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55edfca2
编写于
11月 08, 2018
作者:
Q
Qiao Longfei
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revert unused change
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1 changed file
with
15 addition
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17 deletion
+15
-17
python/paddle/fluid/optimizer.py
python/paddle/fluid/optimizer.py
+15
-17
未找到文件。
python/paddle/fluid/optimizer.py
浏览文件 @
55edfca2
...
@@ -292,28 +292,26 @@ class Optimizer(object):
...
@@ -292,28 +292,26 @@ class Optimizer(object):
This method combines interface `append_backward()` and
This method combines interface `append_backward()` and
`create_optimization_pass()` into one.
`create_optimization_pass()` into one.
"""
"""
with
program_guard
(
loss
.
block
.
program
,
startup_program
):
params_grads
=
append_backward
(
loss
,
parameter_list
,
no_grad_set
,
[
error_clip_callback
])
params_grads
=
append_backward
(
loss
,
parameter_list
,
no_grad_set
,
params_grads
=
sorted
(
params_grads
,
key
=
lambda
x
:
x
[
0
].
name
)
[
error_clip_callback
])
params_grads
=
sorted
(
params_grads
,
key
=
lambda
x
:
x
[
0
].
name
)
params_grads
,
table_param_and_grad
,
table_optimize_op
=
\
self
.
_process_distribute_lookuptable
(
params_grads
,
loss
,
startup_program
)
params_grads
,
table_param_and_grad
,
table_optimize_op
=
\
params_grads
=
append_gradient_clip_ops
(
params_grads
)
self
.
_process_distribute_lookuptable
(
params_grads
,
loss
,
startup_program
)
params_grads
=
append_gradient_clip_ops
(
params_grads
)
# Add regularization if any
params_grads
=
append_regularization_ops
(
params_grads
,
self
.
regularization
)
# Add regularization if any
optimize_ops
=
self
.
_create_optimization_pass
(
params_grads
,
loss
,
params_grads
=
append_regularization_ops
(
params_grads
,
startup_program
)
self
.
regularization
)
if
table_optimize_op
is
not
None
:
optimize_ops
.
append
(
table_optimize_op
)
optimize_ops
=
self
.
_create_optimization_pass
(
params_grads
,
loss
,
params_grads
.
append
(
table_param_and_grad
)
startup_program
)
return
optimize_ops
,
params_grads
if
table_optimize_op
is
not
None
:
optimize_ops
.
append
(
table_optimize_op
)
params_grads
.
append
(
table_param_and_grad
)
return
optimize_ops
,
params_grads
class
SGDOptimizer
(
Optimizer
):
class
SGDOptimizer
(
Optimizer
):
...
...
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