @@ class SequenceEnumerateOpCUDAKernel : public framework::OpKernel<T> {
CalcOutPut
<<<
(
in_len
-
1
)
/
PADDLE_CUDA_NUM_THREADS
+
1
,
CalcOutPut
<<<
(
in_len
-
1
)
/
PADDLE_CUDA_NUM_THREADS
+
1
,
PADDLE_CUDA_NUM_THREADS
,
0
,
stream
>>>
(
PADDLE_CUDA_NUM_THREADS
,
0
,
stream
>>>
(
in_data
,
dev_in_lod_ptr
,
lod0
.
size
(),
win_size
,
pad_value
,
out_data
);
in_data
,
dev_in_lod_ptr
,
lod0
.
size
(),
win_size
,
pad_value
,
out_data
);
out
->
set_lod
(
in
->
lod
());
}
}
};
};
...
...
paddle/fluid/operators/sequence_ops/sequence_enumerate_op.h
浏览文件 @
34404f9c
...
@@ -39,6 +39,7 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
...
@@ -39,6 +39,7 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
// Generate enumerate sequence set
// Generate enumerate sequence set
auto
lod0
=
in_lod
[
0
];
auto
lod0
=
in_lod
[
0
];
auto
in_data
=
in
->
data
<
T
>
();
auto
in_data
=
in
->
data
<
T
>
();
out
->
Resize
({
in_dims
[
0
],
win_size
});
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
auto
out_data
=
out
->
mutable_data
<
T
>
(
context
.
GetPlace
());
for
(
size_t
i
=
0
;
i
<
lod0
.
size
()
-
1
;
++
i
)
{
for
(
size_t
i
=
0
;
i
<
lod0
.
size
()
-
1
;
++
i
)
{
for
(
size_t
idx
=
lod0
[
i
];
idx
<
lod0
[
i
+
1
];
++
idx
)
{
for
(
size_t
idx
=
lod0
[
i
];
idx
<
lod0
[
i
+
1
];
++
idx
)
{
...
@@ -49,6 +50,7 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
...
@@ -49,6 +50,7 @@ class SequenceEnumerateKernel : public framework::OpKernel<T> {
}
}
}
}
}
}
out
->
set_lod
(
in
->
lod
());
}
}
};
};
...
...
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