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体验新版 GitCode,发现更多精彩内容 >>
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09eb82c5
编写于
6月 02, 2021
作者:
W
Wangzheee
提交者:
GitHub
6月 02, 2021
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电子邮件补丁
差异文件
fix (#33264)
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python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
+25
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python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
浏览文件 @
09eb82c5
...
...
@@ -25,21 +25,21 @@ function(inference_analysis_python_api_int8_test_mkldnn target model_dir data_pa
_inference_analysis_python_api_int8_test
(
${
target
}
${
model_dir
}
${
data_path
}
${
filename
}
True
)
endfunction
()
function
(
download_quant_data install_dir data_file
)
function
(
download_quant_data install_dir data_file
check_sum
)
if
(
NOT EXISTS
${
install_dir
}
/
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8
${
data_file
}
${
check_sum
}
)
endif
()
endfunction
()
function
(
download_quant_model install_dir data_file
)
function
(
download_quant_model install_dir data_file
check_sum
)
if
(
NOT EXISTS
${
install_dir
}
/
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models
${
data_file
}
${
check_sum
}
)
endif
()
endfunction
()
function
(
download_quant_fp32_model install_dir data_file
)
function
(
download_quant_fp32_model install_dir data_file
check_sum
)
if
(
NOT EXISTS
${
install_dir
}
/
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models/fp32
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models/fp32
${
data_file
}
${
check_sum
}
)
endif
()
endfunction
()
...
...
@@ -86,15 +86,15 @@ function(inference_quant2_int8_nlp_test target quant_model_dir fp32_model_dir da
--ops_to_quantize
${
ops_to_quantize
}
)
endfunction
()
function
(
download_quant_data install_dir data_file
)
function
(
download_quant_data install_dir data_file
check_sum
)
if
(
NOT EXISTS
${
install_dir
}
/
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8
${
data_file
}
${
check_sum
}
)
endif
()
endfunction
()
function
(
download_quant_model install_dir data_file
)
function
(
download_quant_model install_dir data_file
check_sum
)
if
(
NOT EXISTS
${
install_dir
}
/
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models
${
data_file
}
)
inference_download_and_uncompress
(
${
install_dir
}
${
INFERENCE_URL
}
/int8/QAT_models
${
data_file
}
${
check_sum
}
)
endif
()
endfunction
()
...
...
@@ -149,43 +149,43 @@ if(LINUX AND WITH_MKLDNN)
# Quant ResNet50
set
(
QUANT_RESNET50_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/ResNet50_quant"
)
set
(
QUANT_RESNET50_MODEL_ARCHIVE
"ResNet50_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_RESNET50_MODEL_DIR
}
${
QUANT_RESNET50_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_RESNET50_MODEL_DIR
}
${
QUANT_RESNET50_MODEL_ARCHIVE
}
ff89b934ab961c3a4a844193ece2e8a7
)
inference_quant_int8_image_classification_test
(
test_quant_int8_resnet50_mkldnn
${
QUANT_RESNET50_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant ResNet101
set
(
QUANT_RESNET101_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/ResNet101_quant"
)
set
(
QUANT_RESNET101_MODEL_ARCHIVE
"ResNet101_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_RESNET101_MODEL_DIR
}
${
QUANT_RESNET101_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_RESNET101_MODEL_DIR
}
${
QUANT_RESNET101_MODEL_ARCHIVE
}
95c6d01e3aeba31c13efb2ba8057d558
)
# inference_quant_int8_image_classification_test(test_quant_int8_resnet101_mkldnn ${QUANT_RESNET101_MODEL_DIR}/model ${IMAGENET_DATA_PATH})
# Quant GoogleNet
set
(
QUANT_GOOGLENET_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/GoogleNet_quant"
)
set
(
QUANT_GOOGLENET_MODEL_ARCHIVE
"GoogleNet_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_GOOGLENET_MODEL_DIR
}
${
QUANT_GOOGLENET_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_GOOGLENET_MODEL_DIR
}
${
QUANT_GOOGLENET_MODEL_ARCHIVE
}
1d4a7383baa63e7d1c423e8db2b791d5
)
inference_quant_int8_image_classification_test
(
test_quant_int8_googlenet_mkldnn
${
QUANT_GOOGLENET_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant MobileNetV1
set
(
QUANT_MOBILENETV1_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/MobileNetV1_quant"
)
set
(
QUANT_MOBILENETV1_MODEL_ARCHIVE
"MobileNetV1_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_MOBILENETV1_MODEL_DIR
}
${
QUANT_MOBILENETV1_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_MOBILENETV1_MODEL_DIR
}
${
QUANT_MOBILENETV1_MODEL_ARCHIVE
}
3b774d94a9fcbb604d09bdb731fc1162
)
inference_quant_int8_image_classification_test
(
test_quant_int8_mobilenetv1_mkldnn
${
QUANT_MOBILENETV1_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant MobileNetV2
set
(
QUANT_MOBILENETV2_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/MobileNetV2_quant"
)
set
(
QUANT_MOBILENETV2_MODEL_ARCHIVE
"MobileNetV2_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_MOBILENETV2_MODEL_DIR
}
${
QUANT_MOBILENETV2_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_MOBILENETV2_MODEL_DIR
}
${
QUANT_MOBILENETV2_MODEL_ARCHIVE
}
758a99d9225d8b73e1a8765883f96cdd
)
inference_quant_int8_image_classification_test
(
test_quant_int8_mobilenetv2_mkldnn
${
QUANT_MOBILENETV2_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant VGG16
set
(
QUANT_VGG16_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/VGG16_quant"
)
set
(
QUANT_VGG16_MODEL_ARCHIVE
"VGG16_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_VGG16_MODEL_DIR
}
${
QUANT_VGG16_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_VGG16_MODEL_DIR
}
${
QUANT_VGG16_MODEL_ARCHIVE
}
c37e63ca82a102f47be266f8068b0b55
)
# inference_quant_int8_image_classification_test(test_quant_int8_vgg16_mkldnn ${QUANT_VGG16_MODEL_DIR}/model ${IMAGENET_DATA_PATH})
# Quant VGG19
set
(
QUANT_VGG19_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/VGG19_quant"
)
set
(
QUANT_VGG19_MODEL_ARCHIVE
"VGG19_qat_model.tar.gz"
)
download_quant_model
(
${
QUANT_VGG19_MODEL_DIR
}
${
QUANT_VGG19_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT_VGG19_MODEL_DIR
}
${
QUANT_VGG19_MODEL_ARCHIVE
}
62bcd4b6c3ca2af67e8251d1c96ea18f
)
# inference_quant_int8_image_classification_test(test_quant_int8_vgg19_mkldnn ${QUANT_VGG19_MODEL_DIR}/model ${IMAGENET_DATA_PATH})
### Quant2 for image classification
...
...
@@ -194,7 +194,7 @@ if(LINUX AND WITH_MKLDNN)
# with weight scales in `fake_dequantize_max_abs` operators
set
(
QUANT2_RESNET50_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/ResNet50_quant2"
)
set
(
QUANT2_RESNET50_MODEL_ARCHIVE
"ResNet50_qat_perf.tar.gz"
)
download_quant_model
(
${
QUANT2_RESNET50_MODEL_DIR
}
${
QUANT2_RESNET50_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_RESNET50_MODEL_DIR
}
${
QUANT2_RESNET50_MODEL_ARCHIVE
}
e87309457e8c462a579340607f064d66
)
set
(
FP32_RESNET50_MODEL_DIR
"
${
INT8_INSTALL_DIR
}
/resnet50"
)
inference_quant2_int8_image_classification_test
(
test_quant2_int8_resnet50_mkldnn
${
QUANT2_RESNET50_MODEL_DIR
}
/ResNet50_qat_perf/float
${
FP32_RESNET50_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
...
...
@@ -202,20 +202,20 @@ if(LINUX AND WITH_MKLDNN)
# with weight scales in `fake_dequantize_max_abs` operators
set
(
QUANT2_RESNET50_RANGE_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/ResNet50_quant2_range"
)
set
(
QUANT2_RESNET50_RANGE_MODEL_ARCHIVE
"ResNet50_qat_range.tar.gz"
)
download_quant_model
(
${
QUANT2_RESNET50_RANGE_MODEL_DIR
}
${
QUANT2_RESNET50_RANGE_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_RESNET50_RANGE_MODEL_DIR
}
${
QUANT2_RESNET50_RANGE_MODEL_ARCHIVE
}
2fdc8a139f041c0d270abec826b2d304
)
inference_quant2_int8_image_classification_test
(
test_quant2_int8_resnet50_range_mkldnn
${
QUANT2_RESNET50_RANGE_MODEL_DIR
}
/ResNet50_qat_range
${
FP32_RESNET50_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant2 ResNet50 with input/output scales in `fake_quantize_range_abs_max` operators and the `out_threshold` attributes,
# with weight scales in `fake_channel_wise_dequantize_max_abs` operators
set
(
QUANT2_RESNET50_CHANNELWISE_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/ResNet50_quant2_channelwise"
)
set
(
QUANT2_RESNET50_CHANNELWISE_MODEL_ARCHIVE
"ResNet50_qat_channelwise.tar.gz"
)
download_quant_model
(
${
QUANT2_RESNET50_CHANNELWISE_MODEL_DIR
}
${
QUANT2_RESNET50_CHANNELWISE_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_RESNET50_CHANNELWISE_MODEL_DIR
}
${
QUANT2_RESNET50_CHANNELWISE_MODEL_ARCHIVE
}
887a1b1b0e9a4efd10f263a43764db26
)
inference_quant2_int8_image_classification_test
(
test_quant2_int8_resnet50_channelwise_mkldnn
${
QUANT2_RESNET50_CHANNELWISE_MODEL_DIR
}
/ResNet50_qat_channelwise
${
FP32_RESNET50_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
# Quant2 MobileNetV1
set
(
QUANT2_MOBILENETV1_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/MobileNetV1_quant2"
)
set
(
QUANT2_MOBILENETV1_MODEL_ARCHIVE
"MobileNet_qat_perf.tar.gz"
)
download_quant_model
(
${
QUANT2_MOBILENETV1_MODEL_DIR
}
${
QUANT2_MOBILENETV1_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_MOBILENETV1_MODEL_DIR
}
${
QUANT2_MOBILENETV1_MODEL_ARCHIVE
}
7f626e453db2d56fed6c2538621ffacf
)
set
(
FP32_MOBILENETV1_MODEL_DIR
"
${
INT8_INSTALL_DIR
}
/mobilenetv1"
)
inference_quant2_int8_image_classification_test
(
test_quant2_int8_mobilenetv1_mkldnn
${
QUANT2_MOBILENETV1_MODEL_DIR
}
/MobileNet_qat_perf/float
${
FP32_MOBILENETV1_MODEL_DIR
}
/model
${
IMAGENET_DATA_PATH
}
)
...
...
@@ -225,22 +225,22 @@ if(LINUX AND WITH_MKLDNN)
set
(
NLP_DATA_DIR
"
${
INFERENCE_DEMO_INSTALL_DIR
}
/Ernie_dataset"
)
set
(
NLP_DATA_PATH
"
${
NLP_DATA_DIR
}
/Ernie_dataset/1.8w.bs1"
)
set
(
NLP_LABLES_PATH
"
${
NLP_DATA_DIR
}
/Ernie_dataset/label.xnli.dev"
)
download_quant_data
(
${
NLP_DATA_DIR
}
${
NLP_DATA_ARCHIVE
}
)
download_quant_data
(
${
NLP_DATA_DIR
}
${
NLP_DATA_ARCHIVE
}
e650ce0cbc1fadbed5cc2c01d4e734dc
)
# Quant2 Ernie
set
(
QUANT2_ERNIE_MODEL_ARCHIVE
"ernie_qat.tar.gz"
)
set
(
QUANT2_ERNIE_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/Ernie_quant2"
)
download_quant_model
(
${
QUANT2_ERNIE_MODEL_DIR
}
${
QUANT2_ERNIE_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_ERNIE_MODEL_DIR
}
${
QUANT2_ERNIE_MODEL_ARCHIVE
}
f7cdf4720755ecf66efbc8044e9922d9
)
set
(
FP32_ERNIE_MODEL_ARCHIVE
"ernie_fp32_model.tar.gz"
)
set
(
FP32_ERNIE_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/Ernie_float"
)
download_quant_fp32_model
(
${
FP32_ERNIE_MODEL_DIR
}
${
FP32_ERNIE_MODEL_ARCHIVE
}
)
download_quant_fp32_model
(
${
FP32_ERNIE_MODEL_DIR
}
${
FP32_ERNIE_MODEL_ARCHIVE
}
114f38804a3ef8c45e7259e68bbd838b
)
set
(
QUANT2_ERNIE_OPS_TO_QUANTIZE
"fc,reshape2,transpose2,matmul,elementwise_add"
)
inference_quant2_int8_nlp_test
(
test_quant2_int8_ernie_mkldnn
${
QUANT2_ERNIE_MODEL_DIR
}
/Ernie_qat/float
${
FP32_ERNIE_MODEL_DIR
}
/ernie_fp32_model
${
NLP_DATA_PATH
}
${
NLP_LABLES_PATH
}
${
QUANT2_ERNIE_OPS_TO_QUANTIZE
}
)
# Quant2 GRU
set
(
QUANT2_GRU_MODEL_ARCHIVE
"GRU_quant_acc.tar.gz"
)
set
(
QUANT2_GRU_MODEL_DIR
"
${
QUANT_INSTALL_DIR
}
/GRU_quant2"
)
download_quant_model
(
${
QUANT2_GRU_MODEL_DIR
}
${
QUANT2_GRU_MODEL_ARCHIVE
}
)
download_quant_model
(
${
QUANT2_GRU_MODEL_DIR
}
${
QUANT2_GRU_MODEL_ARCHIVE
}
cf207f8076dcfb8b74d8b6bdddf9090c
)
set
(
QUANT2_GRU_OPS_TO_QUANTIZE
"multi_gru"
)
### Save FP32 model or INT8 model from Quant model
...
...
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