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Paddle/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt

159 lines
7.6 KiB

file(GLOB TEST_OPS RELATIVE "${CMAKE_CURRENT_SOURCE_DIR}" "test_*.py")
string(REPLACE ".py" "" TEST_OPS "${TEST_OPS}")
function(_inference_analysis_python_api_int8_test target model_dir data_dir filename use_mkldnn)
py_test(${target} SRCS ${filename}
ENVS CPU_NUM_THREADS=${CPU_NUM_THREADS_ON_CI}
FLAGS_use_mkldnn=${use_mkldnn}
ARGS --infer_model ${model_dir}/model
--infer_data ${data_dir}/data.bin
--int8_model_save_path int8_models/${target}
--warmup_batch_size 100
--batch_size 50)
endfunction()
function(inference_analysis_python_api_int8_test target model_dir data_dir filename)
_inference_analysis_python_api_int8_test(${target} ${model_dir} ${data_dir} ${filename} False)
endfunction()
function(inference_analysis_python_api_int8_test_mkldnn target model_dir data_dir filename)
_inference_analysis_python_api_int8_test(${target} ${model_dir} ${data_dir} ${filename} True)
endfunction()
function(inference_qat_int8_test target model_dir data_dir test_script use_mkldnn)
py_test(${target} SRCS ${test_script}
ENVS FLAGS_OMP_NUM_THREADS=${CPU_NUM_THREADS_ON_CI}
OMP_NUM_THREADS=${CPU_NUM_THREADS_ON_CI}
FLAGS_use_mkldnn=${use_mkldnn}
ARGS --qat_model ${model_dir}/model
--infer_data ${data_dir}/data.bin
--batch_size 25
--batch_num 2
--acc_diff_threshold 0.1)
endfunction()
# NOTE: TODOOOOOOOOOOO
# temporarily disable test_distillation_strategy since it always failed on a specified machine with 4 GPUs
# Need to figure out the root cause and then add it back
list(REMOVE_ITEM TEST_OPS test_distillation_strategy)
if(WIN32)
list(REMOVE_ITEM TEST_OPS test_light_nas)
endif()
# int8 image classification python api test
if(LINUX AND WITH_MKLDNN)
set(INT8_DATA_DIR "${INFERENCE_DEMO_INSTALL_DIR}/int8v2")
set(MKLDNN_INT8_TEST_FILE "test_mkldnn_int8_quantization_strategy.py")
set(MKLDNN_INT8_TEST_FILE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/${MKLDNN_INT8_TEST_FILE}")
# googlenet int8
set(INT8_GOOGLENET_MODEL_DIR "${INT8_DATA_DIR}/googlenet")
inference_analysis_python_api_int8_test(test_slim_int8_googlenet ${INT8_GOOGLENET_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# mobilenet int8
set(INT8_MOBILENET_MODEL_DIR "${INT8_DATA_DIR}/mobilenetv1")
inference_analysis_python_api_int8_test(test_slim_int8_mobilenet ${INT8_MOBILENET_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
inference_analysis_python_api_int8_test_mkldnn(test_slim_int8_mobilenet_mkldnn ${INT8_MOBILENET_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# temporarily adding WITH_SLIM_MKLDNN_FULL_TEST FLAG for QA testing the following UTs locally,
# since the following UTs cost too much time on CI test.
if (WITH_SLIM_MKLDNN_FULL_TEST)
# resnet50 int8
set(INT8_RESNET50_MODEL_DIR "${INT8_DATA_DIR}/resnet50")
inference_analysis_python_api_int8_test(test_slim_int8_resnet50 ${INT8_RESNET50_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# mobilenetv2 int8
set(INT8_MOBILENETV2_MODEL_DIR "${INT8_DATA_DIR}/mobilenetv2")
inference_analysis_python_api_int8_test(test_slim_int8_mobilenetv2 ${INT8_MOBILENETV2_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# resnet101 int8
set(INT8_RESNET101_MODEL_DIR "${INT8_DATA_DIR}/resnet101")
inference_analysis_python_api_int8_test(test_slim_int8_resnet101 ${INT8_RESNET101_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# vgg16 int8
set(INT8_VGG16_MODEL_DIR "${INT8_DATA_DIR}/vgg16")
inference_analysis_python_api_int8_test(test_slim_int8_vgg16 ${INT8_VGG16_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
# vgg19 int8
set(INT8_VGG19_MODEL_DIR "${INT8_DATA_DIR}/vgg19")
inference_analysis_python_api_int8_test(test_slim_int8_vgg19 ${INT8_VGG19_MODEL_DIR} ${INT8_DATA_DIR} ${MKLDNN_INT8_TEST_FILE_PATH})
endif()
endif()
# Since test_mkldnn_int8_quantization_strategy only supports testing on Linux
# with MKL-DNN, we remove it here for not repeating test, or not testing on other systems.
list(REMOVE_ITEM TEST_OPS test_mkldnn_int8_quantization_strategy)
# QAT FP32 & INT8 comparison python api tests
if(LINUX AND WITH_MKLDNN)
set(DATASET_DIR "${INFERENCE_DEMO_INSTALL_DIR}/int8v2")
set(QAT_DATA_DIR "${INFERENCE_DEMO_INSTALL_DIR}/int8v2")
set(QAT_MODELS_BASE_URL "${INFERENCE_URL}/int8/QAT_models")
set(MKLDNN_QAT_TEST_FILE "qat_int8_comparison.py")
set(MKLDNN_QAT_TEST_FILE_PATH "${CMAKE_CURRENT_SOURCE_DIR}/${MKLDNN_QAT_TEST_FILE}")
# ImageNet small dataset
# May be already downloaded for INT8v2 unit tests
if (NOT EXISTS ${DATASET_DIR})
inference_download_and_uncompress(${DATASET_DIR} "${INFERENCE_URL}/int8" "imagenet_val_100_tail.tar.gz")
endif()
# QAT ResNet50
set(QAT_RESNET50_MODEL_DIR "${QAT_DATA_DIR}/ResNet50_QAT")
if (NOT EXISTS ${QAT_RESNET50_MODEL_DIR})
inference_download_and_uncompress(${QAT_RESNET50_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "ResNet50_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_resnet50_mkldnn ${QAT_RESNET50_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT ResNet101
set(QAT_RESNET101_MODEL_DIR "${QAT_DATA_DIR}/ResNet101_QAT")
if (NOT EXISTS ${QAT_RESNET101_MODEL_DIR})
inference_download_and_uncompress(${QAT_RESNET101_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "ResNet101_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_resnet101_mkldnn ${QAT_RESNET101_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT GoogleNet
set(QAT_GOOGLENET_MODEL_DIR "${QAT_DATA_DIR}/GoogleNet_QAT")
if (NOT EXISTS ${QAT_GOOGLENET_MODEL_DIR})
inference_download_and_uncompress(${QAT_GOOGLENET_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "GoogleNet_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_googlenet_mkldnn ${QAT_GOOGLENET_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT MobileNetV1
set(QAT_MOBILENETV1_MODEL_DIR "${QAT_DATA_DIR}/MobileNetV1_QAT")
if (NOT EXISTS ${QAT_MOBILENETV1_MODEL_DIR})
inference_download_and_uncompress(${QAT_MOBILENETV1_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "MobileNetV1_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_mobilenetv1_mkldnn ${QAT_MOBILENETV1_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT MobileNetV2
set(QAT_MOBILENETV2_MODEL_DIR "${QAT_DATA_DIR}/MobileNetV2_QAT")
if (NOT EXISTS ${QAT_MOBILENETV2_MODEL_DIR})
inference_download_and_uncompress(${QAT_MOBILENETV2_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "MobileNetV2_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_mobilenetv2_mkldnn ${QAT_MOBILENETV2_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT VGG16
set(QAT_VGG16_MODEL_DIR "${QAT_DATA_DIR}/VGG16_QAT")
if (NOT EXISTS ${QAT_VGG16_MODEL_DIR})
inference_download_and_uncompress(${QAT_VGG16_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "VGG16_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_vgg16_mkldnn ${QAT_VGG16_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
# QAT VGG19
set(QAT_VGG19_MODEL_DIR "${QAT_DATA_DIR}/VGG19_QAT")
if (NOT EXISTS ${QAT_VGG19_MODEL_DIR})
inference_download_and_uncompress(${QAT_VGG19_MODEL_DIR} "${QAT_MODELS_BASE_URL}" "VGG19_qat_model.tar.gz" )
endif()
inference_qat_int8_test(test_qat_int8_vgg19_mkldnn ${QAT_VGG19_MODEL_DIR} ${DATASET_DIR} ${MKLDNN_QAT_TEST_FILE_PATH} true)
endif()
# Since the test for QAT FP32 & INT8 comparison supports only testing on Linux
# with MKL-DNN, we remove it here to not test it on other systems.
list(REMOVE_ITEM TEST_OPS qat_int8_comparison.py)
foreach(src ${TEST_OPS})
py_test(${src} SRCS ${src}.py)
endforeach()