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ca392c7e
编写于
3月 15, 2019
作者:
M
minqiyang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Implement infer var type context
上级
0b49e43d
变更
36
隐藏空白更改
内联
并排
Showing
36 changed file
with
283 addition
and
261 deletion
+283
-261
paddle/fluid/framework/details/graph_test_base.h
paddle/fluid/framework/details/graph_test_base.h
+5
-5
paddle/fluid/framework/details/op_registry.h
paddle/fluid/framework/details/op_registry.h
+2
-2
paddle/fluid/framework/ir/graph_test.cc
paddle/fluid/framework/ir/graph_test.cc
+7
-7
paddle/fluid/framework/op_desc.cc
paddle/fluid/framework/op_desc.cc
+3
-1
paddle/fluid/framework/type_defs.h
paddle/fluid/framework/type_defs.h
+2
-1
paddle/fluid/framework/var_type_inference.h
paddle/fluid/framework/var_type_inference.h
+97
-9
paddle/fluid/framework/var_type_inference_test.cc
paddle/fluid/framework/var_type_inference_test.cc
+6
-6
paddle/fluid/operators/beam_search_decode_op.cc
paddle/fluid/operators/beam_search_decode_op.cc
+9
-12
paddle/fluid/operators/beam_search_op.cc
paddle/fluid/operators/beam_search_op.cc
+6
-9
paddle/fluid/operators/controlflow/get_places_op.cc
paddle/fluid/operators/controlflow/get_places_op.cc
+3
-5
paddle/fluid/operators/controlflow/tensor_array_read_write_op.cc
...fluid/operators/controlflow/tensor_array_read_write_op.cc
+6
-9
paddle/fluid/operators/distributed_ops/merge_ids_op.cc
paddle/fluid/operators/distributed_ops/merge_ids_op.cc
+4
-5
paddle/fluid/operators/distributed_ops/split_ids_op.cc
paddle/fluid/operators/distributed_ops/split_ids_op.cc
+4
-5
paddle/fluid/operators/fill_constant_op.cc
paddle/fluid/operators/fill_constant_op.cc
+4
-5
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
+6
-8
paddle/fluid/operators/get_tensor_from_selected_rows_op.cc
paddle/fluid/operators/get_tensor_from_selected_rows_op.cc
+6
-9
paddle/fluid/operators/hierarchical_sigmoid_op.cc
paddle/fluid/operators/hierarchical_sigmoid_op.cc
+9
-15
paddle/fluid/operators/lod_rank_table_op.cc
paddle/fluid/operators/lod_rank_table_op.cc
+3
-5
paddle/fluid/operators/lod_tensor_to_array_op.cc
paddle/fluid/operators/lod_tensor_to_array_op.cc
+3
-4
paddle/fluid/operators/lookup_table_op.cc
paddle/fluid/operators/lookup_table_op.cc
+6
-8
paddle/fluid/operators/nce_op.cc
paddle/fluid/operators/nce_op.cc
+6
-8
paddle/fluid/operators/ngraph/ngraph_engine_op.cc
paddle/fluid/operators/ngraph/ngraph_engine_op.cc
+1
-2
paddle/fluid/operators/optimizers/lars_momentum_op.cc
paddle/fluid/operators/optimizers/lars_momentum_op.cc
+3
-4
paddle/fluid/operators/optimizers/momentum_op.cc
paddle/fluid/operators/optimizers/momentum_op.cc
+7
-11
paddle/fluid/operators/optimizers/sgd_op.cc
paddle/fluid/operators/optimizers/sgd_op.cc
+6
-8
paddle/fluid/operators/py_func_op.cc
paddle/fluid/operators/py_func_op.cc
+16
-20
paddle/fluid/operators/reader/create_custom_reader_op.cc
paddle/fluid/operators/reader/create_custom_reader_op.cc
+11
-12
paddle/fluid/operators/reader/read_op.cc
paddle/fluid/operators/reader/read_op.cc
+7
-10
paddle/fluid/operators/reader/reader_op_registry.h
paddle/fluid/operators/reader/reader_op_registry.h
+2
-4
paddle/fluid/operators/save_op.cc
paddle/fluid/operators/save_op.cc
+3
-6
paddle/fluid/operators/scale_op.cc
paddle/fluid/operators/scale_op.cc
+5
-9
paddle/fluid/operators/split_selected_rows_op.cc
paddle/fluid/operators/split_selected_rows_op.cc
+3
-4
paddle/fluid/operators/sum_op.cc
paddle/fluid/operators/sum_op.cc
+12
-19
paddle/fluid/operators/tensor_array_to_tensor_op.cc
paddle/fluid/operators/tensor_array_to_tensor_op.cc
+3
-4
paddle/fluid/operators/tensorrt/tensorrt_engine_op.cc
paddle/fluid/operators/tensorrt/tensorrt_engine_op.cc
+1
-2
paddle/fluid/operators/uniform_random_op.cc
paddle/fluid/operators/uniform_random_op.cc
+6
-8
未找到文件。
paddle/fluid/framework/details/graph_test_base.h
浏览文件 @
ca392c7e
...
...
@@ -68,11 +68,11 @@ class SplitOpMaker : public OpProtoAndCheckerMaker {
class
DummyVarTypeInference
:
public
VarTypeInference
{
public:
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
override
{
auto
&
inputs
=
op_desc
.
Input
(
"X"
);
auto
type
=
block
->
Var
(
inputs
.
front
())
->
GetType
(
);
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
block
->
Var
(
out_var_name
)
->
SetType
(
type
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
inputs
=
ctx
.
Input
(
"X"
);
auto
type
=
ctx
.
GetType
(
inputs
.
front
()
);
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
ctx
.
SetType
(
out_var_name
,
type
);
}
};
...
...
paddle/fluid/framework/details/op_registry.h
浏览文件 @
ca392c7e
...
...
@@ -127,9 +127,9 @@ struct OpInfoFiller<T, kGradOpDescMaker> {
template
<
typename
T
>
struct
OpInfoFiller
<
T
,
kVarTypeInference
>
{
void
operator
()(
const
char
*
op_type
,
OpInfo
*
info
)
const
{
info
->
infer_var_type_
=
[](
const
OpDesc
&
fwd_op
,
BlockDesc
*
block
)
{
info
->
infer_var_type_
=
[](
InferVarTypeContext
&
context
)
{
T
inference
;
inference
(
fwd_op
,
block
);
inference
(
context
);
};
}
};
...
...
paddle/fluid/framework/ir/graph_test.cc
浏览文件 @
ca392c7e
...
...
@@ -43,20 +43,20 @@ class SumOpMaker : public OpProtoAndCheckerMaker {
class
SumOpVarTypeInference
:
public
VarTypeInference
{
public:
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
override
{
auto
&
inputs
=
op_desc
.
Input
(
"X"
);
void
operator
()(
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
inputs
=
ctx
.
Input
(
"X"
);
auto
default_var_type
=
proto
::
VarType
::
SELECTED_ROWS
;
bool
any_input_is_lod_tensor
=
std
::
any_of
(
inputs
.
begin
(),
inputs
.
end
(),
[
block
](
const
std
::
string
&
name
)
{
return
block
->
Var
(
name
)
->
GetType
(
)
==
proto
::
VarType
::
LOD_TENSOR
;
inputs
.
begin
(),
inputs
.
end
(),
[
ctx
](
const
std
::
string
&
name
)
{
return
ctx
.
GetType
(
name
)
==
proto
::
VarType
::
LOD_TENSOR
;
});
if
(
any_input_is_lod_tensor
)
{
default_var_type
=
proto
::
VarType
::
LOD_TENSOR
;
}
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
block
->
Var
(
out_var_name
)
->
SetType
(
default_var_type
);
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
ctx
.
SetType
(
out_var_name
,
default_var_type
);
}
};
...
...
@@ -71,7 +71,7 @@ class DummyOpMaker : public OpProtoAndCheckerMaker {
class
DummyOpVarTypeInference
:
public
VarTypeInference
{
public:
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
override
{}
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{}
};
}
// namespace framework
}
// namespace paddle
...
...
paddle/fluid/framework/op_desc.cc
浏览文件 @
ca392c7e
...
...
@@ -24,6 +24,7 @@ limitations under the License. */
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
#include "paddle/fluid/framework/shape_inference.h"
#include "paddle/fluid/framework/var_type_inference.h"
namespace
paddle
{
namespace
framework
{
...
...
@@ -677,7 +678,8 @@ void OpDesc::InferVarType(BlockDesc *block) const {
// var type inference. Hence, we don't do any "default" setting here.
auto
&
info
=
OpInfoMap
::
Instance
().
Get
(
this
->
Type
());
if
(
info
.
infer_var_type_
)
{
info
.
infer_var_type_
(
*
this
,
block
);
InferVarTypeContext
context
(
this
,
block
);
info
.
infer_var_type_
(
context
);
}
}
...
...
paddle/fluid/framework/type_defs.h
浏览文件 @
ca392c7e
...
...
@@ -27,6 +27,7 @@ namespace framework {
class
OperatorBase
;
class
OpDesc
;
class
InferShapeContext
;
class
InferVarTypeContext
;
class
BlockDesc
;
class
Variable
;
...
...
@@ -53,7 +54,7 @@ using GradOpMakerFN = std::function<std::vector<std::unique_ptr<OpDesc>>(
const
std
::
vector
<
BlockDesc
*>&
grad_block
)
>
;
using
InferVarTypeFN
=
std
::
function
<
void
(
const
OpDesc
&
/*op_desc*/
,
BlockDesc
*
/*block
*/
)
>
;
std
::
function
<
void
(
framework
::
InferVarTypeContext
&
/*context
*/
)
>
;
using
InferShapeFN
=
std
::
function
<
void
(
InferShapeContext
*
)
>
;
...
...
paddle/fluid/framework/var_type_inference.h
浏览文件 @
ca392c7e
...
...
@@ -14,6 +14,7 @@ limitations under the License. */
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/block_desc.h"
#include "paddle/fluid/framework/op_desc.h"
#include "paddle/fluid/framework/type_defs.h"
...
...
@@ -21,26 +22,113 @@ limitations under the License. */
namespace
paddle
{
namespace
framework
{
class
OpDesc
;
class
BlockDesc
;
// default infer var type context
class
InferVarTypeContext
{
public:
InferVarTypeContext
(
const
OpDesc
*
op
,
BlockDesc
*
block
)
:
op_
(
op
),
block_
(
block
)
{}
Attribute
GetAttr
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
op_
);
return
op_
->
GetAttr
(
name
);
}
inline
bool
HasVar
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
return
block_
->
FindVarRecursive
(
name
)
!=
nullptr
;
}
inline
bool
HasInput
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
op_
);
return
op_
->
Inputs
().
count
(
name
)
>
0
;
}
inline
bool
HasOutput
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
op_
);
return
op_
->
Outputs
().
count
(
name
)
>
0
;
}
inline
const
std
::
vector
<
std
::
string
>&
Input
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
op_
);
return
op_
->
Input
(
name
);
}
inline
const
std
::
vector
<
std
::
string
>&
Output
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
op_
);
return
op_
->
Output
(
name
);
}
inline
proto
::
VarType
::
Type
GetType
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
return
block_
->
FindRecursiveOrCreateVar
(
name
).
GetType
();
}
inline
void
SetType
(
const
std
::
string
&
name
,
proto
::
VarType
::
Type
type
)
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
block_
->
FindRecursiveOrCreateVar
(
name
).
SetType
(
type
);
}
inline
proto
::
VarType
::
Type
GetDataType
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
return
block_
->
FindRecursiveOrCreateVar
(
name
).
GetDataType
();
}
inline
void
SetDataType
(
const
std
::
string
&
name
,
proto
::
VarType
::
Type
type
)
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
block_
->
FindRecursiveOrCreateVar
(
name
).
SetDataType
(
type
);
}
inline
std
::
vector
<
int64_t
>
GetShape
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
return
block_
->
FindRecursiveOrCreateVar
(
name
).
GetShape
();
}
inline
void
SetShape
(
const
std
::
string
&
name
,
const
std
::
vector
<
int64_t
>&
dims
)
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
block_
->
FindRecursiveOrCreateVar
(
name
).
SetShape
(
dims
);
}
inline
int32_t
GetLoDLevel
(
const
std
::
string
&
name
)
const
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
return
block_
->
FindRecursiveOrCreateVar
(
name
).
GetLoDLevel
();
}
inline
void
SetLoDLevel
(
const
std
::
string
&
name
,
int32_t
lod_level
)
{
PADDLE_ENFORCE_NOT_NULL
(
block_
);
block_
->
FindRecursiveOrCreateVar
(
name
).
SetLoDLevel
(
lod_level
);
}
private:
const
OpDesc
*
op_
;
BlockDesc
*
block_
;
};
// infer var type context for imperative mode
class
RuntimeInferVarTypeContext
:
public
InferVarTypeContext
{
public:
RuntimeInferVarTypeContext
()
:
InferVarTypeContext
(
nullptr
,
nullptr
)
{}
};
class
VarTypeInference
{
public:
virtual
~
VarTypeInference
()
{}
virtual
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
=
0
;
virtual
void
operator
()(
InferVarTypeContext
&
context
)
const
=
0
;
// NOLINT
};
class
PassInDtypeAndVarTypeToOutput
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
final
{
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
final
{
// NOLINT
auto
in_out_var_names
=
this
->
GetInputOutputWithSameType
();
for
(
auto
&
i_o_n
:
in_out_var_names
)
{
auto
&
x_name
=
op_desc
.
Input
(
i_o_n
.
first
).
at
(
0
);
auto
&
out_name
=
op_desc
.
Output
(
i_o_n
.
second
).
at
(
0
);
auto
&
x_name
=
ctx
.
Input
(
i_o_n
.
first
).
at
(
0
);
auto
&
out_name
=
ctx
.
Output
(
i_o_n
.
second
).
at
(
0
);
auto
&
x
=
block
->
FindRecursiveOrCreateVar
(
x_name
);
auto
&
out
=
block
->
FindRecursiveOrCreateVar
(
out_name
);
out
.
SetType
(
x
.
GetType
());
out
.
SetDataType
(
x
.
GetDataType
());
ctx
.
SetType
(
out_name
,
ctx
.
GetType
(
x_name
));
ctx
.
SetDataType
(
out_name
,
ctx
.
GetDataType
(
x_name
));
}
}
...
...
paddle/fluid/framework/var_type_inference_test.cc
浏览文件 @
ca392c7e
...
...
@@ -44,20 +44,20 @@ class SumOpMaker : public OpProtoAndCheckerMaker {
class
SumOpVarTypeInference
:
public
VarTypeInference
{
public:
void
operator
()(
const
OpDesc
&
op_desc
,
BlockDesc
*
block
)
const
override
{
auto
&
inputs
=
op_desc
.
Input
(
"X"
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
inputs
=
ctx
.
Input
(
"X"
);
auto
default_var_type
=
proto
::
VarType
::
SELECTED_ROWS
;
bool
any_input_is_lod_tensor
=
std
::
any_of
(
inputs
.
begin
(),
inputs
.
end
(),
[
block
](
const
std
::
string
&
name
)
{
return
block
->
Var
(
name
)
->
GetType
(
)
==
proto
::
VarType
::
LOD_TENSOR
;
inputs
.
begin
(),
inputs
.
end
(),
[
ctx
](
const
std
::
string
&
name
)
{
return
ctx
.
GetType
(
name
)
==
proto
::
VarType
::
LOD_TENSOR
;
});
if
(
any_input_is_lod_tensor
)
{
default_var_type
=
proto
::
VarType
::
LOD_TENSOR
;
}
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
block
->
Var
(
out_var_name
)
->
SetType
(
default_var_type
);
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
ctx
.
SetType
(
out_var_name
,
default_var_type
);
}
};
}
// namespace framework
...
...
paddle/fluid/operators/beam_search_decode_op.cc
浏览文件 @
ca392c7e
...
...
@@ -178,10 +178,10 @@ Beam Search Decode Operator. This Operator constructs the full hypotheses for
each source sentence by walking back along the LoDTensorArray Input(ids)
whose lods can be used to restore the path in the beam search tree.
The Output(SentenceIds) and Output(SentenceScores) separately contain the
generated id sequences and the corresponding scores. The shapes and lods of the
two LodTensor are same. The lod level is 2 and the two levels separately
indicate how many hypotheses each source sentence has and how many ids each
The Output(SentenceIds) and Output(SentenceScores) separately contain the
generated id sequences and the corresponding scores. The shapes and lods of the
two LodTensor are same. The lod level is 2 and the two levels separately
indicate how many hypotheses each source sentence has and how many ids each
hypothesis has.
)DOC"
);
}
...
...
@@ -203,15 +203,12 @@ class BeamSearchDecodeInferShape : public framework::InferShapeBase {
class
BeamSearchDecodeInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
o
:
op_desc
.
Output
(
"SentenceIds"
))
{
auto
&
sentence_ids
=
block
->
FindRecursiveOrCreateVar
(
o
);
sentence_ids
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
o
:
ctx
.
Output
(
"SentenceIds"
))
{
ctx
.
SetType
(
o
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
for
(
auto
&
o
:
op_desc
.
Output
(
"SentenceScores"
))
{
auto
&
sentence_scores
=
block
->
FindRecursiveOrCreateVar
(
o
);
sentence_scores
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
for
(
auto
&
o
:
ctx
.
Output
(
"SentenceScores"
))
{
ctx
.
SetType
(
o
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
}
};
...
...
paddle/fluid/operators/beam_search_op.cc
浏览文件 @
ca392c7e
...
...
@@ -65,7 +65,7 @@ class BeamSearchOpMaker : public framework::OpProtoAndCheckerMaker {
.
SetDefault
(
true
);
AddComment
(
R"DOC(
This operator does the search in beams for one time step.
This operator does the search in beams for one time step.
Specifically, it selects the top-K candidate word ids of current step from
Input(ids) according to their Input(scores) for all source sentences,
where K is Attr(beam_size) and Input(ids), Input(scores) are predicted results
...
...
@@ -120,15 +120,12 @@ class BeamSearchOp : public framework::OperatorWithKernel {
class
BeamSearchInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
o
:
op_desc
.
Output
(
"selected_ids"
))
{
auto
&
selected_ids
=
block
->
FindRecursiveOrCreateVar
(
o
);
selected_ids
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
o
:
ctx
.
Output
(
"selected_ids"
))
{
ctx
.
SetType
(
o
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
for
(
auto
&
o
:
op_desc
.
Output
(
"selected_scores"
))
{
auto
&
selected_scores
=
block
->
FindRecursiveOrCreateVar
(
o
);
selected_scores
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
for
(
auto
&
o
:
ctx
.
Output
(
"selected_scores"
))
{
ctx
.
SetType
(
o
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
}
};
...
...
paddle/fluid/operators/controlflow/get_places_op.cc
浏览文件 @
ca392c7e
...
...
@@ -93,11 +93,9 @@ execution.
class
GetPlacesInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
o_name
:
op_desc
.
Output
(
"Out"
))
{
block
->
FindRecursiveOrCreateVar
(
o_name
).
SetType
(
framework
::
proto
::
VarType
::
PLACE_LIST
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
o_name
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
o_name
,
framework
::
proto
::
VarType
::
PLACE_LIST
);
}
}
};
...
...
paddle/fluid/operators/controlflow/tensor_array_read_write_op.cc
浏览文件 @
ca392c7e
...
...
@@ -100,16 +100,13 @@ class WriteToArrayInferShape : public framework::InferShapeBase {
class
WriteToArrayInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
x_name
=
op_desc
.
Input
(
"X"
)[
0
];
auto
out_name
=
op_desc
.
Output
(
"Out"
)[
0
];
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
x_name
=
ctx
.
Input
(
"X"
)[
0
];
auto
out_name
=
ctx
.
Output
(
"Out"
)[
0
];
VLOG
(
10
)
<<
"Set Variable "
<<
out_name
<<
" as LOD_TENSOR_ARRAY"
;
auto
&
out
=
block
->
FindRecursiveOrCreateVar
(
out_name
);
out
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
auto
*
x
=
block
->
FindVarRecursive
(
x_name
);
if
(
x
!=
nullptr
)
{
out
.
SetDataType
(
x
->
GetDataType
());
ctx
.
SetType
(
out_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
if
(
ctx
.
HasVar
(
x_name
))
{
ctx
.
SetDataType
(
out_name
,
ctx
.
GetDataType
(
x_name
));
}
}
};
...
...
paddle/fluid/operators/distributed_ops/merge_ids_op.cc
浏览文件 @
ca392c7e
...
...
@@ -114,11 +114,10 @@ class MergeIdsOp : public framework::OperatorWithKernel {
class
MergeIdsOpInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
*
input_var
=
block
->
Var
(
op_desc
.
Input
(
"Ids"
)[
0
]);
for
(
auto
&
out_var
:
op_desc
.
Output
(
"Out"
))
{
block
->
Var
(
out_var
)
->
SetType
(
input_var
->
GetType
());
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
input_type
=
ctx
.
GetType
(
ctx
.
Input
(
"Ids"
)[
0
]);
for
(
auto
&
out_var
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
out_var
,
input_type
);
}
}
};
...
...
paddle/fluid/operators/distributed_ops/split_ids_op.cc
浏览文件 @
ca392c7e
...
...
@@ -71,11 +71,10 @@ class SplitIdsOp : public framework::OperatorWithKernel {
class
SplitIdsOpInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
*
input_var
=
block
->
Var
(
op_desc
.
Input
(
"Ids"
)[
0
]);
for
(
auto
&
out_var
:
op_desc
.
Output
(
"Out"
))
{
block
->
Var
(
out_var
)
->
SetType
(
input_var
->
GetType
());
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
input_type
=
ctx
.
GetType
(
ctx
.
Input
(
"Ids"
)[
0
]);
for
(
auto
&
out_var
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
out_var
,
input_type
);
}
}
};
...
...
paddle/fluid/operators/fill_constant_op.cc
浏览文件 @
ca392c7e
...
...
@@ -39,12 +39,11 @@ class FillConstantOp : public framework::OperatorWithKernel {
class
FillConstantOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
data_type
=
static_cast
<
framework
::
proto
::
VarType
::
Type
>
(
boost
::
get
<
int
>
(
op_desc
.
GetAttr
(
"dtype"
)));
auto
&
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
block
->
Var
(
out_var_name
)
->
SetDataType
(
data_type
);
boost
::
get
<
int
>
(
ctx
.
GetAttr
(
"dtype"
)));
auto
&
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
ctx
.
SetDataType
(
out_var_name
,
data_type
);
}
};
...
...
paddle/fluid/operators/fused/fused_embedding_seq_pool_op.cc
浏览文件 @
ca392c7e
...
...
@@ -137,22 +137,20 @@ class FusedEmbeddingSeqPoolOpGrad : public framework::OperatorWithKernel {
class
FusedEmbeddingSeqPoolOpGradVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
out_var_name
=
op_desc
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
attr
=
op_desc
.
GetAttr
(
"is_sparse"
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
out_var_name
=
ctx
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
attr
=
ctx
.
GetAttr
(
"is_sparse"
);
bool
is_sparse
=
boost
::
get
<
bool
>
(
attr
);
if
(
is_sparse
)
{
VLOG
(
3
)
<<
"fused_embedding_seq_pool_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to SelectedRows"
;
block
->
Var
(
out_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
{
VLOG
(
3
)
<<
"fused_embedding_seq_pool_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to LoDTensor"
;
block
->
Var
(
out_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
block
->
Var
(
out_var_name
)
->
SetDataType
(
block
->
Var
(
"W"
)
->
GetDataType
(
));
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
ctx
.
Input
(
"W"
)[
0
]
));
}
};
...
...
paddle/fluid/operators/get_tensor_from_selected_rows_op.cc
浏览文件 @
ca392c7e
...
...
@@ -81,15 +81,12 @@ GetTensorFromSelectedRows is used to get the tensor from SelectedRows.
class
GetTensorFromSelectedRowsOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
final
{
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
auto
in_var_name
=
op_desc
.
Input
(
"X"
).
front
();
auto
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_name
);
auto
in_var
=
block
->
FindRecursiveOrCreateVar
(
in_var_name
);
out_var
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
out_var
.
SetDataType
(
in_var
.
GetDataType
());
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
{
// NOLINT
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
auto
in_var_name
=
ctx
.
Input
(
"X"
).
front
();
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
in_var_name
));
}
};
...
...
paddle/fluid/operators/hierarchical_sigmoid_op.cc
浏览文件 @
ca392c7e
...
...
@@ -197,38 +197,32 @@ class HierarchicalSigmoidGradOp : public framework::OperatorWithKernel {
class
HierarchicalSigmoidGradOpGradVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
w_grad_var_name
=
op_desc
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
bias_grad_var_name_vec
=
op_desc
.
Output
(
framework
::
GradVarName
(
"Bias"
));
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
w_grad_var_name
=
ctx
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
bias_grad_var_name_vec
=
ctx
.
Output
(
framework
::
GradVarName
(
"Bias"
));
std
::
string
bias_grad_var_name
;
bool
hasBias
=
false
;
if
(
bias_grad_var_name_vec
.
size
())
{
hasBias
=
true
;
bias_grad_var_name
=
op_desc
.
Output
(
framework
::
GradVarName
(
"Bias"
)).
front
();
bias_grad_var_name
=
ctx
.
Output
(
framework
::
GradVarName
(
"Bias"
)).
front
();
}
auto
attr
=
op_desc
.
GetAttr
(
"is_sparse"
);
auto
attr
=
ctx
.
GetAttr
(
"is_sparse"
);
bool
is_sparse
=
boost
::
get
<
bool
>
(
attr
);
if
(
is_sparse
)
{
VLOG
(
30
)
<<
"hierarchical_sigmoid_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to SelectedRows"
;
block
->
Var
(
w_grad_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
ctx
.
SetType
(
w_grad_var_name
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
{
VLOG
(
30
)
<<
"hierarchical_sigmoid_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to LoDTensor"
;
block
->
Var
(
w_grad_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
w_grad_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
if
(
hasBias
)
{
VLOG
(
30
)
<<
"hierarchical_sigmoid_grad op "
<<
framework
::
GradVarName
(
"Bias"
)
<<
" is set to LoDTensor"
;
block
->
Var
(
bias_grad_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
bias_grad_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
block
->
Var
(
w_grad_var_name
)
->
SetDataType
(
block
->
Var
(
"W"
)
->
GetDataType
(
));
ctx
.
SetDataType
(
w_grad_var_name
,
ctx
.
GetDataType
(
ctx
.
Input
(
"W"
)[
0
]
));
}
};
...
...
paddle/fluid/operators/lod_rank_table_op.cc
浏览文件 @
ca392c7e
...
...
@@ -64,11 +64,9 @@ class LoDRankTableInferShape : public framework::InferShapeBase {
class
LoDRankTableInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
o
:
op_desc
.
Output
(
"Out"
))
{
block
->
FindRecursiveOrCreateVar
(
o
).
SetType
(
framework
::
proto
::
VarType
::
LOD_RANK_TABLE
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
o
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
o
,
framework
::
proto
::
VarType
::
LOD_RANK_TABLE
);
}
}
};
...
...
paddle/fluid/operators/lod_tensor_to_array_op.cc
浏览文件 @
ca392c7e
...
...
@@ -201,10 +201,9 @@ class LoDTensorToArrayInferShape : public framework::InferShapeBase {
class
LoDTensorToArrayInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
out_var
:
op_desc
.
Output
(
"Out"
))
{
block
->
Var
(
out_var
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
out_var
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
out_var
,
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
}
}
};
...
...
paddle/fluid/operators/lookup_table_op.cc
浏览文件 @
ca392c7e
...
...
@@ -147,22 +147,20 @@ class LookupTableOpGrad : public framework::OperatorWithKernel {
class
LookupTableOpGradVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
out_var_name
=
op_desc
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
attr
=
op_desc
.
GetAttr
(
"is_sparse"
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
out_var_name
=
ctx
.
Output
(
framework
::
GradVarName
(
"W"
)).
front
();
auto
attr
=
ctx
.
GetAttr
(
"is_sparse"
);
bool
is_sparse
=
boost
::
get
<
bool
>
(
attr
);
if
(
is_sparse
)
{
VLOG
(
3
)
<<
"lookup_table_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to SelectedRows"
;
block
->
Var
(
out_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
{
VLOG
(
3
)
<<
"lookup_table_grad op "
<<
framework
::
GradVarName
(
"W"
)
<<
" is set to LoDTensor"
;
block
->
Var
(
out_var_name
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
block
->
Var
(
out_var_name
)
->
SetDataType
(
block
->
Var
(
"W"
)
->
GetDataType
(
));
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
ctx
.
Input
(
"W"
)[
0
]
));
}
};
...
...
paddle/fluid/operators/nce_op.cc
浏览文件 @
ca392c7e
...
...
@@ -237,23 +237,21 @@ class NCEOpGrad : public framework::OperatorWithKernel {
class
NCEOpGradVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
weight_grad
=
op_desc
.
Output
(
framework
::
GradVarName
(
"Weight"
)).
front
();
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
weight_grad
=
ctx
.
Output
(
framework
::
GradVarName
(
"Weight"
)).
front
();
auto
attr
=
op_desc
.
GetAttr
(
"is_sparse"
);
auto
attr
=
ctx
.
GetAttr
(
"is_sparse"
);
bool
is_sparse
=
boost
::
get
<
bool
>
(
attr
);
if
(
is_sparse
)
{
VLOG
(
3
)
<<
"nce_op_grad op "
<<
weight_grad
<<
" and "
<<
" is set to SelectedRows"
;
block
->
Var
(
weight_grad
)
->
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
ctx
.
SetType
(
weight_grad
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
{
VLOG
(
3
)
<<
"nce_op_grad op "
<<
weight_grad
<<
" and "
<<
" is set to LoDTensor"
;
block
->
Var
(
weight_grad
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
weight_grad
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
block
->
Var
(
weight_grad
)
->
SetDataType
(
block
->
Var
(
"Input"
)
->
GetDataType
(
));
ctx
.
SetDataType
(
weight_grad
,
ctx
.
GetDataType
(
ctx
.
Input
(
"Input"
)[
0
]
));
}
};
...
...
paddle/fluid/operators/ngraph/ngraph_engine_op.cc
浏览文件 @
ca392c7e
...
...
@@ -37,8 +37,7 @@ class NgraphEngineOpMaker : public framework::OpProtoAndCheckerMaker {
class
NgraphEngineInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{}
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{}
};
}
// namespace operators
...
...
paddle/fluid/operators/optimizers/lars_momentum_op.cc
浏览文件 @
ca392c7e
...
...
@@ -56,9 +56,9 @@ This optimizer use LARS (https://arxiv.org/abs/1708.03888) to optimize each
weight using a local learning rate:
$$
local\_lr = \eta *
local\_lr = \eta *
\frac{\left \| param \right \|}{\left \| grad \right \| + \beta *\left \| param \right \|} \\
velocity = mu * velocity +
velocity = mu * velocity +
local\_lr * (grad + \beta * param) \\
param = param - velocity. \\
$$
...
...
@@ -72,8 +72,7 @@ use L2 regularizers in case of using LARS.
class
LarsMomentumOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{}
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{}
};
}
// namespace operators
}
// namespace paddle
...
...
paddle/fluid/operators/optimizers/momentum_op.cc
浏览文件 @
ca392c7e
...
...
@@ -21,18 +21,14 @@ using Tensor = framework::Tensor;
class
MomentumOpInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
input_var
=
op_desc
.
Input
(
"Param"
)[
0
];
for
(
auto
&
out_var
:
op_desc
.
Output
(
"ParamOut"
))
{
if
(
block
->
FindRecursiveOrCreateVar
(
input_var
).
GetType
()
==
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
block
->
FindRecursiveOrCreateVar
(
out_var
).
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
if
(
block
->
FindRecursiveOrCreateVar
(
input_var
).
GetType
()
==
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
input_var
=
ctx
.
Input
(
"Param"
)[
0
];
for
(
auto
&
out_var
:
ctx
.
Output
(
"ParamOut"
))
{
if
(
ctx
.
GetType
(
input_var
)
==
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
ctx
.
SetType
(
out_var
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
else
if
(
ctx
.
GetType
(
input_var
)
==
framework
::
proto
::
VarType
::
LOD_TENSOR
)
{
block
->
FindRecursiveOrCreateVar
(
out_var
).
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetType
(
out_var
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
else
{
PADDLE_THROW
(
"Only support LodTensor and SelectedRows, Unexpected Input Type."
);
...
...
paddle/fluid/operators/optimizers/sgd_op.cc
浏览文件 @
ca392c7e
...
...
@@ -50,20 +50,18 @@ class SGDOp : public framework::OperatorWithKernel {
class
SGDOpInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
input_var_n
=
op_desc
.
Input
(
"Param"
)[
0
];
auto
in_var_type
=
block
->
FindRecursiveOrCreateVar
(
input_var_n
).
GetType
();
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
input_var_n
=
ctx
.
Input
(
"Param"
)[
0
];
auto
in_var_type
=
ctx
.
GetType
(
input_var_n
);
PADDLE_ENFORCE
(
in_var_type
==
framework
::
proto
::
VarType
::
SELECTED_ROWS
||
in_var_type
==
framework
::
proto
::
VarType
::
LOD_TENSOR
,
"The input Var's type should be LoDtensor or SelectedRows,"
" but the received var(%s)'s type is %s"
,
input_var_n
,
in_var_type
);
for
(
auto
&
out_var_n
:
op_desc
.
Output
(
"ParamOut"
))
{
auto
&
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_n
);
if
(
out_var
.
GetType
()
!=
in_var_type
)
{
out_var
.
SetType
(
in_var_type
);
for
(
auto
&
out_var_n
:
ctx
.
Output
(
"ParamOut"
))
{
if
(
ctx
.
GetType
(
out_var_n
)
!=
in_var_type
)
{
ctx
.
SetType
(
out_var_n
,
in_var_type
);
}
}
}
...
...
paddle/fluid/operators/py_func_op.cc
浏览文件 @
ca392c7e
...
...
@@ -91,15 +91,12 @@ static void CallPythonFunc(py::object *callable,
}
}
class
PyFuncOpVarTypInference
:
public
framework
::
VarTypeInference
{
class
PyFuncOpVarTyp
e
Inference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
&
outs
=
op
.
Outputs
();
bool
has_out
=
(
outs
.
count
(
"Out"
)
>
0
&&
!
outs
.
at
(
"Out"
).
empty
());
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
bool
has_out
=
(
ctx
.
HasOutput
(
"Out"
)
&&
!
ctx
.
Output
(
"Out"
).
empty
());
auto
&
ins
=
op
.
Inputs
();
bool
has_in
=
(
ins
.
count
(
"X"
)
>
0
&&
!
ins
.
at
(
"X"
).
empty
());
bool
has_in
=
(
ctx
.
HasInput
(
"X"
)
&&
!
ctx
.
Input
(
"Out"
).
empty
());
/**
* X or Out can be empty, so that py_func can be more flexible
...
...
@@ -107,7 +104,7 @@ class PyFuncOpVarTypInference : public framework::VarTypeInference {
*/
PADDLE_ENFORCE
(
has_in
||
has_out
,
"Input(X) or Output(Out) must exist"
);
PADDLE_ENFORCE_GE
(
boost
::
get
<
int
>
(
op
.
GetAttr
(
kForwardPythonCallableId
)),
0
,
PADDLE_ENFORCE_GE
(
boost
::
get
<
int
>
(
ctx
.
GetAttr
(
kForwardPythonCallableId
)),
0
,
"Function id cannot be less than 0"
);
if
(
!
has_out
)
return
;
...
...
@@ -118,7 +115,7 @@ class PyFuncOpVarTypInference : public framework::VarTypeInference {
* the corresponding forward variable
*/
const
std
::
string
kGradVarSuffix
=
framework
::
kGradVarSuffix
;
auto
&
out_var_names
=
outs
.
a
t
(
"Out"
);
auto
&
out_var_names
=
ctx
.
Outpu
t
(
"Out"
);
for
(
auto
&
out_var_name
:
out_var_names
)
{
if
(
out_var_name
==
framework
::
kEmptyVarName
||
out_var_name
.
size
()
<
kGradVarSuffix
.
size
())
{
...
...
@@ -128,18 +125,17 @@ class PyFuncOpVarTypInference : public framework::VarTypeInference {
size_t
len
=
out_var_name
.
size
()
-
kGradVarSuffix
.
size
();
if
(
out_var_name
.
substr
(
len
)
==
kGradVarSuffix
)
{
auto
fwd_var_name
=
out_var_name
.
substr
(
0
,
len
);
auto
*
out_var_desc
=
block
->
FindVarRecursive
(
out_var_name
);
auto
*
fwd_var_desc
=
block
->
FindVarRecursive
(
fwd_var_name
);
PADDLE_ENFORCE_NOT_NULL
(
out_var_desc
,
"Backward variable %s not found"
,
out_var_name
);
PADDLE_ENFORCE_NOT_NULL
(
fwd_var_desc
,
"Forward variable %s not found"
,
fwd_var_name
);
PADDLE_ENFORCE
(
ctx
.
HasVar
(
out_var_name
),
"Backward variable %s not found"
,
out_var_name
);
PADDLE_ENFORCE
(
ctx
.
HasVar
(
fwd_var_name
),
"Backward variable %s not found"
,
fwd_var_name
);
VLOG
(
10
)
<<
"Infer var_desc of Output("
<<
out_var_name
<<
") as Input("
<<
fwd_var_name
<<
")"
;
out_var_desc
->
SetShape
(
fwd_var_desc
->
GetShape
());
out_var_desc
->
SetDataType
(
fwd_var_desc
->
GetDataType
());
out_var_desc
->
SetLoDLevel
(
fwd_var_desc
->
GetLoDLevel
());
out_var_desc
->
SetType
(
fwd_var_desc
->
GetType
());
ctx
.
SetShape
(
out_var_name
,
ctx
.
GetShape
(
fwd_var_name
));
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
fwd_var_name
));
ctx
.
SetLoDLevel
(
out_var_name
,
ctx
.
GetLoDLevel
(
fwd_var_name
));
ctx
.
SetType
(
out_var_name
,
ctx
.
GetType
(
fwd_var_name
));
}
}
}
...
...
@@ -309,5 +305,5 @@ class PyFuncOp : public framework::OperatorBase {
namespace
ops
=
paddle
::
operators
;
REGISTER_OPERATOR
(
py_func
,
ops
::
PyFuncOp
,
ops
::
PyFuncOpMaker
,
ops
::
PyFuncOpVarTypInference
,
ops
::
PyFuncOpShapeInference
,
ops
::
PyFuncOpVarTyp
e
Inference
,
ops
::
PyFuncOpShapeInference
,
ops
::
PyFuncOpGradDescMaker
);
paddle/fluid/operators/reader/create_custom_reader_op.cc
浏览文件 @
ca392c7e
...
...
@@ -85,10 +85,10 @@ class CreateCustomReaderOpMaker : public DecoratedReaderMakerBase {
AddComment
(
R"DOC(
CreateCustomReader Operator
A custom reader can be used for input data preprocessing.
A custom reader holds its own sub-block, which will be executed in CPU
in its 'ReadNext()' function. Users can configurate their own
preprocessing pipelines by inserting operators into custom reader's
A custom reader can be used for input data preprocessing.
A custom reader holds its own sub-block, which will be executed in CPU
in its 'ReadNext()' function. Users can configurate their own
preprocessing pipelines by inserting operators into custom reader's
sub-block.
)DOC"
);
}
...
...
@@ -123,23 +123,22 @@ class CustomReaderInferShape : public framework::InferShapeBase {
class
CustomReaderInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
framework
::
VarDesc
*
out_reader
=
block
->
FindVar
(
op_desc
.
Output
(
"Out"
)[
0
]);
PADDLE_ENFORCE_NOT_NULL
(
out_reader
);
out_reader
->
SetType
(
framework
::
proto
::
VarType
::
READER
);
void
operator
()(
const
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
out_var_name
=
ctx
.
Output
(
"Out"
)[
0
];
PADDLE_ENFORCE
(
ctx
.
HasVar
(
out_var_name
));
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
READER
);
auto
sink_var_names
=
boost
::
get
<
std
::
vector
<
std
::
string
>>
(
op_desc
.
GetAttr
(
"sink_var_names"
));
boost
::
get
<
std
::
vector
<
std
::
string
>>
(
ctx
.
GetAttr
(
"sink_var_names"
));
const
auto
*
sub_block
=
boost
::
get
<
framework
::
BlockDesc
*>
(
op_desc
.
GetAttr
(
"sub_block"
));
boost
::
get
<
framework
::
BlockDesc
*>
(
ctx
.
GetAttr
(
"sub_block"
));
std
::
vector
<
framework
::
proto
::
VarType
::
Type
>
res_data_types
;
for
(
const
std
::
string
&
var_name
:
sink_var_names
)
{
framework
::
VarDesc
*
var
=
sub_block
->
FindVar
(
var_name
);
PADDLE_ENFORCE_NOT_NULL
(
var
);
res_data_types
.
emplace_back
(
var
->
GetDataType
());
}
out_reader
->
SetDataTypes
(
res_data_types
);
ctx
.
SetDataTypes
(
out_var_name
,
res_data_types
);
}
};
...
...
paddle/fluid/operators/reader/read_op.cc
浏览文件 @
ca392c7e
...
...
@@ -51,19 +51,16 @@ class ReadInferShape : public framework::InferShapeBase {
class
ReadInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
bool
infer_out
=
boost
::
get
<
bool
>
(
op_desc
.
GetAttr
(
"infer_out"
));
void
operator
()(
const
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
bool
infer_out
=
boost
::
get
<
bool
>
(
ctx
.
GetAttr
(
"infer_out"
));
if
(
infer_out
)
{
std
::
string
reader_name
=
op_desc
.
Input
(
"Reader"
)[
0
];
std
::
vector
<
std
::
string
>
out_names
=
op_desc
.
Output
(
"Out"
);
framework
::
VarDesc
*
reader
=
block
->
FindVarRecursive
(
reader_name
);
auto
dtypes
=
reader
->
GetDataTypes
();
std
::
string
reader_name
=
ctx
.
Input
(
"Reader"
)[
0
];
std
::
vector
<
std
::
string
>
out_names
=
ctx
.
Output
(
"Out"
);
auto
dtypes
=
ctx
.
GetDataTypes
(
reader_name
);
PADDLE_ENFORCE_EQ
(
dtypes
.
size
(),
out_names
.
size
());
for
(
size_t
i
=
0
;
i
<
dtypes
.
size
();
++
i
)
{
framework
::
VarDesc
&
out
=
block
->
FindRecursiveOrCreateVar
(
out_names
[
i
]);
out
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
out
.
SetDataType
(
dtypes
[
i
]);
ctx
.
SetType
(
out_names
[
i
],
framework
::
proto
::
VarType
::
LOD_TENSOR
);
ctx
.
SetDataType
(
out_names
[
i
],
dtypes
[
i
]);
}
}
}
...
...
paddle/fluid/operators/reader/reader_op_registry.h
浏览文件 @
ca392c7e
...
...
@@ -59,8 +59,7 @@ class FileReaderInferShape : public framework::InferShapeBase {
class
FileReaderInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
;
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
;
};
// general infershape for decorated reader
...
...
@@ -72,8 +71,7 @@ class DecoratedReaderInferShape : public framework::InferShapeBase {
// general var type inference for decorated reader
class
DecoratedReaderInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
;
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
;
};
class
DecoratedReaderMakerBase
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
paddle/fluid/operators/save_op.cc
浏览文件 @
ca392c7e
...
...
@@ -159,12 +159,9 @@ This operator will serialize and write LoDTensor / SelectedRows variable to file
class
SaveOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
out_var_name
=
op_desc
.
Output
(
LOOKUP_TABLE_PATH
).
front
();
auto
&
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_name
);
auto
var_type
=
framework
::
proto
::
VarType
::
RAW
;
out_var
.
SetType
(
var_type
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
out_var_name
=
ctx
.
Output
(
LOOKUP_TABLE_PATH
).
front
();
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
RAW
);
}
};
...
...
paddle/fluid/operators/scale_op.cc
浏览文件 @
ca392c7e
...
...
@@ -69,17 +69,13 @@ $$Out = scale*(X + bias)$$
class
ScaleOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
&
in_var_name
=
op_desc
.
Input
(
"X"
).
front
();
auto
&
in_var
=
detail
::
Ref
(
block
->
FindVarRecursive
(
in_var_name
));
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
auto
*
out_var
=
block
->
FindVarRecursive
(
out_var_name
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
in_var_name
=
ctx
.
Input
(
"X"
).
front
();
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
if
(
in_var_name
!=
out_var_name
)
{
out_var
->
SetType
(
in_var
.
GetType
(
));
out_var
->
SetDataType
(
in_var
.
GetDataType
(
));
ctx
.
SetType
(
out_var_name
,
ctx
.
GetType
(
in_var_name
));
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
in_var_name
));
}
}
};
...
...
paddle/fluid/operators/split_selected_rows_op.cc
浏览文件 @
ca392c7e
...
...
@@ -60,10 +60,9 @@ class SplitSelectedRowsOp : public framework::OperatorWithKernel {
class
SplitSelectedRowsOpInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
out_var
:
op_desc
.
Output
(
"Out"
))
{
block
->
Var
(
out_var
)
->
SetType
(
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
out_var
:
ctx
.
Output
(
"Out"
))
{
ctx
.
SetType
(
out_var
,
framework
::
proto
::
VarType
::
SELECTED_ROWS
);
}
}
};
...
...
paddle/fluid/operators/sum_op.cc
浏览文件 @
ca392c7e
...
...
@@ -159,24 +159,20 @@ the LoD information with the first input.
class
SumOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
&
inputs
=
op_desc
.
Input
(
"X"
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
&
inputs
=
ctx
.
Input
(
"X"
);
auto
var_type
=
framework
::
proto
::
VarType
::
SELECTED_ROWS
;
for
(
auto
&
name
:
op_desc
.
Input
(
"X"
))
{
VLOG
(
10
)
<<
name
<<
" "
<<
block
->
FindRecursiveOrCreateVar
(
name
).
GetType
();
for
(
auto
&
name
:
ctx
.
Input
(
"X"
))
{
VLOG
(
10
)
<<
name
<<
" "
<<
ctx
.
GetType
(
name
);
}
bool
any_input_is_lod_tensor
=
std
::
any_of
(
inputs
.
begin
(),
inputs
.
end
(),
[
block
](
const
std
::
string
&
name
)
{
return
block
->
FindRecursiveOrCreateVar
(
name
).
GetType
()
==
framework
::
proto
::
VarType
::
LOD_TENSOR
;
inputs
.
begin
(),
inputs
.
end
(),
[
ctx
](
const
std
::
string
&
name
)
{
return
ctx
.
GetType
(
name
)
==
framework
::
proto
::
VarType
::
LOD_TENSOR
;
});
auto
is_tensor_array
=
[
block
](
const
std
::
string
&
name
)
{
return
block
->
FindRecursiveOrCreateVar
(
name
).
GetType
()
==
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
;
auto
is_tensor_array
=
[
ctx
](
const
std
::
string
&
name
)
{
return
ctx
.
GetType
(
name
)
==
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
;
};
bool
any_input_is_tensor_array
=
...
...
@@ -188,8 +184,7 @@ class SumOpVarTypeInference : public framework::VarTypeInference {
if
(
!
all_inputs_are_tensor_array
)
{
std
::
ostringstream
os
;
for
(
auto
&
each
:
inputs
)
{
os
<<
" "
<<
each
<<
" type is "
<<
block
->
FindRecursiveOrCreateVar
(
each
).
GetType
()
<<
"
\n
"
;
os
<<
" "
<<
each
<<
" type is "
<<
ctx
.
GetType
(
each
)
<<
"
\n
"
;
}
PADDLE_ENFORCE
(
all_inputs_are_tensor_array
,
"Not all inputs are tensor array:
\n
%s"
,
os
.
str
());
...
...
@@ -199,11 +194,9 @@ class SumOpVarTypeInference : public framework::VarTypeInference {
var_type
=
framework
::
proto
::
VarType
::
LOD_TENSOR
;
}
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
auto
&
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_name
);
out_var
.
SetType
(
var_type
);
auto
&
in_var
=
detail
::
Ref
(
block
->
FindVarRecursive
(
inputs
.
front
()));
out_var
.
SetDataType
(
in_var
.
GetDataType
());
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
ctx
.
SetType
(
out_var_name
,
var_type
);
ctx
.
SetDataType
(
out_var_name
,
ctx
.
GetDataType
(
inputs
.
front
()));
}
};
...
...
paddle/fluid/operators/tensor_array_to_tensor_op.cc
浏览文件 @
ca392c7e
...
...
@@ -177,10 +177,9 @@ class LoDTensorArray2TensorGradInferShape : public framework::InferShapeBase {
class
LoDTensorArray2TensorGradInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
for
(
auto
&
out_var
:
op_desc
.
Output
(
framework
::
GradVarName
(
"X"
)))
{
block
->
Var
(
out_var
)
->
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
for
(
auto
&
out_var
:
ctx
.
Output
(
framework
::
GradVarName
(
"X"
)))
{
ctx
.
SetType
(
out_var
,
framework
::
proto
::
VarType
::
LOD_TENSOR_ARRAY
);
}
}
};
...
...
paddle/fluid/operators/tensorrt/tensorrt_engine_op.cc
浏览文件 @
ca392c7e
...
...
@@ -46,8 +46,7 @@ class TensorRTEngineOpMaker : public framework::OpProtoAndCheckerMaker {
class
TensorRTEngineInferVarType
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{}
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{}
};
}
// namespace operators
...
...
paddle/fluid/operators/uniform_random_op.cc
浏览文件 @
ca392c7e
...
...
@@ -112,17 +112,15 @@ uniform distribution. The random result is in set [min, max].
class
UniformRandomOpVarTypeInference
:
public
framework
::
VarTypeInference
{
public:
void
operator
()(
const
framework
::
OpDesc
&
op_desc
,
framework
::
BlockDesc
*
block
)
const
override
{
auto
out_var_name
=
op_desc
.
Output
(
"Out"
).
front
();
void
operator
()(
framework
::
InferVarTypeContext
&
ctx
)
const
override
{
auto
out_var_name
=
ctx
.
Output
(
"Out"
).
front
();
auto
var_data_type
=
static_cast
<
framework
::
proto
::
VarType
::
Type
>
(
boost
::
get
<
int
>
(
op_desc
.
GetAttr
(
"dtype"
)));
boost
::
get
<
int
>
(
ctx
.
GetAttr
(
"dtype"
)));
auto
out_var
=
block
->
FindRecursiveOrCreateVar
(
out_var_name
);
if
(
out_var
.
GetType
()
!=
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
out_var
.
SetType
(
framework
::
proto
::
VarType
::
LOD_TENSOR
);
if
(
ctx
.
GetType
(
out_var_name
)
!=
framework
::
proto
::
VarType
::
SELECTED_ROWS
)
{
ctx
.
SetType
(
out_var_name
,
framework
::
proto
::
VarType
::
LOD_TENSOR
);
}
out_var
.
SetDataType
(
var_data_type
);
ctx
.
SetDataType
(
out_var_name
,
var_data_type
);
}
};
...
...
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