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192b6d63
编写于
4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
Untrack op in eval mode
test=release/1.4
上级
4914da1b
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
89 addition
and
35 deletion
+89
-35
python/paddle/fluid/dygraph/layers.py
python/paddle/fluid/dygraph/layers.py
+12
-0
python/paddle/fluid/dygraph/tracer.py
python/paddle/fluid/dygraph/tracer.py
+59
-8
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+18
-27
未找到文件。
python/paddle/fluid/dygraph/layers.py
浏览文件 @
192b6d63
...
@@ -48,6 +48,12 @@ class Layer(core.Layer):
...
@@ -48,6 +48,12 @@ class Layer(core.Layer):
self
.
_helper
=
LayerObjectHelper
(
self
.
_full_name
)
self
.
_helper
=
LayerObjectHelper
(
self
.
_full_name
)
def
train
(
self
):
framework
.
_dygraph_tracer
().
_train_mode
()
def
eval
(
self
):
framework
.
_dygraph_tracer
().
_eval_mode
()
def
full_name
(
self
):
def
full_name
(
self
):
"""Full name for this layers.
"""Full name for this layers.
...
@@ -254,6 +260,12 @@ class PyLayer(core.PyLayer):
...
@@ -254,6 +260,12 @@ class PyLayer(core.PyLayer):
def
__init__
(
self
):
def
__init__
(
self
):
super
(
PyLayer
,
self
).
__init__
()
super
(
PyLayer
,
self
).
__init__
()
def
train
(
self
):
framework
.
_dygraph_tracer
().
_train_mode
()
def
eval
(
self
):
framework
.
_dygraph_tracer
().
_eval_mode
()
@
classmethod
@
classmethod
def
_do_forward
(
cls
,
inputs
):
def
_do_forward
(
cls
,
inputs
):
return
cls
.
_to_tuple
(
cls
.
forward
(
inputs
))
return
cls
.
_to_tuple
(
cls
.
forward
(
inputs
))
...
...
python/paddle/fluid/dygraph/tracer.py
浏览文件 @
192b6d63
...
@@ -24,7 +24,9 @@ __all__ = ['Tracer']
...
@@ -24,7 +24,9 @@ __all__ = ['Tracer']
def
release_op
(
op
):
def
release_op
(
op
):
del
framework
.
_dygraph_tracer
().
_ops
[
op
.
_trace_id
]
del
framework
.
_dygraph_tracer
().
_ops
[
op
.
_trace_id
].
inputs
del
framework
.
_dygraph_tracer
().
_ops
[
op
.
_trace_id
].
outputs
del
framework
.
_dygraph_tracer
().
_ops
[
op
.
_trace_id
].
backward_refs
class
Tracer
(
core
.
Tracer
):
class
Tracer
(
core
.
Tracer
):
...
@@ -38,6 +40,7 @@ class Tracer(core.Tracer):
...
@@ -38,6 +40,7 @@ class Tracer(core.Tracer):
self
.
_ops
=
defaultdict
()
self
.
_ops
=
defaultdict
()
self
.
_vars
=
defaultdict
()
self
.
_vars
=
defaultdict
()
self
.
_trace_id
=
0
self
.
_trace_id
=
0
self
.
_train_mode
=
True
def
trace_var
(
self
,
name
,
var
):
def
trace_var
(
self
,
name
,
var
):
self
.
_vars
[
name
]
=
var
self
.
_vars
[
name
]
=
var
...
@@ -46,15 +49,57 @@ class Tracer(core.Tracer):
...
@@ -46,15 +49,57 @@ class Tracer(core.Tracer):
return
list
((
item
for
name
,
item
in
six
.
iteritems
(
self
.
_vars
)
return
list
((
item
for
name
,
item
in
six
.
iteritems
(
self
.
_vars
)
if
isinstance
(
item
,
framework
.
Parameter
)))
if
isinstance
(
item
,
framework
.
Parameter
)))
def
trace_op
(
self
,
op
,
stop_gradient
=
False
):
def
trace_op
(
self
,
op
,
inputs
,
outputs
,
stop_gradient
=
False
):
# TODO(minqiyang): remove this line after we take apart all
# backward grads and forward variables
if
self
.
_train_mode
:
op
.
inputs
=
inputs
inps
=
defaultdict
(
list
)
for
k
,
vars
in
six
.
iteritems
(
inputs
):
if
isinstance
(
vars
,
framework
.
Variable
):
inps
[
k
].
append
(
vars
.
_ivar
)
elif
isinstance
(
vars
,
list
)
or
isinstance
(
vars
,
tuple
):
for
var
in
vars
:
inps
[
k
].
append
(
var
.
_ivar
)
op
.
outputs
=
outputs
outs
=
defaultdict
(
list
)
for
k
,
vars
in
six
.
iteritems
(
outputs
):
if
isinstance
(
vars
,
framework
.
Variable
):
outs
[
k
].
append
(
vars
.
_ivar
)
elif
isinstance
(
vars
,
list
)
or
isinstance
(
vars
,
tuple
):
for
var
in
vars
:
outs
[
k
].
append
(
var
.
_ivar
)
else
:
inps
=
defaultdict
(
list
)
for
k
,
vars
in
six
.
iteritems
(
inputs
):
if
isinstance
(
vars
,
framework
.
Variable
):
op
.
previous_ops
.
append
(
vars
.
op
)
inps
[
k
].
append
(
vars
.
_ivar
)
elif
isinstance
(
vars
,
list
)
or
isinstance
(
vars
,
tuple
):
for
var
in
vars
:
op
.
previous_ops
.
append
(
var
.
op
)
inps
[
k
].
append
(
var
.
_ivar
)
op
.
outputs
=
outputs
outs
=
defaultdict
(
list
)
for
k
,
vars
in
six
.
iteritems
(
outputs
):
if
isinstance
(
vars
,
framework
.
Variable
):
vars
.
op
=
op
outs
[
k
].
append
(
vars
.
_ivar
)
elif
isinstance
(
vars
,
list
)
or
isinstance
(
vars
,
tuple
):
for
var
in
vars
:
var
.
op
=
op
outs
[
k
].
append
(
var
.
_ivar
)
# record op's trace id
# record op's trace id
op
.
iop
.
_trace_id
=
self
.
_trace_id
op
.
iop
.
_trace_id
=
self
.
_trace_id
backward_refs
=
self
.
trace
(
op
.
iop
,
op
.
inputs
,
op
.
outp
uts
,
op
.
attrs
,
backward_refs
=
self
.
trace
(
op
.
iop
,
inps
,
o
uts
,
op
.
attrs
,
framework
.
_current_expected_place
(),
framework
.
_current_expected_place
(),
stop_gradient
)
stop_gradient
)
if
not
stop_gradient
:
if
not
stop_gradient
and
self
.
_train_mode
:
self
.
_trace_id
+=
1
self
.
_trace_id
+=
1
self
.
_ops
[
op
.
iop
.
_trace_id
]
=
op
self
.
_ops
[
op
.
iop
.
_trace_id
]
=
op
...
@@ -65,10 +110,16 @@ class Tracer(core.Tracer):
...
@@ -65,10 +110,16 @@ class Tracer(core.Tracer):
# TODO(minqiyang): remove all inputs and outputs after separate
# TODO(minqiyang): remove all inputs and outputs after separate
# var and grad
# var and grad
op
.
backward_refs
=
defaultdict
(
list
)
op
.
backward_refs
=
defaultdict
(
list
)
for
k
,
v
in
six
.
iteritems
(
op
.
inputs
):
for
k
,
v
in
six
.
iteritems
(
inputs
):
if
k
in
backward_refs
:
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
inputs
[
k
]
op
.
backward_refs
[
k
]
=
inputs
[
k
]
for
k
,
v
in
six
.
iteritems
(
o
p
.
o
utputs
):
for
k
,
v
in
six
.
iteritems
(
outputs
):
if
k
in
backward_refs
:
if
k
in
backward_refs
:
op
.
backward_refs
[
k
]
=
op
.
outputs
[
k
]
op
.
backward_refs
[
k
]
=
outputs
[
k
]
def
_train_mode
(
self
):
self
.
_train_mode
=
True
def
_eval_mode
(
self
):
self
.
_train_mode
=
False
python/paddle/fluid/framework.py
浏览文件 @
192b6d63
...
@@ -407,6 +407,7 @@ class Variable(object):
...
@@ -407,6 +407,7 @@ class Variable(object):
if
persistable
else
False
)
if
persistable
else
False
)
if
persistable
:
if
persistable
:
_dygraph_tracer
().
trace_var
(
name
,
self
)
_dygraph_tracer
().
trace_var
(
name
,
self
)
self
.
op
=
None
else
:
else
:
self
.
error_clip
=
error_clip
self
.
error_clip
=
error_clip
...
@@ -935,26 +936,9 @@ class Operator(object):
...
@@ -935,26 +936,9 @@ class Operator(object):
raise
ValueError
(
raise
ValueError
(
"`type` to initialized an Operator can not be None."
)
"`type` to initialized an Operator can not be None."
)
self
.
iop
=
core
.
OpBase
(
type
)
self
.
iop
=
core
.
OpBase
(
type
)
self
.
previous_ops
=
[]
# TODO(minqiyang): remove these lines after we take apart all
self
.
attrs
=
attrs
# backward grads and forward variables
self
.
inputs
=
defaultdict
(
list
)
if
inputs
is
not
None
:
for
k
,
v
in
six
.
iteritems
(
inputs
):
if
isinstance
(
v
,
Variable
):
self
.
inputs
[
k
].
append
(
v
.
_ivar
)
elif
isinstance
(
v
,
list
)
or
isinstance
(
v
,
tuple
):
self
.
inputs
[
k
].
extend
([
var
.
_ivar
for
var
in
v
])
self
.
outputs
=
defaultdict
(
list
)
if
outputs
is
not
None
:
for
k
,
v
in
six
.
iteritems
(
outputs
):
if
isinstance
(
v
,
Variable
):
self
.
outputs
[
k
].
append
(
v
.
_ivar
)
elif
isinstance
(
v
,
list
)
or
isinstance
(
v
,
tuple
):
self
.
outputs
[
k
].
extend
([
var
.
_ivar
for
var
in
v
])
self
.
attrs
=
attrs
if
attrs
else
{}
else
:
else
:
self
.
block
=
block
self
.
block
=
block
self
.
desc
=
desc
self
.
desc
=
desc
...
@@ -1643,15 +1627,18 @@ class Block(object):
...
@@ -1643,15 +1627,18 @@ class Block(object):
block
=
self
,
block
=
self
,
desc
=
None
,
desc
=
None
,
type
=
kwargs
.
get
(
"type"
,
None
),
type
=
kwargs
.
get
(
"type"
,
None
),
inputs
=
kwargs
.
get
(
"inputs"
,
None
)
,
inputs
=
None
,
outputs
=
kwargs
.
get
(
"outputs"
,
None
)
,
outputs
=
None
,
attrs
=
kwargs
.
get
(
"attrs"
,
None
))
attrs
=
kwargs
.
get
(
"attrs"
,
{}
))
# record ops in tracer rather than blocks
# record ops in tracer rather than blocks
#
#
# TODO(minqiyang): add op stop_gradient support in static mode too.
# TODO(minqiyang): add op stop_gradient support in static mode too.
# currently, we only support stop_gradient in dygraph mode.
# currently, we only support stop_gradient in dygraph mode.
_dygraph_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
_dygraph_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"inputs"
,
{}),
kwargs
.
get
(
"outputs"
,
{}),
kwargs
.
get
(
"stop_gradient"
,
False
))
else
:
else
:
op_desc
=
self
.
desc
.
append_op
()
op_desc
=
self
.
desc
.
append_op
()
op
=
Operator
(
op
=
Operator
(
...
@@ -1715,10 +1702,14 @@ class Block(object):
...
@@ -1715,10 +1702,14 @@ class Block(object):
self
,
self
,
None
,
None
,
type
=
kwargs
.
get
(
"type"
,
None
),
type
=
kwargs
.
get
(
"type"
,
None
),
inputs
=
kwargs
.
get
(
"inputs"
,
None
),
inputs
=
None
,
outputs
=
kwargs
.
get
(
"outputs"
,
None
),
outputs
=
None
,
attrs
=
kwargs
.
get
(
"attrs"
,
None
))
attrs
=
kwargs
.
get
(
"attrs"
,
{}))
_dygraph_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"stop_gradient"
,
False
))
_dygraph_tracer
().
trace_op
(
op
,
kwargs
.
get
(
"inputs"
,
{}),
kwargs
.
get
(
"outputs"
,
{}),
kwargs
.
get
(
"stop_gradient"
,
False
))
else
:
else
:
op_desc
=
self
.
desc
.
_prepend_op
()
op_desc
=
self
.
desc
.
_prepend_op
()
op
=
Operator
(
op
=
Operator
(
...
...
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