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体验新版 GitCode,发现更多精彩内容 >>
提交
f899150e
编写于
12月 21, 2017
作者:
Y
Yang Yang
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
pass forward runtime
上级
2f56d4b3
变更
8
隐藏空白更改
内联
并排
Showing
8 changed file
with
177 addition
and
48 deletion
+177
-48
paddle/framework/backward.cc
paddle/framework/backward.cc
+2
-1
paddle/framework/lod_tensor.cc
paddle/framework/lod_tensor.cc
+25
-0
paddle/framework/lod_tensor.h
paddle/framework/lod_tensor.h
+3
-0
paddle/framework/operator.cc
paddle/framework/operator.cc
+16
-4
paddle/framework/tensor.h
paddle/framework/tensor.h
+11
-0
paddle/operators/parallel_do_op.cc
paddle/operators/parallel_do_op.cc
+93
-39
python/paddle/v2/fluid/layers/control_flow.py
python/paddle/v2/fluid/layers/control_flow.py
+12
-1
python/paddle/v2/fluid/tests/test_parallel_op.py
python/paddle/v2/fluid/tests/test_parallel_op.py
+15
-3
未找到文件。
paddle/framework/backward.cc
浏览文件 @
f899150e
...
...
@@ -429,7 +429,8 @@ std::vector<std::unique_ptr<OpDescBind>> MakeBlockBackward(
VLOG
(
5
)
<<
"Making backward "
<<
(
*
it
)
->
Type
()
<<
" op"
;
std
::
vector
<
std
::
unique_ptr
<
OpDescBind
>>
op_grads
;
if
((
*
it
)
->
Type
()
==
"recurrent"
||
(
*
it
)
->
Type
()
==
"while"
)
{
if
((
*
it
)
->
Type
()
==
"recurrent"
||
(
*
it
)
->
Type
()
==
"while"
||
(
*
it
)
->
Type
()
==
"parallel_do"
)
{
int
step_block_idx
=
(
*
it
)
->
GetBlockAttr
(
"sub_block"
);
BlockDescBind
*
backward_block
=
CreateStepBlock
(
program_desc
,
no_grad_vars
,
grad_to_var
,
step_block_idx
);
...
...
paddle/framework/lod_tensor.cc
浏览文件 @
f899150e
...
...
@@ -314,5 +314,30 @@ void DeserializeFromStream(std::istream &is, LoDTensor *tensor) {
}
}
void
LoDTensor
::
MergeLoDTensor
(
const
std
::
vector
<
const
LoDTensor
*>
&
lod_tensors
,
platform
::
Place
place
)
{
PADDLE_ENFORCE
(
platform
::
is_cpu_place
(
place
));
PADDLE_ENFORCE
(
!
lod_tensors
.
empty
());
framework
::
DDim
new_dim
=
lod_tensors
[
0
]
->
dims
();
std
::
type_index
new_type
=
lod_tensors
[
0
]
->
type
();
for
(
auto
*
lod
:
lod_tensors
)
{
PADDLE_ENFORCE
(
new_dim
==
lod
->
dims
());
PADDLE_ENFORCE
(
new_type
==
lod
->
type
());
PADDLE_ENFORCE
(
platform
::
is_cpu_place
(
lod
->
place
()));
}
new_dim
[
0
]
*=
lod_tensors
.
size
();
Resize
(
new_dim
);
auto
*
dst_ptr
=
reinterpret_cast
<
uint8_t
*>
(
mutable_data
(
place
,
new_type
));
for
(
auto
*
src
:
lod_tensors
)
{
auto
size
=
src
->
numel
()
*
SizeOfType
(
src
->
type
());
memory
::
Copy
(
boost
::
get
<
platform
::
CPUPlace
>
(
place
),
dst_ptr
,
boost
::
get
<
platform
::
CPUPlace
>
(
src
->
place
()),
src
->
data
<
void
>
(),
size
);
dst_ptr
+=
size
;
}
}
}
// namespace framework
}
// namespace paddle
paddle/framework/lod_tensor.h
浏览文件 @
f899150e
...
...
@@ -144,6 +144,9 @@ class LoDTensor : public Tensor {
*/
void
ShrinkInLevel
(
size_t
level
,
size_t
elem_begin
,
size_t
elem_end
);
void
MergeLoDTensor
(
const
std
::
vector
<
const
LoDTensor
*>&
lod_tensors
,
platform
::
Place
place
);
private:
LoD
lod_
;
};
...
...
paddle/framework/operator.cc
浏览文件 @
f899150e
...
...
@@ -179,10 +179,13 @@ static const Tensor* GetTensorFromVar(const Variable* var) {
const
Tensor
*
t
=
nullptr
;
if
(
var
->
IsType
<
LoDTensor
>
())
{
t
=
&
(
var
->
Get
<
LoDTensor
>
());
}
else
if
(
var
->
IsType
<
Tensor
>
())
{
t
=
&
(
var
->
Get
<
Tensor
>
());
}
else
if
(
var
->
IsType
<
SelectedRows
>
())
{
t
=
&
(
var
->
Get
<
SelectedRows
>
().
value
());
}
else
{
PADDLE_THROW
(
"Variable type must be LoDTensor/SelectedRows."
);
PADDLE_THROW
(
"Variable type_id %s, expect LoDTensor/SelectedRows."
,
var
->
Type
().
name
());
}
return
t
;
}
...
...
@@ -191,10 +194,13 @@ static Tensor* GetMutableTensorFromVar(Variable* var) {
Tensor
*
t
=
nullptr
;
if
(
var
->
IsType
<
LoDTensor
>
())
{
t
=
var
->
GetMutable
<
LoDTensor
>
();
}
else
if
(
var
->
IsType
<
Tensor
>
())
{
t
=
var
->
GetMutable
<
Tensor
>
();
}
else
if
(
var
->
IsType
<
SelectedRows
>
())
{
t
=
var
->
GetMutable
<
SelectedRows
>
()
->
mutable_value
();
}
else
{
PADDLE_THROW
(
"Variable type must be LoDTensor/SelectedRows."
);
PADDLE_THROW
(
"Variable type_id %s, expect LoDTensor/SelectedRows."
,
var
->
Type
().
name
());
}
return
t
;
}
...
...
@@ -359,10 +365,13 @@ class RuntimeInferShapeContext : public InferShapeContext {
Variable
*
var
=
scope_
.
FindVar
(
name
);
if
(
var
->
IsType
<
LoDTensor
>
())
{
return
var
->
Get
<
LoDTensor
>
().
dims
();
}
else
if
(
var
->
IsType
<
Tensor
>
())
{
return
var
->
Get
<
Tensor
>
().
dims
();
}
else
if
(
var
->
IsType
<
SelectedRows
>
())
{
return
var
->
Get
<
SelectedRows
>
().
GetCompleteDims
();
}
else
{
PADDLE_THROW
(
"Variable type must be LoDTensor/SelectedRows."
);
PADDLE_THROW
(
"Variable %s type_id %s, expect LoDTensor/SelectedRows."
,
name
,
var
->
Type
().
name
());
}
}
...
...
@@ -370,10 +379,13 @@ class RuntimeInferShapeContext : public InferShapeContext {
Variable
*
var
=
scope_
.
FindVar
(
name
);
if
(
var
->
IsType
<
LoDTensor
>
())
{
var
->
GetMutable
<
LoDTensor
>
()
->
Resize
(
dim
);
}
else
if
(
var
->
IsType
<
Tensor
>
())
{
var
->
GetMutable
<
Tensor
>
()
->
Resize
(
dim
);
}
else
if
(
var
->
IsType
<
SelectedRows
>
())
{
var
->
GetMutable
<
SelectedRows
>
()
->
set_height
(
dim
[
0
]);
}
else
{
PADDLE_THROW
(
"Variable type must be LoDTensor/SelectedRows."
);
PADDLE_THROW
(
"Variable %s type_id %s, expect LoDTensor/SelectedRows."
,
name
,
var
->
Type
().
name
());
}
}
...
...
paddle/framework/tensor.h
浏览文件 @
f899150e
...
...
@@ -55,6 +55,8 @@ class Tensor {
template
<
typename
T
>
inline
const
T
*
data
()
const
;
inline
void
switch_place
(
platform
::
Place
new_place
);
/**
* @brief Return a pointer to mutable memory block.
* @note If not exist, then allocation.
...
...
@@ -183,6 +185,15 @@ class Tensor {
size_t
offset_
;
};
inline
void
Tensor
::
switch_place
(
platform
::
Place
new_place
)
{
if
(
holder_
->
place
()
==
new_place
)
{
return
;
}
// TODO(tonyyang-svail): do memcpy here.
PADDLE_THROW
(
"Not Implemented"
);
}
}
// namespace framework
}
// namespace paddle
...
...
paddle/operators/parallel_do_op.cc
浏览文件 @
f899150e
...
...
@@ -13,9 +13,11 @@
limitations under the License. */
#include <vector>
#include "chunk_eval_op.h"
#include "paddle/framework/executor.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/operator.h"
#include "paddle/platform/place.h"
namespace
paddle
{
namespace
operators
{
...
...
@@ -28,10 +30,6 @@ constexpr char kOutputs[] = "outputs";
constexpr
char
kParallelScopes
[]
=
"parallel_scopes"
;
constexpr
char
kParallelBlock
[]
=
"sub_block"
;
// #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
;
...
...
@@ -46,21 +44,66 @@ class ParallelDoOp : public OperatorBase {
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{
// create scope
// copy parameters
}
};
auto
*
block
=
Attr
<
framework
::
BlockDescBind
*>
(
kParallelBlock
);
auto
*
program
=
block
->
Program
();
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
)
{}
// TODO(tonyyang-svail): get places from input
std
::
vector
<
platform
::
Place
>
places
;
places
.
emplace_back
(
platform
::
CPUPlace
());
places
.
emplace_back
(
platform
::
CPUPlace
());
void
Run
(
const
framework
::
Scope
&
scope
,
const
platform
::
DeviceContext
&
dev_ctx
)
const
override
{}
std
::
vector
<
framework
::
Scope
*>
sub_scopes
;
for
(
int
place_idx
=
0
;
place_idx
<
places
.
size
();
++
place_idx
)
{
VLOG
(
3
)
<<
"Run "
<<
place_idx
;
sub_scopes
.
push_back
(
&
scope
.
NewScope
());
auto
&
place
=
places
[
place_idx
];
auto
*
cur_scope
=
sub_scopes
[
place_idx
];
// copy parameter
if
(
dev_ctx
.
GetPlace
()
!=
place
)
{
PADDLE_THROW
(
"Not Implemented"
);
}
// feed input
for
(
auto
&
argu
:
Inputs
(
kInputs
))
{
auto
*
var
=
scope
.
FindVar
(
argu
);
const
auto
&
tensor
=
var
->
Get
<
LoDTensor
>
();
if
(
!
tensor
.
lod
().
empty
())
{
PADDLE_THROW
(
"Disable parallel lod for now"
);
}
else
{
PADDLE_ENFORCE
(
tensor
.
dims
()[
0
]
%
places
.
size
()
==
0
,
"Batch size should be divided by places size"
);
int
begin
=
place_idx
*
tensor
.
dims
()[
0
]
/
places
.
size
();
int
end
=
(
place_idx
+
1
)
*
tensor
.
dims
()[
0
]
/
places
.
size
();
auto
feed_tensor
=
tensor
.
Slice
(
begin
,
end
);
feed_tensor
.
switch_place
(
place
);
auto
*
cur_var
=
cur_scope
->
Var
(
argu
);
auto
*
cur_tensor
=
cur_var
->
GetMutable
<
Tensor
>
();
*
cur_tensor
=
feed_tensor
;
}
}
// execute
auto
executor
=
framework
::
Executor
(
place
);
executor
.
Run
(
*
program
,
cur_scope
,
block
->
ID
(),
false
/*create_local_scope*/
);
}
// merge output
for
(
auto
&
o_name
:
Outputs
(
kOutputs
))
{
std
::
vector
<
const
framework
::
LoDTensor
*>
lod_tensors
;
for
(
auto
*
sub_scope
:
sub_scopes
)
{
lod_tensors
.
push_back
(
&
sub_scope
->
FindVar
(
o_name
)
->
Get
<
LoDTensor
>
());
}
auto
*
lod_tensor_to_be_merged
=
scope
.
FindVar
(
o_name
)
->
GetMutable
<
LoDTensor
>
();
lod_tensor_to_be_merged
->
MergeLoDTensor
(
lod_tensors
,
dev_ctx
.
GetPlace
());
}
}
};
class
ParallelDoOpProtoMaker
:
public
framework
::
OpProtoAndCheckerMaker
{
...
...
@@ -80,16 +123,28 @@ ParallelDo Operator.
}
};
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
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"
);
grad
->
SetType
(
"
parallel_do
_grad"
);
for
(
auto
&
input_param
:
this
->
InputNames
())
{
LOG
(
INFO
)
<<
input_param
;
grad
->
SetInput
(
input_param
,
this
->
Input
(
input_param
));
grad
->
SetOutput
(
framework
::
GradVarName
(
input_param
),
this
->
InputGrad
(
input_param
));
...
...
@@ -116,26 +171,25 @@ class ParallelDoGradOpDescMaker : public framework::SingleGradOpDescMaker {
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));
// }
std
::
vector
<
std
::
string
>
input
{
kParameters
,
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
));
}
}
};
...
...
python/paddle/v2/fluid/layers/control_flow.py
浏览文件 @
f899150e
...
...
@@ -140,7 +140,18 @@ class ParallelDo(object):
step_scope
=
parent_block
.
create_var
(
type
=
core
.
VarDesc
.
VarType
.
STEP_SCOPES
)
self
.
outputs
=
[
parent_block
.
create_var
(
name
=
o
.
name
,
shape
=
o
.
shape
,
dtype
=
o
.
dtype
,
lod_level
=
o
.
lod_level
,
persistable
=
o
.
persistable
,
stop_gradient
=
o
.
stop_gradient
)
for
o
in
self
.
outputs
]
inputs
=
[
parent_block
.
var
(
i
.
name
)
for
i
in
self
.
inputs
]
outputs
=
[
parent_block
.
var
(
o
.
name
)
for
o
in
self
.
outputs
]
parent_block
.
append_op
(
type
=
'parallel_do'
,
...
...
@@ -149,7 +160,7 @@ class ParallelDo(object):
'parameters'
:
self
.
get_parameters
(),
'places'
:
self
.
places
},
outputs
=
{
'outputs'
:
self
.
outputs
,
outputs
=
{
'outputs'
:
outputs
,
'parallel_scopes'
:
[
step_scope
]},
attrs
=
{
'sub_block'
:
current_block
})
...
...
python/paddle/v2/fluid/tests/test_parallel_op.py
浏览文件 @
f899150e
...
...
@@ -12,7 +12,11 @@ import paddle.v2.fluid.core as core
class
ParallelOpTest
(
unittest
.
TestCase
):
def
setUp
(
self
):
x
=
layers
.
data
(
shape
=
[
2
,
3
,
4
],
dtype
=
'float32'
,
name
=
'x'
,
append_batch_size
=
False
)
shape
=
[
-
1
,
3
,
4
],
dtype
=
'float32'
,
name
=
'x'
,
append_batch_size
=
False
,
stop_gradient
=
False
)
places
=
fluid
.
default_main_program
().
global_block
().
create_var
()
pd
=
layers
.
ParallelDo
(
places
=
places
)
...
...
@@ -22,8 +26,16 @@ class ParallelOpTest(unittest.TestCase):
hidden
=
layers
.
fc
(
input
=
data
,
size
=
7
)
pd
.
write_output
(
hidden
)
data
=
pd
()
print
data
print
fluid
.
default_main_program
()
loss
=
layers
.
mean
(
x
=
data
)
append_backward_ops
(
loss
)
exe
=
fluid
.
Executor
(
fluid
.
CPUPlace
())
exe
.
run
(
fluid
.
default_startup_program
())
exe
.
run
(
fluid
.
default_main_program
(),
feed
=
{
x
.
name
:
np
.
random
.
uniform
(
0.1
,
0.6
,
(
2
,
3
,
4
)).
astype
(
"float32"
)
})
def
test_forward
(
self
):
pass
...
...
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