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9d2c77e6
编写于
12月 19, 2017
作者:
Y
Yang Yang
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差异文件
parallel_do skeleton pass compile
上级
61ec0b95
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
169 addition
and
20 deletion
+169
-20
paddle/operators/CMakeLists.txt
paddle/operators/CMakeLists.txt
+2
-0
paddle/operators/parallel_do_op.cc
paddle/operators/parallel_do_op.cc
+147
-0
paddle/operators/recurrent_op.cc
paddle/operators/recurrent_op.cc
+10
-10
paddle/operators/while_op.cc
paddle/operators/while_op.cc
+10
-10
未找到文件。
paddle/operators/CMakeLists.txt
浏览文件 @
9d2c77e6
...
...
@@ -185,6 +185,7 @@ set(DEPS_OPS
cond_op
cross_entropy_op
recurrent_op
parallel_do_op
softmax_with_cross_entropy_op
softmax_op
sequence_softmax_op
...
...
@@ -256,6 +257,7 @@ op_library(lstm_op DEPS sequence2batch lstm_compute)
op_library
(
conv_transpose_op DEPS vol2col
)
op_library
(
gru_op DEPS sequence2batch gru_compute
)
op_library
(
recurrent_op SRCS recurrent_op.cc DEPS executor
)
op_library
(
parallel_do_op SRCS parallel_do_op.cc DEPS executor
)
# FIXME(typhoonzero): save/load depends lodtensor serialization functions
op_library
(
save_op DEPS lod_tensor
)
...
...
paddle/operators/parallel_do_op.cc
0 → 100644
浏览文件 @
9d2c77e6
/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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 <vector>
#include "paddle/framework/executor.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
namespace
paddle
{
namespace
operators
{
constexpr
char
kInputs
[]
=
"inputs"
;
constexpr
char
kParameters
[]
=
"parameters"
;
constexpr
char
kPlaces
[]
=
"places"
;
constexpr
char
kParallelBlock
[]
=
"parallel_block"
;
constexpr
char
kOutputs
[]
=
"outputs"
;
constexpr
char
kParallelScopes
[]
=
"parallel_scopes"
;
// #define GRAD_SUFFIX "@GRAD"
// constexpr char kInputGrads[] = "inputs" GRAD_SUFFIX;
// constexpr char kOutputGrads[] = "outputs" GRAD_SUFFIX;
// constexpr char kParamGrads[] = "parameters" GRAD_SUFFIX;
using
ParallelScopeVar
=
std
::
vector
<
framework
::
Scope
*>
;
using
OperatorBase
=
framework
::
OperatorBase
;
class
ParallelDoOp
:
public
OperatorBase
{
public:
ParallelDoOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
// create scope
// copy parameters
}
};
class
ParallelDoGradOp
:
public
OperatorBase
{
public:
ParallelDoGradOp
(
const
std
::
string
&
type
,
const
framework
::
VariableNameMap
&
inputs
,
const
framework
::
VariableNameMap
&
outputs
,
const
framework
::
AttributeMap
&
attrs
)
:
OperatorBase
(
type
,
inputs
,
outputs
,
attrs
)
{}
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{}
};
class
ParallelDoOpProtoMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
public:
ParallelDoOpProtoMaker
(
framework
::
OpProto
*
proto
,
framework
::
OpAttrChecker
*
op_checker
)
:
OpProtoAndCheckerMaker
(
proto
,
op_checker
)
{
AddInput
(
kInputs
,
""
).
AsDuplicable
();
AddInput
(
kParameters
,
""
).
AsDuplicable
();
AddInput
(
kPlaces
,
""
);
AddOutput
(
kOutputs
,
""
).
AsDuplicable
();
AddOutput
(
kParallelScopes
,
""
);
AddAttr
<
framework
::
BlockDescBind
*>
(
kParallelBlock
,
""
);
AddComment
(
R"DOC(
ParallelDo Operator.
)DOC"
);
}
};
class
ParallelDoGradOpDescMaker
:
public
framework
::
SingleGradOpDescMaker
{
public:
using
framework
::
SingleGradOpDescMaker
::
SingleGradOpDescMaker
;
protected:
virtual
std
::
unique_ptr
<
framework
::
OpDescBind
>
Apply
()
const
{
PADDLE_THROW
(
"Not Implemented"
);
auto
*
grad
=
new
framework
::
OpDescBind
();
grad
->
SetType
(
"recurrent_grad"
);
for
(
auto
&
input_param
:
this
->
InputNames
())
{
grad
->
SetInput
(
input_param
,
this
->
Input
(
input_param
));
grad
->
SetOutput
(
framework
::
GradVarName
(
input_param
),
this
->
InputGrad
(
input_param
));
}
for
(
auto
&
output_param
:
this
->
OutputNames
())
{
if
(
output_param
==
kParallelScopes
)
{
grad
->
SetInput
(
output_param
,
this
->
Output
(
output_param
));
grad
->
SetInput
(
framework
::
GradVarName
(
output_param
),
this
->
Output
(
output_param
));
}
else
{
grad
->
SetInput
(
output_param
,
this
->
Output
(
output_param
));
grad
->
SetInput
(
framework
::
GradVarName
(
output_param
),
this
->
OutputGrad
(
output_param
));
}
}
grad
->
SetAttrMap
(
this
->
Attrs
());
grad
->
SetBlockAttr
(
kParallelBlock
,
*
grad_block_
[
0
]);
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad
);
}
};
class
ParallelDoGradOpShapeInference
:
public
framework
::
InferShapeBase
{
public:
void
operator
()(
framework
::
InferShapeContext
*
ctx
)
const
override
{
PADDLE_THROW
(
"Not Implemented"
);
// std::vector<std::string> input{kInputs};
// std::vector<std::string> output{kOutputs};
// for (auto &s : input) {
// PADDLE_ENFORCE(ctx->HasInputs(s));
// PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(s)),
// "Cannot find the gradient variable %s",
// framework::GradVarName(s));
// }
// for (auto &s : output) {
// PADDLE_ENFORCE(ctx->HasInputs(s));
// }
// for (auto &s : input) {
// ctx->SetOutputsDim(framework::GradVarName(s), ctx->GetInputsDim(s));
// }
// if (ctx->HasInputs(kParameters)) {
// PADDLE_ENFORCE(ctx->HasOutputs(framework::GradVarName(kParameters)));
// ctx->SetOutputsDim(framework::GradVarName(kParameters),
// ctx->GetInputsDim(kParameters));
// }
}
};
}
// namespace operators
}
// namespace paddle
REGISTER_OPERATOR
(
parallel_do
,
paddle
::
operators
::
ParallelDoOp
,
paddle
::
operators
::
ParallelDoOpProtoMaker
,
paddle
::
operators
::
ParallelDoGradOpDescMaker
);
REGISTER_OPERATOR
(
parallel_do_grad
,
paddle
::
operators
::
ParallelDoGradOp
,
paddle
::
operators
::
ParallelDoGradOpShapeInference
);
paddle/operators/recurrent_op.cc
浏览文件 @
9d2c77e6
...
...
@@ -22,10 +22,10 @@ constexpr char kInputs[] = "inputs";
constexpr
char
kInitialStates
[]
=
"initial_states"
;
constexpr
char
kParameters
[]
=
"parameters"
;
constexpr
char
kOutputs
[]
=
"outputs"
;
constexpr
char
k
Step
Scopes
[]
=
"step_scopes"
;
constexpr
char
k
Parallel
Scopes
[]
=
"step_scopes"
;
constexpr
char
kExStates
[]
=
"ex_states"
;
constexpr
char
kStates
[]
=
"states"
;
constexpr
char
k
Step
Block
[]
=
"step_block"
;
constexpr
char
k
Parallel
Block
[]
=
"step_block"
;
constexpr
char
kReverse
[]
=
"reverse"
;
constexpr
char
kIsTrain
[]
=
"is_train"
;
#define GRAD_SUFFIX "@GRAD"
...
...
@@ -234,7 +234,7 @@ class RecurrentOp : public RecurrentBase {
auto
reverse
=
Attr
<
bool
>
(
kReverse
);
framework
::
Executor
executor
(
dev_ctx
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
);
auto
*
program
=
block
->
Program
();
for
(
size_t
i
=
0
;
i
<
seq_len
;
++
i
)
{
...
...
@@ -295,7 +295,7 @@ class RecurrentOp : public RecurrentBase {
private:
StepScopes
CreateStepScopes
(
const
framework
::
Scope
&
scope
,
size_t
seq_len
)
const
{
auto
*
var
=
scope
.
FindVar
(
Output
(
k
Step
Scopes
));
auto
*
var
=
scope
.
FindVar
(
Output
(
k
Parallel
Scopes
));
PADDLE_ENFORCE
(
var
!=
nullptr
);
return
StepScopes
(
scope
,
var
->
GetMutable
<
StepScopeVar
>
(),
Attr
<
bool
>
(
kIsTrain
),
seq_len
);
...
...
@@ -317,7 +317,7 @@ class RecurrentGradOp : public RecurrentBase {
auto
reverse
=
Attr
<
bool
>
(
kReverse
);
framework
::
Executor
executor
(
dev_ctx
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
);
auto
*
program
=
block
->
Program
();
for
(
size_t
step_id
=
0
;
step_id
<
seq_len
;
++
step_id
)
{
...
...
@@ -465,7 +465,7 @@ class RecurrentGradOp : public RecurrentBase {
private:
StepScopes
CreateStepScopes
(
const
framework
::
Scope
&
scope
,
size_t
seq_len
)
const
{
auto
*
var
=
scope
.
FindVar
(
Input
(
k
Step
Scopes
));
auto
*
var
=
scope
.
FindVar
(
Input
(
k
Parallel
Scopes
));
PADDLE_ENFORCE
(
var
!=
nullptr
);
return
StepScopes
(
scope
,
var
->
GetMutable
<
StepScopeVar
>
(),
Attr
<
bool
>
(
kIsTrain
),
seq_len
,
true
/*is_backward*/
);
...
...
@@ -510,7 +510,7 @@ class RecurrentOpProtoMaker : public framework::OpProtoAndCheckerMaker {
AddOutput
(
kOutputs
,
"The output sequence of RNN. The sequence length must be same."
)
.
AsDuplicable
();
AddOutput
(
k
Step
Scopes
,
AddOutput
(
k
Parallel
Scopes
,
"StepScopes contain all local variables in each time step."
);
AddAttr
<
std
::
vector
<
std
::
string
>>
(
kExStates
,
string
::
Sprintf
(
...
...
@@ -523,7 +523,7 @@ The ex-state means the state value in the ex-timestep or the previous time step
string
::
Sprintf
(
"The state variable names. [%s, %s, %s] must be the same order"
,
kExStates
,
kStates
,
kInitStateGrads
));
AddAttr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
,
AddAttr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
,
"The step block inside RNN"
);
AddAttr
<
bool
>
(
kReverse
,
R"DOC(Calculate RNN reversely or not.
By default reverse=False
...
...
@@ -576,7 +576,7 @@ class RecurrentGradOpDescMaker : public framework::SingleGradOpDescMaker {
}
for
(
auto
&
output_param
:
this
->
OutputNames
())
{
if
(
output_param
==
k
Step
Scopes
)
{
if
(
output_param
==
k
Parallel
Scopes
)
{
grad
->
SetInput
(
output_param
,
this
->
Output
(
output_param
));
grad
->
SetInput
(
framework
::
GradVarName
(
output_param
),
this
->
Output
(
output_param
));
...
...
@@ -587,7 +587,7 @@ class RecurrentGradOpDescMaker : public framework::SingleGradOpDescMaker {
}
}
grad
->
SetAttrMap
(
this
->
Attrs
());
grad
->
SetBlockAttr
(
k
Step
Block
,
*
grad_block_
[
0
]);
grad
->
SetBlockAttr
(
k
Parallel
Block
,
*
grad_block_
[
0
]);
return
std
::
unique_ptr
<
framework
::
OpDescBind
>
(
grad
);
}
...
...
paddle/operators/while_op.cc
浏览文件 @
9d2c77e6
...
...
@@ -25,9 +25,9 @@ namespace operators {
using
StepScopeVar
=
std
::
vector
<
framework
::
Scope
*>
;
using
LoDTensor
=
framework
::
LoDTensor
;
constexpr
char
k
Step
Block
[]
=
"step_block"
;
constexpr
char
k
Parallel
Block
[]
=
"step_block"
;
constexpr
char
kCondition
[]
=
"Condition"
;
constexpr
char
k
Step
Scopes
[]
=
"StepScopes"
;
constexpr
char
k
Parallel
Scopes
[]
=
"StepScopes"
;
constexpr
char
kParameters
[]
=
"X"
;
constexpr
char
kParamGrads
[]
=
"X@GRAD"
;
constexpr
char
kOutputs
[]
=
"Out"
;
...
...
@@ -46,11 +46,11 @@ class WhileOp : public framework::OperatorBase {
PADDLE_ENFORCE_EQ
(
cond
.
dims
(),
paddle
::
framework
::
make_ddim
({
1
}));
framework
::
Executor
executor
(
dev_ctx
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
);
auto
*
program
=
block
->
Program
();
auto
step_scopes
=
scope
.
FindVar
(
Output
(
k
Step
Scopes
))
->
GetMutable
<
StepScopeVar
>
();
scope
.
FindVar
(
Output
(
k
Parallel
Scopes
))
->
GetMutable
<
StepScopeVar
>
();
while
(
cond
.
data
<
bool
>
()[
0
])
{
auto
&
current_scope
=
scope
.
NewScope
();
...
...
@@ -78,11 +78,11 @@ class WhileOpMaker : public framework::OpProtoAndCheckerMaker {
"A set of variables, which will be assigned with values "
"generated by the operators inside the block of While Op."
)
.
AsDuplicable
();
AddOutput
(
k
Step
Scopes
,
AddOutput
(
k
Parallel
Scopes
,
"(StepScopeVar) A vector of local scope, which size equals the "
"step number of While Op. The i'th scope storages temporary "
"variables generated in the i'th step."
);
AddAttr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
,
AddAttr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
,
"The step block inside WhileOp"
);
AddComment
(
R"DOC(
)DOC"
);
...
...
@@ -99,11 +99,11 @@ class WhileGradOp : public framework::OperatorBase {
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
framework
::
Executor
executor
(
dev_ctx
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Step
Block
);
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
k
Parallel
Block
);
auto
*
program
=
block
->
Program
();
auto
*
step_scopes
=
scope
.
FindVar
(
Input
(
k
Step
Scopes
))
->
GetMutable
<
StepScopeVar
>
();
scope
.
FindVar
(
Input
(
k
Parallel
Scopes
))
->
GetMutable
<
StepScopeVar
>
();
auto
outside_og_names
=
Inputs
(
framework
::
GradVarName
(
kOutputs
));
auto
inside_og_names
=
...
...
@@ -272,9 +272,9 @@ class WhileGradOpDescMaker : public framework::SingleGradOpDescMaker {
std
::
copy
(
extra_inputs
.
begin
(),
extra_inputs
.
end
(),
extra_inputs_list
.
begin
());
grad
->
SetInput
(
framework
::
GradVarName
(
kOutputs
),
extra_inputs_list
);
grad
->
SetInput
(
k
StepScopes
,
Output
(
kStep
Scopes
));
grad
->
SetInput
(
k
ParallelScopes
,
Output
(
kParallel
Scopes
));
grad
->
SetAttrMap
(
this
->
Attrs
());
grad
->
SetBlockAttr
(
k
Step
Block
,
*
grad_block_
[
0
]);
grad
->
SetBlockAttr
(
k
Parallel
Block
,
*
grad_block_
[
0
]);
// record the original output gradient names, since the gradient name of
// while operator could be renamed.
grad
->
SetAttr
(
"original_output_grad"
,
extra_inputs_list
);
...
...
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