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体验新版 GitCode,发现更多精彩内容 >>
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提交
187cffd0
编写于
2月 28, 2019
作者:
Q
Qiyang Min
提交者:
GitHub
2月 28, 2019
浏览文件
操作
浏览文件
下载
差异文件
Merge pull request #15928 from velconia/imperative_backward_hooks
Imperative backward hooks
上级
1616c32a
e5f3435d
变更
18
隐藏空白更改
内联
并排
Showing
18 changed file
with
261 addition
and
87 deletion
+261
-87
paddle/fluid/framework/block_desc.cc
paddle/fluid/framework/block_desc.cc
+14
-14
paddle/fluid/framework/block_desc.h
paddle/fluid/framework/block_desc.h
+2
-2
paddle/fluid/framework/python_headers.h
paddle/fluid/framework/python_headers.h
+8
-0
paddle/fluid/imperative/layer.cc
paddle/fluid/imperative/layer.cc
+24
-2
paddle/fluid/imperative/layer.h
paddle/fluid/imperative/layer.h
+44
-3
paddle/fluid/imperative/tracer.cc
paddle/fluid/imperative/tracer.cc
+11
-3
paddle/fluid/pybind/imperative.h
paddle/fluid/pybind/imperative.h
+1
-1
paddle/fluid/pybind/protobuf.cc
paddle/fluid/pybind/protobuf.cc
+0
-2
paddle/fluid/pybind/pybind.cc
paddle/fluid/pybind/pybind.cc
+46
-15
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+14
-29
python/paddle/fluid/imperative/__init__.py
python/paddle/fluid/imperative/__init__.py
+4
-0
python/paddle/fluid/imperative/base.py
python/paddle/fluid/imperative/base.py
+2
-1
python/paddle/fluid/imperative/tracer.py
python/paddle/fluid/imperative/tracer.py
+67
-0
python/paddle/fluid/initializer.py
python/paddle/fluid/initializer.py
+17
-8
python/paddle/fluid/tests/unittests/test_imperative_basic.py
python/paddle/fluid/tests/unittests/test_imperative_basic.py
+0
-0
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
...paddle/fluid/tests/unittests/test_imperative_optimizer.py
+2
-2
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
...n/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
+4
-2
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
...on/paddle/fluid/tests/unittests/test_imperative_resnet.py
+1
-3
未找到文件。
paddle/fluid/framework/block_desc.cc
浏览文件 @
187cffd0
...
...
@@ -13,7 +13,11 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/fluid/framework/block_desc.h"
#include <queue>
#include <unordered_set>
#include <utility>
#include "paddle/fluid/framework/operator.h"
#include "paddle/fluid/framework/program_desc.h"
...
...
@@ -155,6 +159,16 @@ void BlockDesc::RemoveOp(size_t s, size_t e) {
ops_
.
erase
(
ops_
.
begin
()
+
s
,
ops_
.
begin
()
+
e
);
}
void
BlockDesc
::
RemoveOpInternal
(
const
OpDesc
*
op_desc
)
{
// TODO(minqiyang): make this faster
for
(
auto
it
=
ops_
.
begin
();
it
!=
ops_
.
end
();
++
it
)
{
if
(
it
->
get
()
==
op_desc
)
{
ops_
.
erase
(
it
);
break
;
}
}
}
std
::
vector
<
OpDesc
*>
BlockDesc
::
AllOps
()
const
{
std
::
vector
<
OpDesc
*>
res
;
for
(
const
auto
&
op
:
ops_
)
{
...
...
@@ -163,20 +177,6 @@ std::vector<OpDesc *> BlockDesc::AllOps() const {
return
res
;
}
void
BlockDesc
::
Clear
()
{
// clear all ops
ops_
.
clear
();
// clear all vars which are not persistable
for
(
auto
it
=
vars_
.
begin
();
it
!=
vars_
.
end
();)
{
if
(
it
->
second
->
Persistable
())
{
++
it
;
}
else
{
vars_
.
erase
(
it
++
);
}
}
}
void
BlockDesc
::
Flush
()
{
for
(
auto
&
op_desc
:
ops_
)
{
op_desc
->
Flush
();
...
...
paddle/fluid/framework/block_desc.h
浏览文件 @
187cffd0
...
...
@@ -93,12 +93,12 @@ class BlockDesc {
*/
void
RemoveOp
(
size_t
s
,
size_t
e
);
void
RemoveOpInternal
(
const
OpDesc
*
op_desc
);
void
RemoveVar
(
const
std
::
string
&
name
)
{
vars_
.
erase
(
name
);
}
std
::
vector
<
OpDesc
*>
AllOps
()
const
;
void
Clear
();
size_t
OpSize
()
const
{
return
ops_
.
size
();
}
OpDesc
*
Op
(
int
idx
)
const
{
return
ops_
.
at
(
idx
).
get
();
}
...
...
paddle/fluid/framework/python_headers.h
浏览文件 @
187cffd0
...
...
@@ -24,3 +24,11 @@ limitations under the License. */
#pragma pop_macro("_XOPEN_SOURCE")
#pragma pop_macro("_POSIX_C_SOURCE")
#if !defined(PYBIND11_HIDDEN)
#ifdef _WIN32
#define PYBIND11_HIDDEN __declspec(dllexport)
#else
#define PYBIND11_HIDDEN __attribute__((visibility("hidden")))
#endif
#endif
paddle/fluid/imperative/layer.cc
浏览文件 @
187cffd0
...
...
@@ -18,6 +18,7 @@
#include <limits>
#include <map>
#include <random>
#include <unordered_set>
#include <utility>
#include "paddle/fluid/framework/lod_tensor.h"
...
...
@@ -139,6 +140,8 @@ class Autograd {
}
}
}
ready_op
->
InvokeBackwardHooks
();
}
}
...
...
@@ -156,8 +159,10 @@ class Autograd {
for
(
auto
it
:
candidate
->
pre_ops_
)
{
for
(
OpBase
*
pre_op
:
it
.
second
)
{
if
(
!
pre_op
)
continue
;
VLOG
(
5
)
<<
"op dep "
<<
candidate
->
op_desc_
->
Type
()
<<
" <---- "
<<
it
.
first
<<
" <---- "
<<
pre_op
->
op_desc_
->
Type
();
VLOG
(
5
)
<<
"op dep "
<<
candidate
->
op_desc_
->
Type
()
<<
" trace id "
<<
candidate
->
trace_id_
<<
" <---- "
<<
it
.
first
<<
" <---- "
<<
pre_op
->
op_desc_
->
Type
()
<<
" trace id "
<<
pre_op
->
trace_id_
;
if
(
visited
.
find
(
pre_op
)
==
visited
.
end
())
{
visited
.
insert
(
pre_op
);
queue
.
push_back
(
pre_op
);
...
...
@@ -211,6 +216,7 @@ std::map<std::string, std::vector<VarBase*>> OpBase::ApplyGrad() {
return
{};
}
VLOG
(
3
)
<<
"apply op grad: "
<<
op_desc_
->
Type
();
std
::
vector
<
framework
::
VariableValueMap
>
grad_outputs
;
if
(
backward_id_
>
0
)
{
VLOG
(
3
)
<<
"py_layer_grad"
;
...
...
@@ -272,6 +278,22 @@ std::map<std::string, std::vector<VarBase*>> OpBase::ApplyGrad() {
return
input_vars_
;
}
void
OpBase
::
InvokeBackwardHooks
()
{
VLOG
(
3
)
<<
"call backward hooks, hooks num: "
<<
backward_hooks_
.
size
();
// call backward hooks
for
(
py
::
object
&
callable
:
backward_hooks_
)
{
callable
(
this
);
}
}
void
OpBase
::
RegisterBackwardHooks
(
const
py
::
object
&
callable
)
{
VLOG
(
3
)
<<
"Register backward hooks "
<<
trace_id_
;
// TODO(minqiyang): check the callable format
backward_hooks_
.
push_back
(
callable
);
}
void
VarBase
::
RunBackward
()
{
if
(
!
pre_op_
)
return
;
...
...
paddle/fluid/imperative/layer.h
浏览文件 @
187cffd0
...
...
@@ -123,22 +123,32 @@ class VarBase {
private:
VarBase
(
framework
::
Variable
*
var
,
VarBase
*
grad
,
bool
stop_gradient
)
:
var_desc_
(
nullptr
),
:
name_
(),
var_desc_
(
nullptr
),
var_
(
var
),
grads_
(
grad
),
block_
(
nullptr
),
persistable_
(
false
),
stop_gradient_
(
stop_gradient
),
pre_op_
(
nullptr
),
pre_op_out_name_
(),
pre_op_out_idx_
(
-
1
)
{}
public:
virtual
~
VarBase
()
{
// TODO(minqiyang): remove var desc from block desc
if
(
var_
)
{
delete
var_
;
var_
=
nullptr
;
}
if
(
grads_
)
{
delete
grads_
;
grads_
=
nullptr
;
}
pre_op_
=
nullptr
;
pre_op_out_idx_
=
-
1
;
}
inline
OpBase
*
PreOp
()
const
{
return
pre_op_
;
}
...
...
@@ -151,6 +161,14 @@ class VarBase {
void
RunBackward
();
inline
void
ResetPreOp
(
OpBase
*
op
)
{
if
(
op
==
pre_op_
)
{
// clear pre_op info when op equals to var's pre_op
pre_op_
=
nullptr
;
pre_op_out_idx_
=
-
1
;
}
}
void
TrackPreOp
(
OpBase
*
pre_op
,
const
std
::
string
&
pre_op_out_name
,
int
pre_op_out_idx
,
bool
pre_op_stop_gradient
)
{
pre_op_
=
pre_op
;
...
...
@@ -184,11 +202,15 @@ class VarBase {
return
string
::
Sprintf
(
"%s@IGrad"
,
var_desc_
->
Name
());
}
std
::
string
name_
;
framework
::
VarDesc
*
var_desc_
;
framework
::
Variable
*
var_
;
VarBase
*
grads_
;
framework
::
BlockDesc
*
block_
;
bool
persistable_
;
private:
bool
stop_gradient_
;
OpBase
*
pre_op_
;
...
...
@@ -199,15 +221,27 @@ class VarBase {
/* The wrapper for OpDesc which holds a OpDesc and a OpDesc of its
* gradient. This object should be managed totally by Python intepreter.
*/
class
OpBase
{
class
PYBIND11_HIDDEN
OpBase
{
public:
OpBase
()
:
op_desc_
(
nullptr
),
forward_id_
(
-
1
),
backward_id_
(
-
1
),
place_
(
platform
::
CPUPlace
())
{}
trace_id_
(
-
1
),
place_
(
platform
::
CPUPlace
()),
backward_hooks_
()
{}
virtual
~
OpBase
()
{
// TODO(minqiyang): remove op_desc from block_desc in tracer
//
// reset all output vars' pre op
for
(
auto
iter
:
output_vars_
)
{
for
(
VarBase
*
var
:
iter
.
second
)
{
var
->
ResetPreOp
(
this
);
}
}
// release resource
for
(
framework
::
OpDesc
*
desc
:
grad_op_descs_
)
{
delete
desc
;
}
...
...
@@ -215,6 +249,10 @@ class OpBase {
std
::
map
<
std
::
string
,
std
::
vector
<
VarBase
*>>
ApplyGrad
();
void
RegisterBackwardHooks
(
const
py
::
object
&
callable
);
void
InvokeBackwardHooks
();
// One of `op_desc_` or `forward_id_` is set, not both.
// For pure python PyLayer, use `forward_id_`, otherwise, use op_desc_.
framework
::
OpDesc
*
op_desc_
;
...
...
@@ -225,6 +263,7 @@ class OpBase {
// Note: each fwd op corresponds to a vector of bwd ops.
std
::
vector
<
framework
::
OpDesc
*>
grad_op_descs_
;
int
backward_id_
;
int
trace_id_
;
platform
::
Place
place_
;
...
...
@@ -239,6 +278,8 @@ class OpBase {
std
::
vector
<
framework
::
VariableValueMap
>
grad_output_vars_
;
framework
::
BlockDesc
*
block_
;
std
::
vector
<
py
::
object
>
backward_hooks_
;
};
class
Layer
{
...
...
paddle/fluid/imperative/tracer.cc
浏览文件 @
187cffd0
...
...
@@ -14,7 +14,10 @@
#include "paddle/fluid/imperative/tracer.h"
#include <memory>
#include <set>
#include <unordered_map>
#include <unordered_set>
#include "paddle/fluid/operators/math/math_function.h"
#include "paddle/fluid/platform/device_context.h"
...
...
@@ -110,7 +113,8 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
std
::
map
<
std
::
string
,
VarBase
*>
vars
;
framework
::
OpDesc
*
op_desc
=
op
->
op_desc_
;
VLOG
(
3
)
<<
"tracer tracing "
<<
op_desc
->
Type
();
VLOG
(
3
)
<<
"tracer tracing "
<<
op_desc
->
Type
()
<<
" trace id "
<<
op
->
trace_id_
;
op_desc
->
InferShape
(
*
block
);
op_desc
->
InferVarType
(
block
);
...
...
@@ -133,11 +137,13 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
if
(
inp
->
PreOp
()
&&
!
inp
->
IsStopGradient
())
{
op
->
pre_ops_
[
it
.
first
].
push_back
(
inp
->
PreOp
());
op
->
pre_ops_out_idx_
[
it
.
first
].
push_back
(
inp
->
PreOpOutIdx
());
VLOG
(
3
)
<<
"add pre op "
<<
inp
->
PreOp
()
->
op_desc_
->
Type
();
}
else
{
op
->
pre_ops_
[
it
.
first
].
push_back
(
nullptr
);
}
VLOG
(
3
)
<<
"input vname "
<<
inp
->
var_desc_
->
Name
()
<<
" "
<<
inp
->
var_
->
IsInitialized
();
<<
inp
->
var_
->
IsInitialized
()
<<
" stop_gradient "
<<
inp
->
IsStopGradient
();
}
}
...
...
@@ -189,6 +195,7 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
op
->
grad_input_vars_
.
resize
(
op
->
grad_op_descs_
.
size
());
op
->
grad_output_vars_
.
resize
(
op
->
grad_op_descs_
.
size
());
for
(
size_t
i
=
0
;
i
<
op
->
grad_op_descs_
.
size
();
++
i
)
{
framework
::
OpDesc
*
grad_op_desc
=
op
->
grad_op_descs_
[
i
];
for
(
auto
it
:
grad_op_desc
->
Inputs
())
{
...
...
@@ -201,7 +208,6 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
PADDLE_ENFORCE
(
fwd_var_it
!=
vars
.
end
());
// Forward inputs or outputs.
grad_in_vars
.
push_back
(
fwd_var_it
->
second
->
var_
);
vars_saved_for_backward
.
insert
(
it
.
first
);
}
else
{
VarBase
*
var
=
vars
[
var_it
->
second
];
if
(
!
var
->
grads_
->
var_
->
IsInitialized
())
{
...
...
@@ -211,6 +217,8 @@ std::set<std::string> Tracer::Trace(OpBase* op, const VarBasePtrMap& inputs,
// Douts.
grad_in_vars
.
push_back
(
var
->
grads_
->
var_
);
}
vars_saved_for_backward
.
insert
(
it
.
first
);
}
}
...
...
paddle/fluid/pybind/imperative.h
浏览文件 @
187cffd0
...
...
@@ -33,7 +33,7 @@ class Layer : public imperative::Layer {
}
};
class
PyOpBase
:
public
imperative
::
OpBase
{
class
P
YBIND11_HIDDEN
P
yOpBase
:
public
imperative
::
OpBase
{
public:
using
imperative
::
OpBase
::
OpBase
;
// Inherit constructors
};
...
...
paddle/fluid/pybind/protobuf.cc
浏览文件 @
187cffd0
...
...
@@ -189,8 +189,6 @@ void BindBlockDesc(pybind11::module *m) {
return
self
.
HasVar
(
name
);
},
pybind11
::
return_value_policy
::
reference
)
.
def
(
"_clear_block"
,
[](
pd
::
BlockDesc
&
self
)
{
return
self
.
Clear
();
},
pybind11
::
return_value_policy
::
reference
)
.
def
(
"_rename_var"
,
[](
pd
::
BlockDesc
&
self
,
const
pybind11
::
bytes
&
byte_name
,
const
pybind11
::
bytes
&
byte_name_new
)
{
...
...
paddle/fluid/pybind/pybind.cc
浏览文件 @
187cffd0
...
...
@@ -177,6 +177,23 @@ PYBIND11_MODULE(core, m) {
py
::
return_value_policy
::
take_ownership
)
.
def
(
"value"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
var_
;
},
py
::
return_value_policy
::
reference
)
.
def_property
(
"name"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
name_
;
},
[](
imperative
::
VarBase
&
self
,
const
std
::
string
&
name
)
{
self
.
name_
=
name
;
})
.
def_property
(
"block"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
block_
;
},
[](
imperative
::
VarBase
&
self
,
framework
::
BlockDesc
*
block
)
{
self
.
block_
=
block
;
},
py
::
return_value_policy
::
reference
)
.
def_property
(
"persistable"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
persistable_
;
},
[](
imperative
::
VarBase
&
self
,
const
bool
persistable
)
{
self
.
persistable_
=
persistable
;
})
.
def_property
(
"desc"
,
[](
const
imperative
::
VarBase
&
self
)
{
return
self
.
var_desc_
;
},
...
...
@@ -193,6 +210,10 @@ PYBIND11_MODULE(core, m) {
py
::
class_
<
imperative
::
OpBase
,
PyOpBase
>
(
m
,
"OpBase"
,
R"DOC()DOC"
)
.
def
(
py
::
init
<>
())
.
def
(
"register_backward_hooks"
,
[](
imperative
::
OpBase
&
self
,
const
py
::
object
&
callable
)
{
self
.
RegisterBackwardHooks
(
callable
);
})
.
def_property
(
"desc"
,
[](
const
imperative
::
OpBase
&
self
)
{
return
self
.
op_desc_
;
},
[](
imperative
::
OpBase
&
self
,
framework
::
OpDesc
*
op_desc
)
{
...
...
@@ -201,6 +222,16 @@ PYBIND11_MODULE(core, m) {
}
},
py
::
return_value_policy
::
reference
)
.
def_property
(
"_trace_id"
,
[](
const
imperative
::
OpBase
&
self
)
{
pybind11
::
gil_scoped_release
release
;
return
self
.
trace_id_
;
},
[](
imperative
::
OpBase
&
self
,
int
trace_id
)
{
pybind11
::
gil_scoped_release
release
;
self
.
trace_id_
=
trace_id
;
},
py
::
return_value_policy
::
reference
)
.
def_property
(
"forward_id"
,
[](
const
imperative
::
OpBase
&
self
)
{
return
self
.
forward_id_
;
},
...
...
@@ -413,11 +444,11 @@ PYBIND11_MODULE(core, m) {
Set LoD of the LoDTensor according to recursive sequence length.
For example, if recursive_sequence_lengths=[[2, 3]], meaning that
there are two sequences with length 2 and 3 respectively, the
corresponding lod would be [[0, 2, 2+3]], i.e, [[0, 2, 5]].
there are two sequences with length 2 and 3 respectively, the
corresponding lod would be [[0, 2, 2+3]], i.e, [[0, 2, 5]].
Args:
recursive_sequence_lengths (List[List[int]]): sequence lengths.
recursive_sequence_lengths (List[List[int]]): sequence lengths.
)DOC"
)
.
def
(
"lod"
,
[](
LoDTensor
&
self
)
->
std
::
vector
<
std
::
vector
<
size_t
>>
{
...
...
@@ -448,7 +479,7 @@ PYBIND11_MODULE(core, m) {
Return the sequence length of the LoDTensor corresponding to LoD.
Returns:
out (List[List[int]): the sequence lengths.
out (List[List[int]): the sequence lengths.
)DOC"
)
.
def
(
"has_valid_recursive_sequence_lengths"
,
[](
LoDTensor
&
self
)
->
bool
{
...
...
@@ -599,29 +630,29 @@ All parameter, weight, gradient are variables in Paddle.
},
py
::
arg
(
"name"
),
R"DOC(
Find or create variable named :code:`name` in the current scope.
Find or create variable named :code:`name` in the current scope.
If the variable named :code:`name` does not exist in the
If the variable named :code:`name` does not exist in the
current scope, the variable would be created. Otherwise,
return the existing variable.
return the existing variable.
Args:
name (str): the variable name.
name (str): the variable name.
Returns:
out (core.Variable): the found or created variable.
out (core.Variable): the found or created variable.
)DOC"
,
py
::
return_value_policy
::
reference
)
.
def
(
"find_var"
,
&
Scope
::
FindVar
,
py
::
arg
(
"name"
),
R"DOC(
Find variable named :code:`name` in the current scope or
Find variable named :code:`name` in the current scope or
its parent scope. Return None if not found.
Args:
name (str): the variable name.
Returns:
out (core.Variable|None): the found variable or None.
out (core.Variable|None): the found variable or None.
)DOC"
,
py
::
return_value_policy
::
reference
)
.
def
(
"new_scope"
,
[](
Scope
&
self
)
->
Scope
*
{
return
&
self
.
NewScope
();
},
...
...
@@ -645,7 +676,7 @@ All parameter, weight, gradient are variables in Paddle.
},
R"DOC(
Create a new scope.
Returns:
out (core._Scope): the created scope.
)DOC"
,
...
...
python/paddle/fluid/framework.py
浏览文件 @
187cffd0
...
...
@@ -393,6 +393,9 @@ class Variable(object):
if
not
self
.
_ivar
:
self
.
_ivar
=
core
.
VarBase
(
stop_gradient
)
self
.
_ivar
.
desc
=
self
.
desc
self
.
_ivar
.
block
=
block
.
desc
self
.
_ivar
.
name
=
name
self
.
_ivar
.
persistable
=
persistable
if
persistable
:
self
.
block
.
vars
[
name
]
=
self
else
:
...
...
@@ -721,7 +724,9 @@ class Operator(object):
out_arg_names
=
[]
for
arg
in
out_args
:
out_arg_names
.
append
(
cpt
.
to_text
(
arg
.
name
))
arg
.
op
=
self
# TODO(minqiyang): could we remove variable's op in static mode?
if
not
_in_imperative_mode
():
arg
.
op
=
self
self
.
desc
.
set_output
(
out_proto
.
name
,
out_arg_names
)
if
op_attrs
is
not
None
:
...
...
@@ -1200,15 +1205,6 @@ class Block(object):
else
:
raise
ValueError
(
"Var {0} is not found recursively"
.
format
(
name
))
def
_clear_block
(
self
):
# TODO(minqiyang): move this to backward_hooks
self
.
desc
.
_clear_block
()
for
name
in
self
.
vars
.
keys
():
assert
self
.
vars
[
name
].
persistable
del
self
.
ops
[:]
def
all_parameters
(
self
):
return
list
(
self
.
iter_parameters
())
...
...
@@ -1345,26 +1341,13 @@ class Block(object):
#
# TODO(minqiyang): add op stop_gradient support in static mode too.
# currently, we only support stop_gradient in imperative mode.
self
.
_trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
self
.
ops
.
append
(
op
)
_imperative_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
else
:
self
.
ops
.
append
(
op
)
return
op
def
_trace_op
(
self
,
op
,
stop_gradient
=
False
):
backward_refs
=
_imperative_tracer
().
trace
(
op
.
iop
,
op
.
inputs
,
op
.
outputs
,
self
.
desc
,
_imperative_current_expected_place_
,
stop_gradient
)
# TODO(minqiyang): support backward_hooks to eager remove backward_refs
op
.
backward_refs
=
defaultdict
(
list
)
for
k
,
v
in
six
.
iteritems
(
op
.
inputs
):
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
inputs
[
k
]
for
k
,
v
in
six
.
iteritems
(
op
.
outputs
):
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
outputs
[
k
]
def
_insert_op
(
self
,
index
,
*
args
,
**
kwargs
):
"""
Insert a Operator according to the giving arguments.
...
...
@@ -1417,9 +1400,11 @@ class Block(object):
inputs
=
kwargs
.
get
(
"inputs"
,
None
),
outputs
=
kwargs
.
get
(
"outputs"
,
None
),
attrs
=
kwargs
.
get
(
"attrs"
,
None
))
self
.
ops
.
insert
(
0
,
op
)
if
_in_imperative_mode
():
self
.
_trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
_imperative_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
else
:
self
.
ops
.
insert
(
0
,
op
)
return
op
def
_sync_with_cpp
(
self
):
...
...
python/paddle/fluid/imperative/__init__.py
浏览文件 @
187cffd0
...
...
@@ -23,7 +23,11 @@ from .layers import *
from
.
import
nn
from
.nn
import
*
from
.
import
tracer
from
.tracer
import
*
__all__
=
[]
__all__
+=
layers
.
__all__
__all__
+=
base
.
__all__
__all__
+=
nn
.
__all__
__all__
+=
tracer
.
__all__
python/paddle/fluid/imperative/base.py
浏览文件 @
187cffd0
...
...
@@ -16,6 +16,7 @@ import numpy as np
from
paddle.fluid
import
core
from
paddle.fluid
import
framework
from
.tracer
import
Tracer
__all__
=
[
'enabled'
,
'guard'
,
'to_variable'
]
...
...
@@ -28,7 +29,7 @@ def enabled():
def
guard
(
place
=
None
):
train
=
framework
.
Program
()
startup
=
framework
.
Program
()
tracer
=
core
.
Tracer
(
train
.
current_block
().
desc
)
tracer
=
Tracer
(
train
.
current_block
().
desc
)
if
place
is
None
:
if
core
.
is_compiled_with_cuda
():
...
...
python/paddle/fluid/imperative/tracer.py
0 → 100644
浏览文件 @
187cffd0
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
from
__future__
import
print_function
import
six
from
collections
import
defaultdict
from
paddle.fluid
import
core
from
paddle.fluid
import
framework
__all__
=
[
'Tracer'
]
def
release_op
(
op
):
del
framework
.
_imperative_tracer
().
_ops
[
op
.
_trace_id
]
class
Tracer
(
core
.
Tracer
):
"""
Python wrapper of imperative tracer
"""
def
__init__
(
self
,
block
):
super
(
Tracer
,
self
).
__init__
(
block
)
self
.
_ops
=
defaultdict
()
self
.
_trace_id
=
0
def
trace_op
(
self
,
op
,
stop_gradient
=
False
):
# record op's trace id
op
.
iop
.
_trace_id
=
self
.
_trace_id
# trace op and save it
backward_refs
=
self
.
trace
(
op
.
iop
,
op
.
inputs
,
op
.
outputs
,
op
.
block
.
desc
,
framework
.
_current_expected_place
(),
stop_gradient
)
if
not
stop_gradient
:
self
.
_trace_id
+=
1
self
.
_ops
[
op
.
iop
.
_trace_id
]
=
op
# register backward hooks and variables if needed
if
len
(
backward_refs
)
>
0
:
op
.
iop
.
register_backward_hooks
(
release_op
)
# TODO(minqiyang): remove all inputs and outputs after seperate
# var and grad
op
.
backward_refs
=
defaultdict
(
list
)
for
k
,
v
in
six
.
iteritems
(
op
.
inputs
):
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
inputs
[
k
]
for
k
,
v
in
six
.
iteritems
(
op
.
outputs
):
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
outputs
[
k
]
python/paddle/fluid/initializer.py
浏览文件 @
187cffd0
...
...
@@ -19,6 +19,7 @@ import numpy as np
from
.wrapped_decorator
import
signature_safe_contextmanager
from
.core
import
VarDesc
from
.
import
unique_name
from
.imperative
import
base
as
imperative_base
__all__
=
[
'Constant'
,
'Uniform'
,
'Normal'
,
'TruncatedNormal'
,
'Xavier'
,
'Bilinear'
,
...
...
@@ -165,7 +166,8 @@ class ConstantInitializer(Initializer):
'force_cpu'
:
self
.
_force_cpu
or
force_init_on_cpu
()
},
stop_gradient
=
True
)
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -244,7 +246,8 @@ class UniformInitializer(Initializer):
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -322,7 +325,8 @@ class NormalInitializer(Initializer):
outputs
=
{
"Out"
:
var
},
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -400,7 +404,8 @@ class TruncatedNormalInitializer(Initializer):
outputs
=
{
"Out"
:
var
},
attrs
=
{
"in_dtype"
:
out_var
.
dtype
,
"out_dtype"
:
var
.
dtype
})
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -505,7 +510,8 @@ class XavierInitializer(Initializer):
"seed"
:
self
.
_seed
},
stop_gradient
=
True
)
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -605,7 +611,8 @@ class MSRAInitializer(Initializer):
"seed"
:
self
.
_seed
},
stop_gradient
=
True
)
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -703,7 +710,8 @@ class BilinearInitializer(Initializer):
'shape'
:
list
(
shape
),
value_name
:
values
})
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
@@ -761,7 +769,8 @@ class NumpyArrayInitializer(Initializer):
value_name
:
values
},
stop_gradient
=
True
)
var
.
op
=
op
if
not
imperative_base
.
enabled
():
var
.
op
=
op
return
op
...
...
python/paddle/fluid/tests/unittests/test_imperative.py
→
python/paddle/fluid/tests/unittests/test_imperative
_basic
.py
浏览文件 @
187cffd0
文件已移动
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
浏览文件 @
187cffd0
...
...
@@ -12,6 +12,8 @@
# See the License for the specific language governing permissions and
# limitations under the License.
from
__future__
import
print_function
import
contextlib
import
unittest
import
numpy
as
np
...
...
@@ -142,8 +144,6 @@ class TestImperativeMnist(unittest.TestCase):
sgd
.
minimize
(
avg_loss
)
mnist
.
clear_gradients
()
fluid
.
default_main_program
().
global_block
().
_clear_block
()
dy_param_value
=
{}
for
param
in
mnist
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_numpy
()
...
...
python/paddle/fluid/tests/unittests/test_imperative_ptb_rnn.py
浏览文件 @
187cffd0
...
...
@@ -243,7 +243,9 @@ class TestImperativePtbRnn(unittest.TestCase):
dy_loss
=
None
last_hidden
=
None
last_cell
=
None
for
i
in
range
(
2
):
batch_num
=
50
for
i
in
range
(
batch_num
):
x_data
=
np
.
arange
(
12
).
reshape
(
4
,
3
).
astype
(
'int64'
)
y_data
=
np
.
arange
(
1
,
13
).
reshape
(
4
,
3
).
astype
(
'int64'
)
x_data
=
x_data
.
reshape
((
-
1
,
num_steps
,
1
))
...
...
@@ -302,7 +304,7 @@ class TestImperativePtbRnn(unittest.TestCase):
static_loss_value
=
None
static_last_cell_value
=
None
static_last_hidden_value
=
None
for
i
in
range
(
2
):
for
i
in
range
(
batch_num
):
x_data
=
np
.
arange
(
12
).
reshape
(
4
,
3
).
astype
(
'int64'
)
y_data
=
np
.
arange
(
1
,
13
).
reshape
(
4
,
3
).
astype
(
'int64'
)
x_data
=
x_data
.
reshape
((
-
1
,
num_steps
,
1
))
...
...
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
浏览文件 @
187cffd0
...
...
@@ -231,7 +231,7 @@ class TestImperativeResnet(unittest.TestCase):
seed
=
90
batch_size
=
train_parameters
[
"batch_size"
]
batch_num
=
2
batch_num
=
2
0
with
fluid
.
imperative
.
guard
():
fluid
.
default_startup_program
().
random_seed
=
seed
fluid
.
default_main_program
().
random_seed
=
seed
...
...
@@ -286,8 +286,6 @@ class TestImperativeResnet(unittest.TestCase):
optimizer
.
minimize
(
avg_loss
)
resnet
.
clear_gradients
()
fluid
.
default_main_program
().
global_block
().
_clear_block
()
dy_param_value
=
{}
for
param
in
resnet
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_numpy
()
...
...
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