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1bf4b8ab
编写于
2月 22, 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
keep parameters in block
test=develop
上级
8fe0c0c5
变更
4
显示空白变更内容
内联
并排
Showing
4 changed file
with
16 addition
and
33 deletion
+16
-33
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+5
-6
python/paddle/fluid/imperative/nn.py
python/paddle/fluid/imperative/nn.py
+0
-3
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
...paddle/fluid/tests/unittests/test_imperative_optimizer.py
+5
-12
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
...on/paddle/fluid/tests/unittests/test_imperative_resnet.py
+6
-12
未找到文件。
python/paddle/fluid/framework.py
浏览文件 @
1bf4b8ab
...
...
@@ -382,6 +382,8 @@ class Variable(object):
if
not
self
.
_ivar
:
self
.
_ivar
=
core
.
VarBase
(
stop_gradient
)
self
.
_ivar
.
desc
=
self
.
desc
if
persistable
:
self
.
block
.
vars
[
name
]
=
self
else
:
self
.
block
.
vars
[
name
]
=
self
self
.
op
=
None
...
...
@@ -1188,11 +1190,11 @@ class Block(object):
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
():
if
not
self
.
vars
[
name
].
persistable
:
del
self
.
vars
[
name
]
assert
self
.
vars
[
name
].
persistable
del
self
.
ops
[:]
...
...
@@ -1341,11 +1343,8 @@ class Block(object):
backward_refs
=
_imperative_tracer
().
trace
(
op
.
iop
,
op
.
inputs
,
op
.
outputs
,
self
.
desc
,
_imperative_current_expected_place_
,
stop_gradient
)
print
(
"backward_refs"
,
backward_refs
)
import
sys
sys
.
stdout
.
flush
()
# TODO(minqiyang): support backward
hooks to eager remove backward_refs
# 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
:
...
...
python/paddle/fluid/imperative/nn.py
浏览文件 @
1bf4b8ab
...
...
@@ -225,9 +225,6 @@ class FC(layers.Layer):
act
=
act
,
name
=
name
)
def
parameters
(
self
):
return
[
self
.
_w
,
self
.
_b
]
def
_build_once
(
self
,
input
):
input_shape
=
input
.
shape
param_shape
=
[
...
...
python/paddle/fluid/tests/unittests/test_imperative_optimizer.py
浏览文件 @
1bf4b8ab
...
...
@@ -131,8 +131,7 @@ class TestImperativeMnist(unittest.TestCase):
dy_out
=
avg_loss
.
_numpy
()
if
epoch
==
0
and
batch_id
==
0
:
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
mnist
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_numpy
()
avg_loss
.
_backward
()
...
...
@@ -142,8 +141,7 @@ class TestImperativeMnist(unittest.TestCase):
fluid
.
default_main_program
().
global_block
().
_clear_block
()
dy_param_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
mnist
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_numpy
()
with
new_program_scope
():
...
...
@@ -169,8 +167,7 @@ class TestImperativeMnist(unittest.TestCase):
# initialize params and fetch them
static_param_init_value
=
{}
static_param_name_list
=
[]
for
param
in
fluid
.
default_startup_program
().
global_block
(
).
all_parameters
():
for
param
in
mnist
.
parameters
():
static_param_name_list
.
append
(
param
.
name
)
out
=
exe
.
run
(
fluid
.
default_startup_program
(),
...
...
@@ -204,16 +201,12 @@ class TestImperativeMnist(unittest.TestCase):
self
.
assertTrue
(
np
.
allclose
(
dy_x_data
.
all
(),
static_x_data
.
all
()))
for
key
,
value
in
six
.
iteritems
(
static_param_init_value
):
if
not
np
.
allclose
(
value
,
dy_param_init_value
[
key
]):
print
(
key
,
value
,
dy_param_value
[
key
])
# self.assertTrue(np.allclose(value, dy_param_init_value[key]))
self
.
assertTrue
(
np
.
allclose
(
value
,
dy_param_init_value
[
key
]))
self
.
assertTrue
(
np
.
allclose
(
static_out
,
dy_out
))
for
key
,
value
in
six
.
iteritems
(
static_param_value
):
if
not
np
.
allclose
(
value
,
dy_param_value
[
key
],
atol
=
1e-6
):
print
(
key
,
value
,
dy_param_value
[
key
])
# self.assertTrue(np.allclose(value, dy_param_value[key], atol=1e-5))
self
.
assertTrue
(
np
.
allclose
(
value
,
dy_param_value
[
key
],
atol
=
1e-5
))
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/tests/unittests/test_imperative_resnet.py
浏览文件 @
1bf4b8ab
...
...
@@ -223,8 +223,7 @@ class TestImperativeResnet(unittest.TestCase):
batch_size
=
batch_size
)
dy_param_init_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
dy_param_init_value
[
param
.
name
]
=
param
.
_numpy
()
for
batch_id
,
data
in
enumerate
(
train_reader
()):
...
...
@@ -247,16 +246,14 @@ class TestImperativeResnet(unittest.TestCase):
dy_out
=
avg_loss
.
_numpy
()
if
batch_id
==
0
:
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
if
param
.
name
not
in
dy_param_init_value
:
dy_param_init_value
[
param
.
name
]
=
param
.
_numpy
()
avg_loss
.
_backward
()
dy_grad_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
if
not
param
.
stop_gradient
:
np_array
=
np
.
array
(
param
.
_ivar
.
_grad_ivar
().
value
()
.
get_tensor
())
...
...
@@ -269,8 +266,7 @@ class TestImperativeResnet(unittest.TestCase):
fluid
.
default_main_program
().
global_block
().
_clear_block
()
dy_param_value
=
{}
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
dy_param_value
[
param
.
name
]
=
param
.
_numpy
()
with
new_program_scope
():
...
...
@@ -302,11 +298,9 @@ class TestImperativeResnet(unittest.TestCase):
static_param_init_value
=
{}
static_param_name_list
=
[]
static_grad_name_list
=
[]
for
param
in
fluid
.
default_startup_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
static_param_name_list
.
append
(
param
.
name
)
for
param
in
fluid
.
default_main_program
().
global_block
(
).
all_parameters
():
for
param
in
resnet
.
parameters
():
if
not
param
.
stop_gradient
:
static_grad_name_list
.
append
(
param
.
name
+
core
.
grad_var_suffix
())
...
...
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