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体验新版 GitCode,发现更多精彩内容 >>
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5e725dc5
编写于
7月 11, 2018
作者:
Y
yuyang18
浏览文件
操作
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电子邮件补丁
差异文件
Hide Optimizer methods
上级
6c83dcd6
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
23 addition
and
23 deletion
+23
-23
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+12
-12
python/paddle/fluid/tests/unittests/test_optimizer.py
python/paddle/fluid/tests/unittests/test_optimizer.py
+11
-11
未找到文件。
python/paddle/fluid/optimizer.py
浏览文件 @
5e725dc5
...
...
@@ -29,7 +29,7 @@ __all__ = [
'SGD'
,
'Momentum'
,
'Adagrad'
,
'Adam'
,
'Adamax'
,
'DecayedAdagrad'
,
'Ftrl'
,
'SGDOptimizer'
,
'MomentumOptimizer'
,
'AdagradOptimizer'
,
'AdamOptimizer'
,
'AdamaxOptimizer'
,
'DecayedAdagradOptimizer'
,
'RMSPropOptimizer'
,
'FtrlOptimizer'
,
'Adadelta'
,
'ModelAverage'
,
'
Optimizer'
,
'
RMSPropOptimizer'
'FtrlOptimizer'
,
'Adadelta'
,
'ModelAverage'
,
'RMSPropOptimizer'
]
...
...
@@ -67,7 +67,7 @@ class Optimizer(object):
self
.
_LARS_weight_decay
=
LARS_weight_decay
def
_create_global_learning_rate
(
self
):
lr
=
self
.
global_learning_rate
()
lr
=
self
.
_
global_learning_rate
()
if
isinstance
(
lr
,
framework
.
Variable
):
return
...
...
@@ -86,7 +86,7 @@ class Optimizer(object):
dtype
=
'float32'
if
self
.
_dtype
==
None
else
self
.
_dtype
,
persistable
=
True
)
def
global_learning_rate
(
self
,
program
=
None
):
def
_
global_learning_rate
(
self
,
program
=
None
):
"""
get global decayed learning rate
:return:
...
...
@@ -110,9 +110,9 @@ class Optimizer(object):
return
param_lr
else
:
if
param_lr
==
1.0
:
return
self
.
global_learning_rate
()
return
self
.
_
global_learning_rate
()
else
:
return
self
.
global_learning_rate
()
*
param_lr
return
self
.
_
global_learning_rate
()
*
param_lr
def
_create_accumulators
(
self
,
block
,
parameters
):
"""Create all accumulators needed by the parameters
...
...
@@ -185,10 +185,10 @@ class Optimizer(object):
format
(
name
,
param
.
name
))
return
self
.
_accumulators
[
name
][
param
.
name
]
def
create_optimization_pass
(
self
,
parameters_and_grads
,
loss
,
startup_program
=
None
):
def
_
create_optimization_pass
(
self
,
parameters_and_grads
,
loss
,
startup_program
=
None
):
"""Add optimization operators to update gradients to variables.
Args:
...
...
@@ -221,7 +221,7 @@ class Optimizer(object):
self
.
_create_global_learning_rate
()
if
self
.
_LARS_weight_decay
>
0.0
:
layers
.
append_LARS
(
parameters_and_grads
,
self
.
global_learning_rate
(),
self
.
_
global_learning_rate
(),
self
.
_LARS_weight_decay
)
optimize_ops
=
[]
...
...
@@ -262,8 +262,8 @@ class Optimizer(object):
params_grads
=
append_regularization_ops
(
params_grads
,
self
.
regularization
)
optimize_ops
=
self
.
create_optimization_pass
(
params_grads
,
loss
,
startup_program
)
optimize_ops
=
self
.
_
create_optimization_pass
(
params_grads
,
loss
,
startup_program
)
return
optimize_ops
,
params_grads
...
...
python/paddle/fluid/tests/unittests/test_optimizer.py
浏览文件 @
5e725dc5
...
...
@@ -97,7 +97,7 @@ class TestMomentumOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
momentum_optimizer
.
get_accumulators
()),
0
)
opts
=
momentum_optimizer
.
create_optimization_pass
(
opts
=
momentum_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
3
)
sgd_op
=
opts
[
-
1
]
...
...
@@ -151,7 +151,7 @@ class TestMomentumOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
momentum_optimizer
.
get_accumulators
()),
0
)
opts
=
momentum_optimizer
.
create_optimization_pass
(
opts
=
momentum_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
3
)
sgd_op
=
opts
[
-
1
]
...
...
@@ -214,8 +214,8 @@ class TestAdagradOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
adagrad_optimizer
.
get_accumulators
()),
0
)
opts
=
adagrad_optimizer
.
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
opts
=
adagrad_optimizer
.
_create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
3
)
self
.
assertEqual
([
op
.
type
for
op
in
opts
],
[
"fill_constant"
,
"elementwise_mul"
,
"adagrad"
])
...
...
@@ -278,8 +278,8 @@ class TestAdamOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
adam_optimizer
.
get_accumulators
()),
0
)
opts
=
adam_optimizer
.
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
opts
=
adam_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
5
)
self
.
assertEqual
(
[
op
.
type
for
op
in
opts
],
...
...
@@ -345,8 +345,8 @@ class TestAdamaxOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
adamax_optimizer
.
get_accumulators
()),
0
)
opts
=
adamax_optimizer
.
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
opts
=
adamax_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
4
)
self
.
assertEqual
(
[
op
.
type
for
op
in
opts
],
...
...
@@ -409,7 +409,7 @@ class TestDecayedAdagradOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
decayed_adagrad_optimizer
.
get_accumulators
()),
0
)
opts
=
decayed_adagrad_optimizer
.
create_optimization_pass
(
opts
=
decayed_adagrad_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
3
)
self
.
assertEqual
(
...
...
@@ -475,8 +475,8 @@ class TestFtrlOptimizer(unittest.TestCase):
params_grads
=
append_backward
(
mean_out
)
self
.
assertEqual
(
len
(
params_grads
),
1
)
self
.
assertEqual
(
len
(
ftrl_optimizer
.
get_accumulators
()),
0
)
opts
=
ftrl_optimizer
.
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
opts
=
ftrl_optimizer
.
_
create_optimization_pass
(
params_grads
,
mul_out
,
init_program
)
self
.
assertEqual
(
len
(
opts
),
3
)
self
.
assertEqual
([
op
.
type
for
op
in
opts
],
[
"fill_constant"
,
"elementwise_mul"
,
"ftrl"
])
...
...
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