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fdaf0772
编写于
10月 20, 2017
作者:
K
Kexin Zhao
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差异文件
add adagrad optimizer python implementation
上级
0e31d7d7
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
99 addition
and
1 deletion
+99
-1
python/paddle/v2/framework/optimizer.py
python/paddle/v2/framework/optimizer.py
+58
-1
python/paddle/v2/framework/tests/test_optimizer.py
python/paddle/v2/framework/tests/test_optimizer.py
+41
-0
未找到文件。
python/paddle/v2/framework/optimizer.py
浏览文件 @
fdaf0772
import
paddle.v2.framework.framework
as
framework
from
collections
import
defaultdict
__all__
=
[
'SGDOptimizer'
,
'MomentumOptimizer'
]
__all__
=
[
'SGDOptimizer'
,
'MomentumOptimizer'
,
'AdagradOptimizer'
]
class
Optimizer
(
object
):
...
...
@@ -272,3 +272,60 @@ class MomentumOptimizer(Optimizer):
attrs
=
{
"mu"
:
self
.
_momentum
})
return
momentum_op
class
AdagradOptimizer
(
Optimizer
):
"""Simple Adagrad optimizer with moment state
"""
_moment_acc_str
=
"moment"
def
__init__
(
self
,
learning_rate
,
epsilon
):
assert
learning_rate
is
not
None
assert
epsilon
is
not
None
super
(
AdagradOptimizer
,
self
).
__init__
()
self
.
type
=
"adagrad"
self
.
_learning_rate
=
learning_rate
self
.
_epsilon
=
epsilon
def
_initialize_tensors
(
self
,
block
):
assert
isinstance
(
block
,
framework
.
Block
)
lr_shape
=
[
1
]
# create a variable for learning_rate
self
.
_lr
=
block
.
create_var
(
dtype
=
"float32"
,
shape
=
lr_shape
,
lod_level
=
0
)
# create an op to init the learning_rate
# FIXME: Fix when Initialization design has been implemented
# https://github.com/PaddlePaddle/Paddle/pull/4852
block
.
append_op
(
type
=
"fill_constant"
,
outputs
=
{
"Out"
:
self
.
_lr
},
attrs
=
{
"shape"
:
lr_shape
,
"value"
:
self
.
_learning_rate
})
def
_create_accumulators
(
self
,
block
,
parameters
):
assert
isinstance
(
block
,
framework
.
Block
)
for
p
in
parameters
:
self
.
_add_accumulator
(
block
,
self
.
_moment_acc_str
,
p
,
'float32'
)
def
_append_optimize_op
(
self
,
block
,
param_and_grad
):
assert
isinstance
(
block
,
framework
.
Block
)
moment_acc
=
self
.
_get_accumulator
(
self
.
_moment_acc_str
,
param_and_grad
[
0
])
# create the adagrad optimizer op
adagrad_op
=
block
.
append_op
(
type
=
self
.
type
,
inputs
=
{
"Param"
:
param_and_grad
[
0
],
"Grad"
:
param_and_grad
[
1
],
"Moment"
:
moment_acc
,
"LearningRate"
:
self
.
_lr
},
outputs
=
{
"ParamOut"
:
param_and_grad
[
0
],
"MomentOut"
:
moment_acc
},
attrs
=
{
"epsilon"
:
self
.
_epsilon
})
return
adagrad_op
python/paddle/v2/framework/tests/test_optimizer.py
浏览文件 @
fdaf0772
...
...
@@ -69,5 +69,46 @@ class TestMomentumOptimizer(unittest.TestCase):
self
.
assertTrue
(
mul_x
.
name
in
velocity_acc
)
class
TestAdagradOptimizer
(
unittest
.
TestCase
):
class
MockAdagrad
(
optimizer
.
AdagradOptimizer
):
def
get_accumulators
(
self
):
return
self
.
_accumulators
def
get_moment_str
(
self
):
return
self
.
_moment_acc_str
def
test_adagrad_optimizer
(
self
):
program
=
framework
.
Program
()
block
=
program
.
global_block
()
mul_x
=
block
.
create_parameter
(
dtype
=
"float32"
,
shape
=
[
5
,
10
],
lod_level
=
0
,
name
=
"mul.x"
)
mul_y
=
block
.
create_var
(
dtype
=
"float32"
,
shape
=
[
10
,
8
],
lod_level
=
0
,
name
=
"mul.y"
)
mul_out
=
block
.
create_var
(
dtype
=
"float32"
,
shape
=
[
5
,
8
],
lod_level
=
0
,
name
=
"mul.out"
)
block
.
append_op
(
type
=
"mul"
,
inputs
=
{
"X"
:
mul_x
,
"Y"
:
mul_y
},
outputs
=
{
"Out"
:
mul_out
},
attrs
=
{
"x_num_col_dims"
:
1
})
adagrad_optimizer
=
self
.
MockAdagrad
(
learning_rate
=
0.01
,
epsilon
=
1.0e-6
)
params_grads
=
adagrad_optimizer
.
create_backward_pass
(
mul_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
)
self
.
assertEqual
(
len
(
opts
),
1
)
adagrad_op
=
opts
[
0
]
self
.
assertEqual
(
adagrad_op
.
type
,
"adagrad"
)
# check accumulators
accumulators
=
adagrad_optimizer
.
get_accumulators
()
self
.
assertEqual
(
len
(
accumulators
),
1
)
self
.
assertTrue
(
adagrad_optimizer
.
get_moment_str
()
in
accumulators
)
moment_acc
=
accumulators
[
adagrad_optimizer
.
get_moment_str
()]
self
.
assertEqual
(
len
(
moment_acc
),
1
)
self
.
assertTrue
(
mul_x
.
name
in
moment_acc
)
if
__name__
==
'__main__'
:
unittest
.
main
()
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