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cb284283
编写于
9月 14, 2017
作者:
D
dangqingqing
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
Replace LoDTensor in elementwise_mul_op, pad_op and recurrent_op_utils.
上级
30a58b51
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
51 addition
and
39 deletion
+51
-39
paddle/framework/operator.cc
paddle/framework/operator.cc
+12
-19
paddle/framework/operator.h
paddle/framework/operator.h
+19
-6
paddle/operators/elementwise_mul_op.cc
paddle/operators/elementwise_mul_op.cc
+3
-3
paddle/operators/pad_op.cc
paddle/operators/pad_op.cc
+5
-4
paddle/operators/rnn/recurrent_op_utils.cc
paddle/operators/rnn/recurrent_op_utils.cc
+12
-7
未找到文件。
paddle/framework/operator.cc
浏览文件 @
cb284283
...
...
@@ -189,13 +189,7 @@ void OperatorBase::GenerateTemporaryNames() {
template
<
>
const
Tensor
*
InferShapeContext
::
Input
<
Tensor
>
(
const
std
::
string
&
name
)
const
{
auto
*
var
=
InputVar
(
name
);
if
(
var
==
nullptr
)
return
nullptr
;
if
(
var
->
IsType
<
LoDTensor
>
())
{
return
&
var
->
Get
<
LoDTensor
>
();
}
PADDLE_ENFORCE
(
var
->
IsType
<
Tensor
>
(),
"The Input(%s) must be LoDTensor or Tensor."
);
return
&
var
->
Get
<
Tensor
>
();
return
var
==
nullptr
?
nullptr
:
GetTensorFromVar
(
var
);
}
template
<
>
...
...
@@ -204,9 +198,11 @@ const std::vector<const Tensor*> InferShapeContext::MultiInput<Tensor>(
auto
names
=
op
().
Inputs
(
name
);
std
::
vector
<
const
Tensor
*>
res
;
res
.
reserve
(
names
.
size
());
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
return
Input
<
Tensor
>
(
sub_name
);
});
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
auto
var
=
scope_
.
FindVar
(
sub_name
);
return
var
==
nullptr
?
nullptr
:
GetTensorFromVar
(
var
);
});
return
res
;
}
...
...
@@ -214,12 +210,7 @@ template <>
Tensor
*
ExecutionContext
::
Output
<
Tensor
>
(
const
std
::
string
&
name
)
const
{
auto
*
var
=
OutputVar
(
name
);
if
(
var
==
nullptr
)
return
nullptr
;
if
(
var
->
IsType
<
LoDTensor
>
())
{
return
const_cast
<
LoDTensor
*>
(
&
var
->
Get
<
LoDTensor
>
());
}
PADDLE_ENFORCE
(
var
->
IsType
<
Tensor
>
(),
"The Input(%s) must be LoDTensor or Tensor."
);
return
const_cast
<
Tensor
*>
(
&
var
->
Get
<
Tensor
>
());
return
GetTensorFromVar
(
var
);
}
template
<
>
...
...
@@ -228,9 +219,11 @@ std::vector<Tensor*> ExecutionContext::MultiOutput<Tensor>(
auto
names
=
op
().
Outputs
(
name
);
std
::
vector
<
Tensor
*>
res
;
res
.
reserve
(
names
.
size
());
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
return
Output
<
Tensor
>
(
sub_name
);
});
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
auto
var
=
scope
().
FindVar
(
sub_name
);
return
var
==
nullptr
?
nullptr
:
GetTensorFromVar
(
var
);
});
return
res
;
}
...
...
paddle/framework/operator.h
浏览文件 @
cb284283
...
...
@@ -306,9 +306,11 @@ class InferShapeContext {
auto
names
=
op_
.
Inputs
(
name
);
std
::
vector
<
const
T
*>
res
;
res
.
reserve
(
names
.
size
());
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
return
Input
<
T
>
(
sub_name
);
});
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
auto
var
=
scope_
.
FindVar
(
sub_name
);
return
var
==
nullptr
?
nullptr
:
&
var
->
Get
<
T
>
();
});
return
res
;
}
...
...
@@ -317,12 +319,23 @@ class InferShapeContext {
auto
names
=
op_
.
Outputs
(
name
);
std
::
vector
<
T
*>
res
;
res
.
reserve
(
names
.
size
());
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
return
Output
<
T
>
(
sub_name
);
});
std
::
transform
(
names
.
begin
(),
names
.
end
(),
std
::
back_inserter
(
res
),
[
&
](
const
std
::
string
&
sub_name
)
{
auto
var
=
scope_
.
FindVar
(
sub_name
);
return
var
==
nullptr
?
nullptr
:
var
->
GetMutable
<
T
>
();
});
return
res
;
}
Tensor
*
GetTensorFromVar
(
const
Variable
*
var
)
const
{
if
(
var
->
IsType
<
LoDTensor
>
())
{
return
const_cast
<
LoDTensor
*>
(
&
var
->
Get
<
LoDTensor
>
());
}
PADDLE_ENFORCE
(
var
->
IsType
<
Tensor
>
(),
"The Input(%s) must be LoDTensor or Tensor."
);
return
const_cast
<
Tensor
*>
(
&
var
->
Get
<
Tensor
>
());
}
private:
const
OperatorBase
&
op_
;
const
Scope
&
scope_
;
...
...
paddle/operators/elementwise_mul_op.cc
浏览文件 @
cb284283
...
...
@@ -31,7 +31,7 @@ class ElementWiseMulOp : public framework::OperatorWithKernel {
auto
y_dim
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
PADDLE_ENFORCE_GE
(
x_dim
.
size
(),
y_dim
.
size
(),
"Rank of first input must >= rank of second input."
)
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
x_dim
);
ctx
.
Output
<
framework
::
Tensor
>
(
"Out"
)
->
Resize
(
x_dim
);
}
};
...
...
@@ -80,8 +80,8 @@ class ElementWiseMulOpGrad : public framework::OperatorWithKernel {
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
y_dims
=
ctx
.
Input
<
Tensor
>
(
"Y"
)
->
dims
();
auto
out_dims
=
ctx
.
Input
<
Tensor
>
(
framework
::
GradVarName
(
"Out"
))
->
dims
();
auto
*
x_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y_grad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
auto
*
x_grad
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"X"
));
auto
*
y_grad
=
ctx
.
Output
<
framework
::
Tensor
>
(
framework
::
GradVarName
(
"Y"
));
PADDLE_ENFORCE_GE
(
x_dims
.
size
(),
y_dims
.
size
(),
"Rank of first input must >= rank of second input."
)
...
...
paddle/operators/pad_op.cc
浏览文件 @
cb284283
...
...
@@ -34,7 +34,8 @@ class PadOp : public framework::OperatorWithKernel {
for
(
int
i
=
0
;
i
<
x_dim
.
size
();
++
i
)
{
out_dims
[
i
]
=
x_dim
[
i
]
+
paddings
[
i
*
2
]
+
paddings
[
i
*
2
+
1
];
}
ctx
.
Output
<
Tensor
>
(
"Out"
)
->
Resize
(
framework
::
make_ddim
(
out_dims
));
ctx
.
Output
<
framework
::
LoDTensor
>
(
"Out"
)
->
Resize
(
framework
::
make_ddim
(
out_dims
));
}
};
...
...
@@ -95,9 +96,9 @@ class PadOpGrad : public framework::OperatorWithKernel {
PADDLE_ENFORCE_NOT_NULL
(
ctx
.
InputVar
(
framework
::
GradVarName
(
"Out"
)),
"Input(Out@GRAD) should not be null"
);
auto
x_dims
=
ctx
.
Input
<
Tensor
>
(
"X"
)
->
dims
();
auto
*
x_g
rad
=
ctx
.
Output
<
Tensor
>
(
framework
::
GradVarName
(
"X"
));
if
(
x_g
rad
!=
nullptr
)
{
x_g
rad
->
Resize
(
x_dims
);
auto
*
x_g
=
ctx
.
Output
<
framework
::
LoD
Tensor
>
(
framework
::
GradVarName
(
"X"
));
if
(
x_g
!=
nullptr
)
{
x_g
->
Resize
(
x_dims
);
}
}
};
...
...
paddle/operators/rnn/recurrent_op_utils.cc
浏览文件 @
cb284283
...
...
@@ -21,6 +21,7 @@ namespace rnn {
namespace
f
=
paddle
::
framework
;
using
Tensor
=
framework
::
Tensor
;
using
LoDTensor
=
framework
::
LoDTensor
;
void
SegmentInputs
(
const
std
::
vector
<
Scope
*>&
step_scopes
,
const
std
::
vector
<
Link
>&
inlinks
,
const
size_t
seq_len
,
...
...
@@ -31,7 +32,7 @@ void SegmentInputs(const std::vector<Scope*>& step_scopes,
PADDLE_ENFORCE
(
input_var
!=
nullptr
,
"input link [%s] is not in scope."
,
inlinks
[
i
].
external
);
Tensor
*
input
=
input_var
->
GetMutable
<
Tensor
>
();
LoDTensor
*
input
=
input_var
->
GetMutable
<
LoD
Tensor
>
();
f
::
DDim
dims
=
input
->
dims
();
PADDLE_ENFORCE
(
static_cast
<
size_t
>
(
dims
[
0
])
==
seq_len
,
"all the inlinks must have same length"
);
...
...
@@ -40,6 +41,8 @@ void SegmentInputs(const std::vector<Scope*>& step_scopes,
Tensor
*
step_input
=
step_scopes
[
j
]
->
NewVar
(
inlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
();
if
(
!
infer_shape_mode
)
{
// The input of operators of each step is Tensor here.
// Maybe need to modify Slice function.
*
step_input
=
input
->
Slice
<
float
>
(
j
,
j
+
1
);
}
step_input
->
Resize
(
step_dims
);
...
...
@@ -54,21 +57,23 @@ void ConcatOutputs(const std::vector<Scope*>& step_scopes,
auto
output_var
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
external
);
PADDLE_ENFORCE
(
output_var
!=
nullptr
,
"output link [%s] is not in scope."
,
outlinks
[
i
].
external
);
Tensor
*
output
=
output_var
->
GetMutable
<
Tensor
>
();
LoDTensor
*
output
=
output_var
->
GetMutable
<
LoD
Tensor
>
();
if
(
infer_shape_mode
)
{
auto
step_scope_var
=
step_scopes
[
0
]
->
FindVar
(
outlinks
[
i
].
internal
);
PADDLE_ENFORCE
(
step_scope_var
!=
nullptr
,
"%s not in scope"
,
outlinks
[
i
].
internal
);
f
::
DDim
step_dims
=
step_scope_var
->
template
GetMutable
<
Tensor
>()
->
dims
();
f
::
DDim
step_dims
=
step_scope_var
->
template
GetMutable
<
LoDTensor
>()
->
dims
();
std
::
vector
<
int64_t
>
dims_vec
=
vectorize
(
step_dims
);
dims_vec
.
insert
(
dims_vec
.
begin
(),
seq_len
);
output
->
Resize
(
f
::
make_ddim
(
dims_vec
));
}
else
{
output
->
mutable_data
<
float
>
(
platform
::
CPUPlace
());
for
(
size_t
j
=
0
;
j
<
seq_len
;
j
++
)
{
Tensor
*
step_output
=
step_scopes
[
j
]
->
FindVar
(
outlinks
[
i
].
internal
)
->
GetMutable
<
Tensor
>
();
LoDTensor
*
step_output
=
step_scopes
[
j
]
->
FindVar
(
outlinks
[
i
].
internal
)
->
GetMutable
<
LoDTensor
>
();
// TODO(luotao02) data type and platform::DeviceContext() should set
// correctly
(
output
->
Slice
<
float
>
(
j
,
j
+
1
))
...
...
@@ -94,8 +99,8 @@ void LinkMemories(const std::vector<Scope*>& scopes,
auto
scope
=
scopes
[
step_id
];
auto
linked_scope
=
scopes
[
step_id
+
offset
];
for
(
auto
&
attr
:
memories
)
{
auto
mem
=
scope
->
FindVar
(
attr
.
pre_var
)
->
GetMutable
<
Tensor
>
();
auto
linked_mem
=
linked_scope
->
FindVar
(
attr
.
var
)
->
GetMutable
<
Tensor
>
();
auto
mem
=
scope
->
FindVar
(
attr
.
pre_var
)
->
GetMutable
<
LoD
Tensor
>
();
auto
linked_mem
=
linked_scope
->
FindVar
(
attr
.
var
)
->
GetMutable
<
LoD
Tensor
>
();
if
(
infer_shape_mode
)
{
mem
->
Resize
(
linked_mem
->
dims
());
}
else
{
...
...
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