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体验新版 GitCode,发现更多精彩内容 >>
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b339dff2
编写于
1月 16, 2020
作者:
J
juncaipeng
提交者:
GitHub
1月 16, 2020
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电子邮件补丁
差异文件
fix use cache file, test=develop (#22240)
上级
895f8da7
变更
2
隐藏空白更改
内联
并排
Showing
2 changed file
with
14 addition
and
11 deletion
+14
-11
python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py
...slim/tests/test_post_training_quantization_mobilenetv1.py
+10
-8
python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_resnet50.py
...ib/slim/tests/test_post_training_quantization_resnet50.py
+4
-3
未找到文件。
python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_mobilenetv1.py
浏览文件 @
b339dff2
...
...
@@ -236,6 +236,7 @@ class TestPostTrainingQuantization(unittest.TestCase):
def
generate_quantized_model
(
self
,
model_path
,
quantizable_op_type
,
algo
=
"KL"
,
is_full_quantize
=
False
,
is_use_cache_file
=
False
):
...
...
@@ -250,9 +251,6 @@ class TestPostTrainingQuantization(unittest.TestCase):
exe
=
fluid
.
Executor
(
place
)
scope
=
fluid
.
global_scope
()
val_reader
=
val
()
quantizable_op_type
=
[
"conv2d"
,
"depthwise_conv2d"
,
"mul"
,
"pool2d"
,
"elementwise_add"
]
ptq
=
PostTrainingQuantization
(
executor
=
exe
,
...
...
@@ -265,8 +263,8 @@ class TestPostTrainingQuantization(unittest.TestCase):
ptq
.
quantize
()
ptq
.
save_quantized_model
(
self
.
int8_model
)
def
run_test
(
self
,
model
,
algo
,
data_urls
,
data_md5s
,
is_full_quantiz
e
,
is_use_cache_file
):
def
run_test
(
self
,
model
,
algo
,
data_urls
,
data_md5s
,
quantizable_op_typ
e
,
is_
full_quantize
,
is_
use_cache_file
):
infer_iterations
=
self
.
infer_iterations
batch_size
=
self
.
batch_size
sample_iterations
=
self
.
sample_iterations
...
...
@@ -280,7 +278,8 @@ class TestPostTrainingQuantization(unittest.TestCase):
print
(
"Start INT8 post training quantization for {0} on {1} images ..."
.
format
(
model
,
sample_iterations
*
batch_size
))
self
.
generate_quantized_model
(
model_cache_folder
+
"/model"
,
algo
,
self
.
generate_quantized_model
(
model_cache_folder
+
"/model"
,
quantizable_op_type
,
algo
,
is_full_quantize
,
is_use_cache_file
)
print
(
"Start INT8 inference for {0} on {1} images ..."
.
format
(
...
...
@@ -308,10 +307,13 @@ class TestPostTrainingForMobilenetv1(TestPostTrainingQuantization):
'http://paddle-inference-dist.bj.bcebos.com/int8/mobilenetv1_int8_model.tar.gz'
]
data_md5s
=
[
'13892b0716d26443a8cdea15b3c6438b'
]
quantizable_op_type
=
[
"conv2d"
,
"depthwise_conv2d"
,
"mul"
,
"pool2d"
,
"elementwise_add"
]
is_full_quantize
=
True
is_use_cache_file
=
False
self
.
run_test
(
model
,
algo
,
data_urls
,
data_md5s
,
is_full_quantiz
e
,
is_use_cache_file
)
self
.
run_test
(
model
,
algo
,
data_urls
,
data_md5s
,
quantizable_op_typ
e
,
is_
full_quantize
,
is_
use_cache_file
)
if
__name__
==
'__main__'
:
...
...
python/paddle/fluid/contrib/slim/tests/test_post_training_quantization_resnet50.py
浏览文件 @
b339dff2
...
...
@@ -25,10 +25,11 @@ class TestPostTrainingForResnet50(TestPostTrainingQuantization):
'http://paddle-inference-dist.bj.bcebos.com/int8/resnet50_int8_model.tar.gz'
]
data_md5s
=
[
'4a5194524823d9b76da6e738e1367881'
]
quantizable_op_type
=
[
"conv2d"
,
"mul"
]
is_full_quantize
=
False
is_use_cache_file
=
Tru
e
self
.
run_test
(
model
,
algo
,
data_urls
,
data_md5s
,
is_full_quantiz
e
,
is_use_cache_file
)
is_use_cache_file
=
Fals
e
self
.
run_test
(
model
,
algo
,
data_urls
,
data_md5s
,
quantizable_op_typ
e
,
is_
full_quantize
,
is_
use_cache_file
)
if
__name__
==
'__main__'
:
...
...
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