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体验新版 GitCode,发现更多精彩内容 >>
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ed7956a8
编写于
3月 21, 2021
作者:
G
guofei
提交者:
GitHub
3月 21, 2021
浏览文件
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电子邮件补丁
差异文件
Fix skip_quant in QAT (#31704)
* Fix skip_quant in QAT
上级
8c19d7aa
变更
4
隐藏空白更改
内联
并排
Showing
4 changed file
with
60 addition
and
7 deletion
+60
-7
python/paddle/fluid/contrib/slim/quantization/imperative/qat.py
.../paddle/fluid/contrib/slim/quantization/imperative/qat.py
+35
-3
python/paddle/fluid/contrib/slim/quantization/imperative/utils.py
...addle/fluid/contrib/slim/quantization/imperative/utils.py
+6
-0
python/paddle/fluid/contrib/slim/tests/test_imperative_out_scale.py
...dle/fluid/contrib/slim/tests/test_imperative_out_scale.py
+7
-0
python/paddle/fluid/contrib/slim/tests/test_imperative_skip_op.py
...addle/fluid/contrib/slim/tests/test_imperative_skip_op.py
+12
-4
未找到文件。
python/paddle/fluid/contrib/slim/quantization/imperative/qat.py
浏览文件 @
ed7956a8
...
...
@@ -515,6 +515,8 @@ class ImperativeCalcOutputScale(object):
self
.
_out_scale_dict
[
ops_list
[
op_count
]])
op_count
+=
1
self
.
_set_skip_quant_attr
(
inference_program
)
# save the final quantized model that has output scales
save_inference_model
(
dirname
=
dirname
,
...
...
@@ -537,9 +539,12 @@ class ImperativeCalcOutputScale(object):
Init the scale params for calculating output scales and save them in the
target layer.
After the users define the dygraph model, the hooks for calculating output
scales will not execute immediately. If the users load the checkpoint now,
the scale params have not been created, so them cann't be loaded.
Therefore, define the scale params in the beginning.
scales will not execute immediately. If the users load parameters form
checkpoint and save the quantized inference model immediately, the inference
model would not be saved successfully. Beacuse the dygraph_to_static requires
that the parameters created in __init__, but the uniqueness of hook make it
impossible to create parameters in __init__. To avoid this mistake, we define
the scale parameters in the beginning instead of hook.
"""
def
_create_param
(
in_layer
,
first_name
,
last_name
,
dtype
):
...
...
@@ -587,6 +592,33 @@ class ImperativeCalcOutputScale(object):
op_type
=
op_type
.
replace
(
'relu'
,
're_lu'
)
return
op_type
in
layer_name
def
_set_skip_quant_attr
(
self
,
program
):
block
=
program
.
global_block
()
for
op
in
block
.
ops
:
if
self
.
_is_skip_quant_op
(
block
,
op
):
op
.
_set_attr
(
"skip_quant"
,
True
)
def
_is_skip_quant_op
(
self
,
block
,
in_op
):
"""
The input op should be skipped quantization.
1. the type of input op should be conv2d, depthwise_conv2d or matmul
2. the previous ops of the input op are not fake_quantize_dequantize ops
"""
def
_find_previous_op
(
block
,
var_name
):
for
op
in
block
.
ops
:
if
var_name
in
op
.
output_arg_names
:
return
op
target_op_types
=
[
"conv2d"
,
"depthwise_conv2d"
,
"matmul"
]
if
in_op
.
type
not
in
target_op_types
:
return
False
previous_ops
=
[
_find_previous_op
(
block
,
arg_name
)
\
for
arg_name
in
in_op
.
input_arg_names
]
return
any
(
op
is
not
None
and
op
.
type
not
in
utils
.
fake_quantize_dequantize_types
\
for
op
in
previous_ops
)
def
_calc_output_scale_hook
(
self
,
layer
,
input
,
output
):
"""
Create the MovingAverageAbsMaxScale layer for the target layer if needed.
...
...
python/paddle/fluid/contrib/slim/quantization/imperative/utils.py
浏览文件 @
ed7956a8
...
...
@@ -52,6 +52,12 @@ supported_quant_layers_map = {
'LayerNorm'
:
paddle
.
nn
.
LayerNorm
,
}
fake_quantize_dequantize_types
=
[
"fake_quantize_dequantize_abs_max"
,
"fake_quantize_dequantize_channel_wise_abs_max"
,
"fake_quantize_dequantize_moving_average_abs_max"
]
out_scale_layers_list
=
(
paddle
.
nn
.
Conv2D
,
paddle
.
nn
.
Linear
,
paddle
.
nn
.
MaxPool2D
,
paddle
.
nn
.
BatchNorm
,
paddle
.
nn
.
BatchNorm2D
,
paddle
.
nn
.
SyncBatchNorm
,
...
...
python/paddle/fluid/contrib/slim/tests/test_imperative_out_scale.py
浏览文件 @
ed7956a8
...
...
@@ -393,12 +393,16 @@ class TestImperativeOutSclae(unittest.TestCase):
if
'fake'
in
op
.
type
:
static_ops
.
remove
(
op
)
op_count
=
0
for
i
in
range
(
len
(
dynamic_ops
)):
if
dynamic_ops
[
i
].
has_attr
(
"out_threshold"
):
op_count
+=
1
self
.
assertTrue
(
dynamic_ops
[
i
].
type
==
static_ops
[
i
].
type
)
self
.
assertTrue
(
dynamic_ops
[
i
].
attr
(
"out_threshold"
)
==
static_ops
[
i
].
attr
(
"out_threshold"
))
self
.
assertTrue
(
op_count
==
13
)
class
TestSaveQuanztizedModelFromCheckPoint
(
unittest
.
TestCase
):
def
test_save_quantized_model
(
self
):
...
...
@@ -459,11 +463,14 @@ class TestSaveQuanztizedModelFromCheckPoint(unittest.TestCase):
if
'fake'
in
op
.
type
:
static_ops
.
remove
(
op
)
op_count
=
0
for
i
in
range
(
len
(
dynamic_ops
)):
if
dynamic_ops
[
i
].
has_attr
(
"out_threshold"
):
op_count
+=
1
self
.
assertTrue
(
dynamic_ops
[
i
].
type
==
static_ops
[
i
].
type
)
self
.
assertTrue
(
dynamic_ops
[
i
].
attr
(
"out_threshold"
)
==
static_ops
[
i
].
attr
(
"out_threshold"
))
self
.
assertTrue
(
op_count
==
13
)
class
TestSaveQuantizedModel_Warning
(
unittest
.
TestCase
):
...
...
python/paddle/fluid/contrib/slim/tests/test_imperative_skip_op.py
浏览文件 @
ed7956a8
...
...
@@ -200,9 +200,12 @@ class TestImperativeOutSclae(unittest.TestCase):
params_filename
=
"lenet"
+
INFER_PARAMS_SUFFIX
))
model_ops
=
inference_program
.
global_block
().
ops
conv2d_count
,
mul_count
=
0
,
0
conv2d_count
,
matmul_count
=
0
,
0
conv2d_skip_count
,
matmul_skip_count
=
0
,
0
for
i
,
op
in
enumerate
(
model_ops
):
if
op
.
type
==
'conv2d'
:
if
op
.
has_attr
(
"skip_quant"
):
conv2d_skip_count
+=
1
if
conv2d_count
>
0
:
self
.
assertTrue
(
'fake_quantize_dequantize'
in
model_ops
[
i
-
1
].
type
)
...
...
@@ -211,14 +214,19 @@ class TestImperativeOutSclae(unittest.TestCase):
'fake_quantize_dequantize'
not
in
model_ops
[
i
-
1
].
type
)
conv2d_count
+=
1
if
op
.
type
==
'mul'
:
if
mul_count
>
0
:
if
op
.
type
==
'matmul'
:
if
op
.
has_attr
(
"skip_quant"
):
matmul_skip_count
+=
1
if
matmul_count
>
0
:
self
.
assertTrue
(
'fake_quantize_dequantize'
in
model_ops
[
i
-
1
].
type
)
else
:
self
.
assertTrue
(
'fake_quantize_dequantize'
not
in
model_ops
[
i
-
1
].
type
)
mul_count
+=
1
matmul_count
+=
1
self
.
assertTrue
(
conv2d_skip_count
==
1
)
self
.
assertTrue
(
matmul_skip_count
==
1
)
if
__name__
==
'__main__'
:
...
...
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