diff --git a/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt b/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
index 758e01b8245a2d7ea80791d6910ad868ac346492..249de87090ed8a50fa3e00cd4087b42636c70fa0 100644
--- a/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
+++ b/python/paddle/fluid/contrib/slim/tests/CMakeLists.txt
@@ -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