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体验新版 GitCode,发现更多精彩内容 >>
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2b4ef509
编写于
6月 28, 2019
作者:
J
Jie Fang
提交者:
Yibing Liu
6月 28, 2019
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差异文件
init custom black white list (#18377)
test=develop
上级
b9630799
变更
5
隐藏空白更改
内联
并排
Showing
5 changed file
with
63 addition
and
14 deletion
+63
-14
paddle/fluid/API.spec
paddle/fluid/API.spec
+2
-1
python/paddle/fluid/contrib/mixed_precision/__init__.py
python/paddle/fluid/contrib/mixed_precision/__init__.py
+2
-0
python/paddle/fluid/contrib/mixed_precision/decorator.py
python/paddle/fluid/contrib/mixed_precision/decorator.py
+12
-6
python/paddle/fluid/contrib/mixed_precision/fp16_lists.py
python/paddle/fluid/contrib/mixed_precision/fp16_lists.py
+41
-0
python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
+6
-7
未找到文件。
paddle/fluid/API.spec
浏览文件 @
2b4ef509
...
...
@@ -426,7 +426,8 @@ paddle.fluid.contrib.HDFSClient.upload (ArgSpec(args=['self', 'hdfs_path', 'loca
paddle.fluid.contrib.multi_download (ArgSpec(args=['client', 'hdfs_path', 'local_path', 'trainer_id', 'trainers', 'multi_processes'], varargs=None, keywords=None, defaults=(5,)), ('document', '100927be598ed8f9eaa1f3ef1b23568a'))
paddle.fluid.contrib.multi_upload (ArgSpec(args=['client', 'hdfs_path', 'local_path', 'multi_processes', 'overwrite', 'sync'], varargs=None, keywords=None, defaults=(5, False, True)), ('document', '183f34c83d30dbe16e09e8716c41958a'))
paddle.fluid.contrib.extend_with_decoupled_weight_decay (ArgSpec(args=['base_optimizer'], varargs=None, keywords=None, defaults=None), ('document', 'a1095dfd4ec725747f662d69cd7659d4'))
paddle.fluid.contrib.mixed_precision.decorate (ArgSpec(args=['optimizer', 'init_loss_scaling', 'incr_every_n_steps', 'decr_every_n_nan_or_inf', 'incr_ratio', 'decr_ratio', 'use_dynamic_loss_scaling'], varargs=None, keywords=None, defaults=(1.0, 1000, 2, 2.0, 0.8, False)), ('document', 'bdb8f9dbb0d94b3957272c53eeee9818'))
paddle.fluid.contrib.mixed_precision.decorate (ArgSpec(args=['optimizer', 'amp_lists', 'init_loss_scaling', 'incr_every_n_steps', 'decr_every_n_nan_or_inf', 'incr_ratio', 'decr_ratio', 'use_dynamic_loss_scaling'], varargs=None, keywords=None, defaults=(None, 1.0, 1000, 2, 2.0, 0.8, False)), ('document', 'd05e71f5b0bd6d92bb94e70e00b3f9cf'))
paddle.fluid.contrib.mixed_precision.AutoMixedPrecisionLists.__init__ (ArgSpec(args=['self', 'custom_white_list', 'custom_black_list'], varargs=None, keywords=None, defaults=(None, None)), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.contrib.fused_elemwise_activation (ArgSpec(args=['x', 'y', 'functor_list', 'axis', 'scale', 'save_intermediate_out'], varargs=None, keywords=None, defaults=(-1, 0.0, True)), ('document', '1c4b247a2858cea8d9d8750693688270'))
paddle.fluid.contrib.BasicGRUUnit.__init__ (ArgSpec(args=['self', 'name_scope', 'hidden_size', 'param_attr', 'bias_attr', 'gate_activation', 'activation', 'dtype'], varargs=None, keywords=None, defaults=(None, None, None, None, 'float32')), ('document', '6adf97f83acf6453d4a6a4b1070f3754'))
paddle.fluid.contrib.BasicGRUUnit.add_parameter (ArgSpec(args=['self', 'name', 'parameter'], varargs=None, keywords=None, defaults=None), ('document', 'f35ab374c7d5165c3daf3bd64a5a2ec1'))
...
...
python/paddle/fluid/contrib/mixed_precision/__init__.py
浏览文件 @
2b4ef509
...
...
@@ -15,5 +15,7 @@
from
__future__
import
print_function
from
.
import
decorator
from
.decorator
import
*
from
.fp16_lists
import
AutoMixedPrecisionLists
__all__
=
decorator
.
__all__
__all__
+=
fp16_lists
.
__all__
python/paddle/fluid/contrib/mixed_precision/decorator.py
浏览文件 @
2b4ef509
...
...
@@ -19,6 +19,7 @@ from ... import unique_name
from
.
import
fp16_utils
from
.fp16_utils
import
create_master_params_grads
,
master_param_to_train_param
from
.fp16_utils
import
update_loss_scaling
,
rewrite_program
from
.fp16_lists
import
AutoMixedPrecisionLists
__all__
=
[
"decorate"
]
...
...
@@ -34,6 +35,7 @@ class OptimizerWithMixedPrecison(object):
Args:
optimizer (Optimizer): A common Optimizer object.
amp_lists (AutoMixedPrecisionLists): An AutoMixedPrecisionLists object.
init_loss_scaling (float): The initial loss scaling factor.
use_dynamic_loss_scaling (bool): Whether to use dynamic loss scaling.
incr_every_n_steps(int): Increases loss scaling every n consecutive
...
...
@@ -48,10 +50,11 @@ class OptimizerWithMixedPrecison(object):
"""
def
__init__
(
self
,
optimizer
,
init_loss_scaling
,
use_dynamic
_loss_scaling
,
incr_every_n_steps
,
decr_every_n_nan_or_inf
,
incr_ratio
,
decr_ratio
):
def
__init__
(
self
,
optimizer
,
amp_lists
,
init
_loss_scaling
,
use_dynamic_loss_scaling
,
incr_every_n_steps
,
decr_
every_n_nan_or_inf
,
incr_ratio
,
decr_
ratio
):
self
.
_optimizer
=
optimizer
self
.
_amp_lists
=
amp_lists
self
.
_param_grads
=
None
self
.
_train_program
=
default_main_program
()
self
.
_startup_prog
=
default_startup_program
()
...
...
@@ -120,7 +123,7 @@ class OptimizerWithMixedPrecison(object):
A list of (param, grad), which is a tuple of a parameter and its
gradient respectively, and the scaled loss.
"""
rewrite_program
(
self
.
_train_program
)
rewrite_program
(
self
.
_train_program
,
self
.
_amp_lists
)
scaled_loss
=
loss
*
self
.
_loss_scaling
self
.
_param_grads
=
self
.
_optimizer
.
backward
(
scaled_loss
,
startup_program
,
parameter_list
,
no_grad_set
,
...
...
@@ -189,6 +192,7 @@ class OptimizerWithMixedPrecison(object):
def
decorate
(
optimizer
,
amp_lists
=
None
,
init_loss_scaling
=
1.0
,
incr_every_n_steps
=
1000
,
decr_every_n_nan_or_inf
=
2
,
...
...
@@ -200,6 +204,7 @@ def decorate(optimizer,
Args:
optimizer(Optimizer): A common Optimizer.
amp_lists (AutoMixedPrecisionLists): An AutoMixedPrecisionLists object.
init_loss_scaling(float): The initial loss scaling factor.
incr_every_n_steps(int): Increases loss scaling every n consecutive
steps with finite gradients.
...
...
@@ -227,9 +232,10 @@ def decorate(optimizer,
scaled_loss, _, _ = mp_optimizer.minimize(loss)
"""
if
amp_lists
is
None
:
amp_lists
=
AutoMixedPrecisionLists
()
mp_optimizer
=
OptimizerWithMixedPrecison
(
optimizer
,
init_loss_scaling
,
use_dynamic_loss_scaling
,
optimizer
,
amp_lists
,
init_loss_scaling
,
use_dynamic_loss_scaling
,
incr_every_n_steps
,
decr_every_n_nan_or_inf
,
incr_ratio
,
decr_ratio
)
return
mp_optimizer
python/paddle/fluid/contrib/mixed_precision/fp16_lists.py
浏览文件 @
2b4ef509
...
...
@@ -12,6 +12,47 @@
# See the License for the specific language governing permissions and
# limitations under the License.
import
copy
__all__
=
[
"AutoMixedPrecisionLists"
]
class
AutoMixedPrecisionLists
(
object
):
"""
AutoMixedPrecisionLists is a class for black/white list. It can update
pre-defined black list and white list according to users' custom black
white lists. The lists are used for an algorithm which determines op's
exectuion mode (fp32 or fp16).
Args:
custom_white_list (set): Users' custom white list.
custom_black_list (set): Users' custom black list.
"""
def
__init__
(
self
,
custom_white_list
=
None
,
custom_black_list
=
None
):
self
.
_custom_white_list
=
custom_white_list
self
.
_custom_black_list
=
custom_black_list
self
.
white_list
=
copy
.
copy
(
white_list
)
self
.
black_list
=
copy
.
copy
(
black_list
)
self
.
gray_list
=
copy
.
copy
(
gray_list
)
self
.
_update_list
()
def
_update_list
(
self
):
"""
Update black and white list according to users' custom list.
"""
if
self
.
_custom_white_list
:
for
op_name
in
self
.
_custom_white_list
:
if
op_name
in
self
.
black_list
:
self
.
black_list
.
remove
(
op_name
)
self
.
white_list
.
add
(
op_name
)
if
self
.
_custom_black_list
:
for
op_name
in
self
.
_custom_black_list
:
if
op_name
in
self
.
white_list
:
self
.
white_list
.
remove
(
op_name
)
self
.
black_list
.
add
(
op_name
)
# The three sets listed below are changed dynamiclly. They don't contain all
# paddle ops currently.
...
...
python/paddle/fluid/contrib/mixed_precision/fp16_utils.py
浏览文件 @
2b4ef509
...
...
@@ -17,7 +17,6 @@ from __future__ import print_function
from
...
import
core
from
...
import
layers
from
...
import
framework
from
.fp16_lists
import
black_list
,
white_list
,
gray_list
def
append_cast_op
(
i
,
o
,
prog
):
...
...
@@ -218,7 +217,7 @@ def find_true_prev_op(ops, var_name):
return
op
def
rewrite_program
(
main_prog
):
def
rewrite_program
(
main_prog
,
amp_lists
):
"""
Traverse all ops in current block and insert cast op according to
which set current op belongs to.
...
...
@@ -244,11 +243,11 @@ def rewrite_program(main_prog):
black_op_set
=
set
()
for
i
in
range
(
len
(
ops
)):
op
=
ops
[
i
]
if
op
.
type
in
black_list
:
if
op
.
type
in
amp_lists
.
black_list
:
black_op_set
.
add
(
op
)
elif
op
.
type
in
white_list
:
elif
op
.
type
in
amp_lists
.
white_list
:
white_op_set
.
add
(
op
)
elif
op
.
type
in
op
.
type
in
gray_list
:
elif
op
.
type
in
amp_lists
.
gray_list
:
is_black_op
=
False
is_white_op
=
False
for
in_name
in
op
.
input_names
:
...
...
@@ -265,10 +264,10 @@ def rewrite_program(main_prog):
prev_op
=
in_var
.
op
# if it's one of inputs
if
prev_op
in
black_op_set
or
\
prev_op
.
type
in
black_list
:
prev_op
.
type
in
amp_lists
.
black_list
:
is_black_op
=
True
if
prev_op
in
white_op_set
or
\
prev_op
.
type
in
white_list
:
prev_op
.
type
in
amp_lists
.
white_list
:
is_white_op
=
True
if
is_black_op
:
black_op_set
.
add
(
op
)
...
...
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