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体验新版 GitCode,发现更多精彩内容 >>
提交
f96a344b
编写于
4月 02, 2019
作者:
Z
Zhen Wang
浏览文件
操作
浏览文件
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电子邮件补丁
差异文件
add checkpoint function for pass.
上级
9726da54
变更
3
隐藏空白更改
内联
并排
Showing
3 changed file
with
101 addition
and
12 deletion
+101
-12
fluid/PaddleSlim/quant_low_level_api/quant.py
fluid/PaddleSlim/quant_low_level_api/quant.py
+16
-5
fluid/PaddleSlim/quant_low_level_api/run_quant.sh
fluid/PaddleSlim/quant_low_level_api/run_quant.sh
+7
-7
fluid/PaddleSlim/utility.py
fluid/PaddleSlim/utility.py
+78
-0
未找到文件。
fluid/PaddleSlim/quant_low_level_api/quant.py
浏览文件 @
f96a344b
...
@@ -20,6 +20,7 @@ sys.path.append('..')
...
@@ -20,6 +20,7 @@ sys.path.append('..')
import
reader
import
reader
import
models
import
models
from
utility
import
add_arguments
,
print_arguments
from
utility
import
add_arguments
,
print_arguments
from
utility
import
save_persistable_nodes
,
load_persistable_nodes
parser
=
argparse
.
ArgumentParser
(
description
=
__doc__
)
parser
=
argparse
.
ArgumentParser
(
description
=
__doc__
)
add_arg
=
functools
.
partial
(
add_arguments
,
argparser
=
parser
)
add_arg
=
functools
.
partial
(
add_arguments
,
argparser
=
parser
)
...
@@ -31,7 +32,8 @@ add_arg('num_epochs', int, 120, "number of epochs.")
...
@@ -31,7 +32,8 @@ add_arg('num_epochs', int, 120, "number of epochs.")
add_arg
(
'class_dim'
,
int
,
1000
,
"Class number."
)
add_arg
(
'class_dim'
,
int
,
1000
,
"Class number."
)
add_arg
(
'image_shape'
,
str
,
"3,224,224"
,
"input image size"
)
add_arg
(
'image_shape'
,
str
,
"3,224,224"
,
"input image size"
)
add_arg
(
'model_save_dir'
,
str
,
"output"
,
"model save directory"
)
add_arg
(
'model_save_dir'
,
str
,
"output"
,
"model save directory"
)
add_arg
(
'pretrained_model'
,
str
,
None
,
"Whether to use pretrained model."
)
add_arg
(
'pretrained_fp32_model'
,
str
,
None
,
"Whether to use the pretrained float32 model to initialize the weights."
)
add_arg
(
'checkpoint'
,
str
,
None
,
"Whether to resume the training process from the checkpoint."
)
add_arg
(
'lr'
,
float
,
0.1
,
"set learning rate."
)
add_arg
(
'lr'
,
float
,
0.1
,
"set learning rate."
)
add_arg
(
'lr_strategy'
,
str
,
"piecewise_decay"
,
"Set the learning rate decay strategy."
)
add_arg
(
'lr_strategy'
,
str
,
"piecewise_decay"
,
"Set the learning rate decay strategy."
)
add_arg
(
'model'
,
str
,
"SE_ResNeXt50_32x4d"
,
"Set the network to use."
)
add_arg
(
'model'
,
str
,
"SE_ResNeXt50_32x4d"
,
"Set the network to use."
)
...
@@ -180,7 +182,8 @@ def build_program(is_train, main_prog, startup_prog, args):
...
@@ -180,7 +182,8 @@ def build_program(is_train, main_prog, startup_prog, args):
def
train
(
args
):
def
train
(
args
):
# parameters from arguments
# parameters from arguments
model_name
=
args
.
model
model_name
=
args
.
model
pretrained_model
=
args
.
pretrained_model
pretrained_fp32_model
=
args
.
pretrained_fp32_model
checkpoint
=
args
.
checkpoint
model_save_dir
=
args
.
model_save_dir
model_save_dir
=
args
.
model_save_dir
data_dir
=
args
.
data_dir
data_dir
=
args
.
data_dir
activation_quant_type
=
args
.
act_quant_type
activation_quant_type
=
args
.
act_quant_type
...
@@ -210,11 +213,11 @@ def train(args):
...
@@ -210,11 +213,11 @@ def train(args):
main_graph
=
IrGraph
(
core
.
Graph
(
train_prog
.
desc
),
for_test
=
False
)
main_graph
=
IrGraph
(
core
.
Graph
(
train_prog
.
desc
),
for_test
=
False
)
test_graph
=
IrGraph
(
core
.
Graph
(
test_prog
.
desc
),
for_test
=
True
)
test_graph
=
IrGraph
(
core
.
Graph
(
test_prog
.
desc
),
for_test
=
True
)
if
pretrained_model
:
if
pretrained_
fp32_
model
:
def
if_exist
(
var
):
def
if_exist
(
var
):
return
os
.
path
.
exists
(
os
.
path
.
join
(
pretrained_model
,
var
.
name
))
return
os
.
path
.
exists
(
os
.
path
.
join
(
pretrained_
fp32_
model
,
var
.
name
))
fluid
.
io
.
load_vars
(
fluid
.
io
.
load_vars
(
exe
,
pretrained_model
,
main_program
=
train_prog
,
predicate
=
if_exist
)
exe
,
pretrained_
fp32_
model
,
main_program
=
train_prog
,
predicate
=
if_exist
)
if
args
.
use_gpu
:
if
args
.
use_gpu
:
visible_device
=
os
.
getenv
(
'CUDA_VISIBLE_DEVICES'
)
visible_device
=
os
.
getenv
(
'CUDA_VISIBLE_DEVICES'
)
...
@@ -248,6 +251,9 @@ def train(args):
...
@@ -248,6 +251,9 @@ def train(args):
transform_pass
.
apply
(
main_graph
)
transform_pass
.
apply
(
main_graph
)
transform_pass
.
apply
(
test_graph
)
transform_pass
.
apply
(
test_graph
)
if
checkpoint
:
load_persistable_nodes
(
exe
,
checkpoint
,
main_graph
)
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
=
fluid
.
BuildStrategy
()
build_strategy
.
memory_optimize
=
False
build_strategy
.
memory_optimize
=
False
build_strategy
.
enable_inplace
=
False
build_strategy
.
enable_inplace
=
False
...
@@ -327,6 +333,11 @@ def train(args):
...
@@ -327,6 +333,11 @@ def train(args):
test_acc1
,
test_acc5
))
test_acc1
,
test_acc5
))
sys
.
stdout
.
flush
()
sys
.
stdout
.
flush
()
save_checkpoint_path
=
os
.
path
.
join
(
model_save_dir
,
model_name
,
str
(
pass_id
))
if
not
os
.
path
.
isdir
(
save_checkpoint_path
):
os
.
makedirs
(
save_checkpoint_path
)
save_persistable_nodes
(
exe
,
save_checkpoint_path
,
main_graph
)
model_path
=
os
.
path
.
join
(
model_save_dir
,
model_name
,
args
.
act_quant_type
)
model_path
=
os
.
path
.
join
(
model_save_dir
,
model_name
,
args
.
act_quant_type
)
float_path
=
os
.
path
.
join
(
model_path
,
'float'
)
float_path
=
os
.
path
.
join
(
model_path
,
'float'
)
int8_path
=
os
.
path
.
join
(
model_path
,
'int8'
)
int8_path
=
os
.
path
.
join
(
model_path
,
'int8'
)
...
...
fluid/PaddleSlim/quant_low_level_api/run_quant.sh
浏览文件 @
f96a344b
#!/usr/bin/env bash
#!/usr/bin/env bash
export
CUDA_VISIBLE_DEVICES
=
0
export
CUDA_VISIBLE_DEVICES
=
0
,1,2,3
#MobileNet v1:
#MobileNet v1:
python quant.py
\
python quant.py
\
--model
=
MobileNet
\
--model
=
MobileNet
\
--pretrained_model
=
../data/pretrain/MobileNetV1_pretrained
\
--pretrained_
fp32_
model
=
../data/pretrain/MobileNetV1_pretrained
\
--use_gpu
=
True
\
--use_gpu
=
True
\
--data_dir
=
../data/ILSVRC2012
\
--data_dir
=
../data/ILSVRC2012
\
--batch_size
=
64
\
--batch_size
=
256
\
--total_images
=
1281167
\
--total_images
=
1281167
\
--class_dim
=
1000
\
--class_dim
=
1000
\
--image_shape
=
3,224,224
\
--image_shape
=
3,224,224
\
--model_save_dir
=
output/
\
--model_save_dir
=
output/
\
--lr_strategy
=
piecewise_decay
\
--lr_strategy
=
piecewise_decay
\
--num_epochs
=
1
0
\
--num_epochs
=
2
0
\
--lr
=
0.0001
\
--lr
=
0.0001
\
--act_quant_type
=
abs_max
\
--act_quant_type
=
abs_max
\
--wt_quant_type
=
abs_max
--wt_quant_type
=
abs_max
...
@@ -23,16 +23,16 @@ python quant.py \
...
@@ -23,16 +23,16 @@ python quant.py \
#ResNet50:
#ResNet50:
#python quant.py \
#python quant.py \
# --model=ResNet50 \
# --model=ResNet50 \
# --pretrained_model=../data/pretrain/ResNet50_pretrained \
# --pretrained_
fp32_
model=../data/pretrain/ResNet50_pretrained \
# --use_gpu=True \
# --use_gpu=True \
# --data_dir=../data/ILSVRC2012 \
# --data_dir=../data/ILSVRC2012 \
# --batch_size=
32
\
# --batch_size=
128
\
# --total_images=1281167 \
# --total_images=1281167 \
# --class_dim=1000 \
# --class_dim=1000 \
# --image_shape=3,224,224 \
# --image_shape=3,224,224 \
# --model_save_dir=output/ \
# --model_save_dir=output/ \
# --lr_strategy=piecewise_decay \
# --lr_strategy=piecewise_decay \
# --num_epochs=
1
0 \
# --num_epochs=
2
0 \
# --lr=0.0001 \
# --lr=0.0001 \
# --act_quant_type=abs_max \
# --act_quant_type=abs_max \
# --wt_quant_type=abs_max
# --wt_quant_type=abs_max
...
...
fluid/PaddleSlim/utility.py
浏览文件 @
f96a344b
...
@@ -17,9 +17,12 @@ from __future__ import absolute_import
...
@@ -17,9 +17,12 @@ from __future__ import absolute_import
from
__future__
import
division
from
__future__
import
division
from
__future__
import
print_function
from
__future__
import
print_function
import
distutils.util
import
distutils.util
import
os
import
numpy
as
np
import
numpy
as
np
import
six
import
six
import
paddle.fluid
as
fluid
from
paddle.fluid
import
core
from
paddle.fluid
import
core
from
paddle.fluid.framework
import
Program
def
print_arguments
(
args
):
def
print_arguments
(
args
):
...
@@ -61,3 +64,78 @@ def add_arguments(argname, type, default, help, argparser, **kwargs):
...
@@ -61,3 +64,78 @@ def add_arguments(argname, type, default, help, argparser, **kwargs):
type
=
type
,
type
=
type
,
help
=
help
+
' Default: %(default)s.'
,
help
=
help
+
' Default: %(default)s.'
,
**
kwargs
)
**
kwargs
)
def
save_persistable_nodes
(
executor
,
dirname
,
graph
):
"""
Save persistable nodes to the given directory by the executor.
Args:
executor(Executor): The executor to run for saving node values.
dirname(str): The directory path.
graph(IrGraph): All the required persistable nodes in the graph will be saved.
"""
persistable_node_names
=
set
()
persistable_nodes
=
[]
all_persistable_nodes
=
graph
.
all_persistable_nodes
()
for
node
in
all_persistable_nodes
:
name
=
node
.
name
()
if
name
not
in
persistable_node_names
:
persistable_node_names
.
add
(
name
)
persistable_nodes
.
append
(
node
)
program
=
Program
()
var_list
=
[]
for
node
in
persistable_nodes
:
var_desc
=
node
.
var
()
if
var_desc
.
type
()
==
core
.
VarDesc
.
VarType
.
RAW
or
\
var_desc
.
type
()
==
core
.
VarDesc
.
VarType
.
READER
:
continue
var
=
program
.
global_block
().
create_var
(
name
=
var_desc
.
name
(),
shape
=
var_desc
.
shape
(),
dtype
=
var_desc
.
dtype
(),
type
=
var_desc
.
type
(),
lod_level
=
var_desc
.
lod_level
(),
persistable
=
var_desc
.
persistable
())
var_list
.
append
(
var
)
fluid
.
io
.
save_vars
(
executor
=
executor
,
dirname
=
dirname
,
vars
=
var_list
)
def
load_persistable_nodes
(
executor
,
dirname
,
graph
):
"""
Load persistable node values from the given directory by the executor.
Args:
executor(Executor): The executor to run for loading node values.
dirname(str): The directory path.
graph(IrGraph): All the required persistable nodes in the graph will be loaded.
"""
persistable_node_names
=
set
()
persistable_nodes
=
[]
all_persistable_nodes
=
graph
.
all_persistable_nodes
()
for
node
in
all_persistable_nodes
:
name
=
node
.
name
()
if
name
not
in
persistable_node_names
:
persistable_node_names
.
add
(
name
)
persistable_nodes
.
append
(
node
)
program
=
Program
()
var_list
=
[]
def
_exist
(
var
):
return
os
.
path
.
exists
(
os
.
path
.
join
(
dirname
,
var
.
name
))
for
node
in
persistable_nodes
:
var_desc
=
node
.
var
()
if
var_desc
.
type
()
==
core
.
VarDesc
.
VarType
.
RAW
or
\
var_desc
.
type
()
==
core
.
VarDesc
.
VarType
.
READER
:
continue
var
=
program
.
global_block
().
create_var
(
name
=
var_desc
.
name
(),
shape
=
var_desc
.
shape
(),
dtype
=
var_desc
.
dtype
(),
type
=
var_desc
.
type
(),
lod_level
=
var_desc
.
lod_level
(),
persistable
=
var_desc
.
persistable
())
if
_exist
(
var
):
var_list
.
append
(
var
)
fluid
.
io
.
load_vars
(
executor
=
executor
,
dirname
=
dirname
,
vars
=
var_list
)
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