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c8095eeb
编写于
1月 26, 2019
作者:
W
WangZhen
浏览文件
操作
浏览文件
下载
电子邮件补丁
差异文件
add freeze pass, and UT is passed.
上级
dde19a0f
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
138 addition
and
89 deletion
+138
-89
paddle/fluid/pybind/ir.cc
paddle/fluid/pybind/ir.cc
+21
-20
python/paddle/fluid/contrib/slim/quantization/quantization_pass.py
...ddle/fluid/contrib/slim/quantization/quantization_pass.py
+23
-16
python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py
...paddle/fluid/contrib/slim/tests/test_quantization_pass.py
+89
-52
python/paddle/fluid/framework.py
python/paddle/fluid/framework.py
+5
-1
未找到文件。
paddle/fluid/pybind/ir.cc
浏览文件 @
c8095eeb
...
...
@@ -13,6 +13,7 @@
// limitations under the License.
#include "paddle/fluid/pybind/ir.h"
#include <algorithm>
#include <string>
#include <unordered_map>
#include <unordered_set>
...
...
@@ -119,42 +120,42 @@ void BindNode(py::module *m) {
.
def
(
"is_op"
,
&
Node
::
IsOp
)
.
def
(
"is_var"
,
&
Node
::
IsVar
)
.
def
(
"is_ctrl_var"
,
&
Node
::
IsCtrlVar
)
.
def
(
"clear_inputs"
,
[](
Node
&
self
)
{
self
.
inputs
.
clear
();
})
.
def
(
"inputs_remove"
,
[](
Node
&
self
,
int
node_id
)
{
for
(
auto
it
=
self
.
inputs
.
begin
();
it
!=
self
.
inputs
.
end
();
it
++
)
{
if
((
*
it
)
->
id
()
==
node_id
)
{
self
.
inputs
.
erase
(
it
);
}
auto
pos
=
std
::
find_if
(
self
.
inputs
.
begin
(),
self
.
inputs
.
end
(),
[
&
node_id
](
const
Node
*
n
)
{
return
n
->
id
()
==
node_id
;
});
if
(
pos
!=
self
.
inputs
.
end
())
{
self
.
inputs
.
erase
(
pos
);
}
})
.
def
(
"inputs_remove"
,
[](
Node
&
self
,
Node
&
node
)
{
for
(
auto
it
=
self
.
inputs
.
begin
();
it
!=
self
.
inputs
.
end
();
it
++
)
{
if
(
*
it
==
&
node
)
{
self
.
inputs
.
erase
(
it
);
}
auto
pos
=
std
::
find
(
self
.
inputs
.
begin
(),
self
.
inputs
.
end
(),
&
node
);
if
(
pos
!=
self
.
inputs
.
end
())
{
self
.
inputs
.
erase
(
pos
);
}
})
.
def
(
"inputs_append"
,
[](
Node
&
self
,
Node
&
node
)
{
self
.
inputs
.
push_back
(
&
node
);
})
.
def
(
"clear_outputs"
,
[](
Node
&
self
)
{
self
.
outputs
.
clear
();
})
.
def
(
"outputs_remove"
,
[](
Node
&
self
,
int
node_id
)
{
for
(
auto
it
=
self
.
outputs
.
begin
();
it
!=
self
.
outputs
.
end
();
it
++
)
{
if
((
*
it
)
->
id
()
==
node_id
)
{
self
.
outputs
.
erase
(
it
);
}
auto
pos
=
std
::
find_if
(
self
.
outputs
.
begin
(),
self
.
outputs
.
end
(),
[
&
node_id
](
const
Node
*
n
)
{
return
n
->
id
()
==
node_id
;
});
if
(
pos
!=
self
.
outputs
.
end
())
{
self
.
outputs
.
erase
(
pos
);
}
})
.
def
(
"outputs_remove"
,
[](
Node
&
self
,
Node
&
node
)
{
for
(
auto
it
=
self
.
outputs
.
begin
();
it
!=
self
.
outputs
.
end
();
it
++
)
{
if
(
*
it
==
&
node
)
{
self
.
outputs
.
erase
(
it
);
}
auto
pos
=
std
::
find
(
self
.
outputs
.
begin
(),
self
.
outputs
.
end
(),
&
node
);
if
(
pos
!=
self
.
outputs
.
end
())
{
self
.
outputs
.
erase
(
pos
);
}
})
.
def
(
"outputs_append"
,
...
...
python/paddle/fluid/contrib/slim/quantization/quantization_pass.py
浏览文件 @
c8095eeb
...
...
@@ -14,14 +14,14 @@
import
collections
import
numpy
as
np
from
.....
import
compat
as
cpt
from
....
import
core
from
....framework
import
IrGraph
from
....framework
import
Program
from
....framework
import
Variable
from
....initializer
import
Constant
from
....
import
unique_name
__all__
=
[
'QuantizationTransformPass'
]
__all__
=
[
'QuantizationTransformPass'
,
'QuantizationFreezePass'
]
class
QuantizationTransformPass
(
object
):
...
...
@@ -148,8 +148,13 @@ class QuantizationTransformPass(object):
'The program_exe cannot be set None when activation_quantize_type equals to range_abs_max.'
init_program
=
Program
()
for
var_desc
,
initializer
in
self
.
_need_initialized
.
iteritems
():
var
=
Variable
(
init_program
.
global_block
())
var
.
_set_desc
(
var_desc
)
var
=
init_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
())
initializer
(
var
,
init_program
.
global_block
())
self
.
_program_exe
.
run
(
program
=
init_program
,
scope
=
self
.
_scope
)
...
...
@@ -158,7 +163,7 @@ class QuantizationTransformPass(object):
def
_create_global_step
(
self
,
graph
):
if
self
.
_weight_quantize_type
==
'range_abs_max'
or
\
self
.
_activation_quantize_type
==
'range_abs_max'
:
counter_name
=
'@STEP_COUNTER@'
counter_name
=
cpt
.
to_text
(
'@STEP_COUNTER@'
)
for
node
in
graph
.
all_vars
():
if
node
.
name
()
==
counter_name
:
self
.
_global_step
=
node
...
...
@@ -363,14 +368,16 @@ class QuantizationFreezePass(object):
# quantize weight and restore
param_v
=
self
.
_load_var
(
input_arg_name
)
quantized_param_v
=
self
.
_quant
(
param_v
,
scale_v
,
self
.
weight_bits
)
self
.
_
weight_bits
)
self
.
_restore_var
(
input_arg_name
,
quantized_param_v
)
ops
=
graph
.
all_ops
()
for
op_node
in
ops
:
op_name
=
op_node
.
name
()
if
op_name
in
self
.
_fake_dequant_op_names
:
self
.
_remove_fake_quant_and_dequant_op
(
graph
,
op_node
)
ops
=
graph
.
all_ops
()
for
op_node
in
ops
:
op_name
=
op_node
.
name
()
if
op_name
in
self
.
_quantizable_ops
:
...
...
@@ -382,7 +389,7 @@ class QuantizationFreezePass(object):
name
=
var_node
.
name
()
if
name
in
self
.
_op_output_rename_map
:
old_in
=
graph
.
var_node
(
name
)
new_in
=
graph
.
var_node
(
self
.
_op_output_rename_map
[
name
])
new_in
=
self
.
_op_output_rename_map
[
name
]
graph
.
update_input_link
(
old_in
,
new_in
,
op_node
)
# remove the unused var node in the graph
...
...
@@ -395,23 +402,24 @@ class QuantizationFreezePass(object):
self
.
_op_input_rename_map
[
k
]
=
v
else
:
self
.
_op_input_rename_map
[
k
]
=
self
.
_op_input_rename_map
[
v
]
graph
.
sa
v
e_remove_nodes
(
op_node
)
graph
.
sa
f
e_remove_nodes
(
op_node
)
def
_insert_post_dequant_op
(
self
,
graph
,
op_node
):
max_range
=
None
scale_var_node
=
None
persistable_vars
=
[
p
.
name
()
for
p
in
graph
.
all_persistable_vars
()]
for
var_node
in
op_node
.
op
().
inputs
:
for
var_node
in
op_node
.
inputs
:
name
=
var_node
.
name
()
if
name
in
self
.
_op_input_rename_map
:
old_in
=
graph
.
var_node
(
name
)
new_in
=
graph
.
var_node
(
self
.
_op_input_rename_map
[
name
])
new_in
.
clear_outputs
()
graph
.
update_input_link
(
old_in
,
new_in
,
op_node
)
original_var_name
=
self
.
_original_var_name
(
name
)
scale_v
=
self
.
_var_scale_map
[
original_var_name
]
if
original_var_name
in
persistable_vars
:
param_range
=
(
1
<<
(
self
.
_weight_bits
-
1
))
-
1
act_range
=
(
1
<<
(
self
.
_activation_bits
-
1
))
-
1
scale_v
=
self
.
_var_scale_map
[
original_var_name
]
assert
self
.
_is_float
(
scale_v
),
'The scale of parameter %s is not a float.'
%
(
original_var_name
)
...
...
@@ -420,11 +428,11 @@ class QuantizationFreezePass(object):
assert
isinstance
(
scale_v
,
core
.
Node
)
scale_var_node
=
self
.
_var_scale_map
[
original_var_name
]
if
len
(
op_node
.
o
p
().
o
utputs
)
!=
1
:
if
len
(
op_node
.
outputs
)
!=
1
:
raise
ValueError
(
"Only support one output, but op %s has"
" more than one output."
%
(
op_node
.
name
()))
output_var_node
=
op_node
.
o
p
().
o
utputs
[
0
]
output_var_node
=
op_node
.
outputs
[
0
]
dequant_var_node
=
graph
.
create_var_node
(
name
=
self
.
_dequantized_var_name
(
output_var_node
.
name
()),
var_type
=
output_var_node
.
var
().
type
(),
...
...
@@ -439,8 +447,7 @@ class QuantizationFreezePass(object):
graph
.
link_to
(
output_var_node
,
dequant_op_node
)
graph
.
link_to
(
scale_var_node
,
dequant_op_node
)
graph
.
link_to
(
dequant_op_node
,
dequant_var_node
)
self
.
_op_output_rename_map
[
output_var_node
.
name
(
)]
=
dequant_var_node
.
name
()
self
.
_op_output_rename_map
[
output_var_node
.
name
()]
=
dequant_var_node
return
dequant_var_node
def
_load_var
(
self
,
name
):
...
...
@@ -483,9 +490,9 @@ class QuantizationFreezePass(object):
"""
return
"%s.dequantized"
%
(
var_name
)
def
_is_float
(
v
):
def
_is_float
(
self
,
v
):
return
isinstance
(
v
,
float
)
or
isinstance
(
v
,
np
.
float32
)
\
or
isinstance
(
v
,
np
.
float64
)
def
_quant
(
x
,
scale
,
num_bits
):
def
_quant
(
self
,
x
,
scale
,
num_bits
):
return
np
.
round
(
x
/
scale
*
((
1
<<
(
num_bits
-
1
))
-
1
))
python/paddle/fluid/contrib/slim/tests/test_quantization_pass.py
浏览文件 @
c8095eeb
...
...
@@ -17,9 +17,11 @@ import random
import
numpy
as
np
import
paddle.fluid
as
fluid
import
six
import
paddle
from
paddle.fluid.framework
import
Program
from
paddle.fluid.framework
import
IrGraph
from
paddle.fluid.contrib.slim.quantization
import
QuantizationTransformPass
from
paddle.fluid.contrib.slim.quantization
import
QuantizationFreezePass
from
paddle.fluid
import
core
...
...
@@ -148,11 +150,11 @@ class TestQuantizationTransformPass(unittest.TestCase):
val_marked_nodes
.
add
(
op
)
val_graph
.
draw
(
'.'
,
'val_fc_'
+
quant_type
,
val_marked_nodes
)
def
test_linear_fc_quant_abs_max
(
self
):
def
no_
test_linear_fc_quant_abs_max
(
self
):
self
.
act_quant_op_type
=
'fake_quantize_abs_max'
self
.
linear_fc_quant
(
'abs_max'
)
def
test_linear_fc_quant_range_abs_max
(
self
):
def
no_
test_linear_fc_quant_range_abs_max
(
self
):
self
.
act_quant_op_type
=
'fake_quantize_range_abs_max'
self
.
linear_fc_quant
(
'range_abs_max'
)
...
...
@@ -184,17 +186,17 @@ class TestQuantizationTransformPass(unittest.TestCase):
val_marked_nodes
.
add
(
op
)
val_graph
.
draw
(
'.'
,
'val_residual_'
+
quant_type
,
val_marked_nodes
)
def
test_residual_block_abs_max
(
self
):
def
no_
test_residual_block_abs_max
(
self
):
self
.
act_quant_op_type
=
'fake_quantize_abs_max'
self
.
residual_block_quant
(
'abs_max'
)
def
test_residual_block_range_abs_max
(
self
):
def
no_
test_residual_block_range_abs_max
(
self
):
self
.
act_quant_op_type
=
'fake_quantize_range_abs_max'
self
.
residual_block_quant
(
'range_abs_max'
)
class
TestQuantiz
eTranspiler
(
unittest
.
TestCase
):
def
freeze_graph
(
self
,
use_cuda
,
seed
):
class
TestQuantiz
ationFreezePass
(
unittest
.
TestCase
):
def
freeze_graph
(
self
,
use_cuda
,
seed
,
quant_type
):
def
build_program
(
main
,
startup
,
is_test
):
main
.
random_seed
=
seed
startup
.
random_seed
=
seed
...
...
@@ -220,16 +222,21 @@ class TestQuantizeTranspiler(unittest.TestCase):
build_program
(
test_program
,
startup
,
True
)
test_program
=
test_program
.
clone
(
for_test
=
True
)
main_graph
=
IrGraph
(
core
.
Graph
(
main
.
desc
),
for_test
=
False
)
test_graph
=
IrGraph
(
core
.
Graph
(
test_
graph
.
desc
),
for_test
=
True
)
test_graph
=
IrGraph
(
core
.
Graph
(
test_
program
.
desc
),
for_test
=
True
)
place
=
fluid
.
CUDAPlace
(
0
)
if
use_cuda
else
fluid
.
CPUPlace
()
exe
=
fluid
.
Executor
(
place
)
scope
=
fluid
.
Scope
()
with
fluid
.
scope_guard
(
scope
):
exe
.
run
(
startup
)
transform_pass
=
QuantizationTransformPass
(
scope
=
fluid
.
global_scope
(),
program_exe
=
exe
)
scope
=
scope
,
program_exe
=
exe
,
activation_quantize_type
=
quant_type
)
transform_pass
.
apply
(
main_graph
)
transform_pass
.
apply
(
test_graph
)
iters
=
5
batch_size
=
8
class_num
=
10
exe
.
run
(
startup
)
dev_name
=
'_gpu_'
if
use_cuda
else
'_cpu_'
train_reader
=
paddle
.
batch
(
paddle
.
reader
.
shuffle
(
...
...
@@ -238,57 +245,87 @@ class TestQuantizeTranspiler(unittest.TestCase):
test_reader
=
paddle
.
batch
(
paddle
.
dataset
.
mnist
.
test
(),
batch_size
=
batch_size
)
feeder
=
fluid
.
DataFeeder
(
feed_list
=
feeds
,
place
=
place
)
with
fluid
.
program_guard
(
main
):
with
fluid
.
scope_guard
(
scope
):
for
_
in
range
(
iters
):
data
=
next
(
train_reader
())
loss_v
=
exe
.
run
(
program
=
main
,
loss_v
=
exe
.
run
(
program
=
main
_graph
.
to_program
()
,
feed
=
feeder
.
feed
(
data
),
fetch_list
=
[
loss
])
print
(
'{}: {}'
.
format
(
dev_name
,
loss_v
))
marked_nodes
=
set
()
for
op
in
main_graph
.
all_ops
():
if
op
.
name
().
find
(
'quantize'
)
>
-
1
:
marked_nodes
.
add
(
op
)
main_graph
.
draw
(
'.'
,
'main'
+
dev_name
+
quant_type
,
marked_nodes
)
freeze_pass
=
QuantizationFreezePass
(
scope
=
scope
,
place
=
place
)
origin_marked_nodes
=
set
()
for
op
in
test_graph
.
all_ops
():
if
op
.
name
().
find
(
'quantize'
)
>
-
1
:
origin_marked_nodes
.
add
(
op
)
test_graph
.
draw
(
'.'
,
'test_origin'
+
dev_name
+
quant_type
,
origin_marked_nodes
)
freeze_pass
.
apply
(
test_graph
)
freeze_marked_nodes
=
set
()
for
op
in
test_graph
.
all_ops
():
if
op
.
name
().
find
(
'quantize'
)
>
-
1
:
freeze_marked_nodes
.
add
(
op
)
test_graph
.
draw
(
'.'
,
'test_freeze'
+
dev_name
+
quant_type
,
freeze_marked_nodes
)
# with fluid.program_guard(test_program):
# test_data = next(test_reader())
# w_var = fluid.framework._get_var('conv2d_1.w_0.quantized',
# test_program)
# # Testing during training
# test_loss1, w_quant = exe.run(program=test_program,
# feed=feeder.feed(test_data),
# fetch_list=[loss, w_var])
# # Freeze program for inference, but the weight of fc/conv is still float type.
# quant_transpiler.freeze_program(test_program, place)
# test_loss2, = exe.run(program=test_program,
# feed=feeder.feed(test_data),
# fetch_list=[loss])
# self.assertAlmostEqual(test_loss1, test_loss2, delta=5e-3)
# w_freeze = np.array(fluid.global_scope().find_var('conv2d_1.w_0')
# .get_tensor())
# # fail: -432.0 != -433.0, this is due to the calculation precision
# #self.assertAlmostEqual(np.sum(w_freeze), np.sum(w_quant))
# # Convert parameter to 8-bit.
# quant_transpiler.convert_to_int8(test_program, place)
# # Save the 8-bit parameter and model file.
# fluid.io.save_inference_model('model_8bit', ['image', 'label'],
# [loss], exe, test_program)
# # Test whether the 8-bit parameter and model file can be loaded successfully.
# [infer, feed, fetch] = fluid.io.load_inference_model('model_8bit',
# exe)
# # Check the loaded 8-bit weight.
# w_8bit = np.array(fluid.global_scope().find_var('conv2d_1.w_0.int8')
# .get_tensor())
# self.assertEqual(w_8bit.dtype, np.int8)
# self.assertEqual(np.sum(w_8bit), np.sum(w_freeze))
def
test_freeze_program_cuda_dynamic
(
self
):
if
fluid
.
core
.
is_compiled_with_cuda
():
with
fluid
.
unique_name
.
guard
():
self
.
freeze_graph
(
True
,
seed
=
1
,
quant_type
=
'abs_max'
)
def
test_freeze_program_cpu_dynamic
(
self
):
with
fluid
.
unique_name
.
guard
():
self
.
freeze_graph
(
False
,
seed
=
2
,
quant_type
=
'abs_max'
)
with
fluid
.
program_guard
(
test_program
):
test_data
=
next
(
test_reader
())
w_var
=
fluid
.
framework
.
_get_var
(
'conv2d_1.w_0.quantized'
,
test_program
)
# Testing during training
test_loss1
,
w_quant
=
exe
.
run
(
program
=
test_program
,
feed
=
feeder
.
feed
(
test_data
),
fetch_list
=
[
loss
,
w_var
])
# Freeze program for inference, but the weight of fc/conv is still float type.
quant_transpiler
.
freeze_program
(
test_program
,
place
)
test_loss2
,
=
exe
.
run
(
program
=
test_program
,
feed
=
feeder
.
feed
(
test_data
),
fetch_list
=
[
loss
])
self
.
assertAlmostEqual
(
test_loss1
,
test_loss2
,
delta
=
5e-3
)
w_freeze
=
np
.
array
(
fluid
.
global_scope
().
find_var
(
'conv2d_1.w_0'
)
.
get_tensor
())
# fail: -432.0 != -433.0, this is due to the calculation precision
#self.assertAlmostEqual(np.sum(w_freeze), np.sum(w_quant))
# Convert parameter to 8-bit.
quant_transpiler
.
convert_to_int8
(
test_program
,
place
)
# Save the 8-bit parameter and model file.
fluid
.
io
.
save_inference_model
(
'model_8bit'
,
[
'image'
,
'label'
],
[
loss
],
exe
,
test_program
)
# Test whether the 8-bit parameter and model file can be loaded successfully.
[
infer
,
feed
,
fetch
]
=
fluid
.
io
.
load_inference_model
(
'model_8bit'
,
exe
)
# Check the loaded 8-bit weight.
w_8bit
=
np
.
array
(
fluid
.
global_scope
().
find_var
(
'conv2d_1.w_0.int8'
)
.
get_tensor
())
self
.
assertEqual
(
w_8bit
.
dtype
,
np
.
int8
)
self
.
assertEqual
(
np
.
sum
(
w_8bit
),
np
.
sum
(
w_freeze
))
def
not_test_freeze_program_cuda
(
self
):
def
test_freeze_program_cuda_static
(
self
):
if
fluid
.
core
.
is_compiled_with_cuda
():
with
fluid
.
unique_name
.
guard
():
self
.
freeze_
program
(
True
,
seed
=
1
)
self
.
freeze_
graph
(
True
,
seed
=
1
,
quant_type
=
'range_abs_max'
)
def
not_test_freeze_program_cpu
(
self
):
def
test_freeze_program_cpu_static
(
self
):
with
fluid
.
unique_name
.
guard
():
self
.
freeze_
program
(
False
,
seed
=
2
)
self
.
freeze_
graph
(
False
,
seed
=
2
,
quant_type
=
'range_abs_max'
)
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/framework.py
浏览文件 @
c8095eeb
...
...
@@ -16,6 +16,7 @@ from __future__ import print_function
import
collections
from
collections
import
defaultdict
from
collections
import
Iterable
import
contextlib
import
os
import
re
...
...
@@ -1630,7 +1631,10 @@ class IrGraph(object):
def
safe_remove_nodes
(
self
,
remove_nodes
):
if
not
isinstance
(
remove_nodes
,
set
):
remove_nodes
=
set
(
remove_nodes
)
if
isinstance
(
remove_nodes
,
Iterable
):
remove_nodes
=
set
(
remove_nodes
)
else
:
remove_nodes
=
{
remove_nodes
}
core
.
graph_safe_remove_nodes
(
self
.
graph
,
remove_nodes
)
def
has_circle
(
self
):
...
...
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