# Quantization ## ===================================================================================== ## Trained Quantization ## ===================================================================================== # #### Image Classification - Trained Quantization - MobileNetV2 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth \ #--batch_size 64 --quantize True --epochs 25 --epoch_size 1000 --lr 1e-5 --evaluate_start False # # #### Image Classification - Trained Quantization - MobileNetV2(Shicai) - a TOUGH MobileNetV2 pretrained model #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name mobilenetv2_shicai_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained ./data/modelzoo/pretrained/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.tar \ #--batch_size 64 --quantize True --epochs 25 --epoch_size 1000 --lr 1e-5 --evaluate_start False # # #### Semantic Segmentation - Trained Quantization for MobileNetV2+DeeplabV3Lite #python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name deeplabv3lite_mobilenetv2_tv --data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \ #--pretrained ./data/modelzoo/semantic_segmentation/cityscapes/deeplabv3lite-mobilenetv2/cityscapes_segmentation_deeplabv3lite-mobilenetv2_2019-06-26-08-59-32.pth \ #--batch_size 12 --quantize True --epochs 150 --lr 1e-5 --evaluate_start False ## ===================================================================================== ## Acuracy Evaluation with Post Training Quantization - cannot save quantized model - only accuracy evaluation ## ===================================================================================== #### Image Classification - Accuracy Estimation with Post Training Quantization - MobileNetV2 #python ./scripts/train_classification_main.py --phase validation --dataset_name image_folder_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth \ #--batch_size 64 --quantize True #### Image Classification - Accuracy Estimation with Post Training Quantization - ResNet50 #python ./scripts/train_classification_main.py --phase validation --dataset_name image_folder_classification --model_name resnet50_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained https://download.pytorch.org/models/resnet50-19c8e357.pth \ #--batch_size 64 --quantize True #### Image Classification - Accuracy Estimation with Post Training Quantization - A TOUGH MobileNetV2 pretrained model #python ./scripts/train_classification_main.py --phase validation --dataset_name image_folder_classification --model_name mobilenetv2_shicai_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained ./data/modelzoo/pretrained/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.tar \ #--batch_size 64 --quantize True #### Semantic Segmentation - Accuracy Estimation with Post Training Quantization #python ./scripts/train_segmentation_main.py --phase validation --dataset_name cityscapes_segmentation --model_name deeplabv3lite_mobilenetv2_tv --data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \ #--pretrained './data/modelzoo/semantic_segmentation/cityscapes/deeplabv3lite-mobilenetv2/cityscapes_segmentation_deeplabv3lite-mobilenetv2_2019-06-26-08-59-32.pth' \ #--batch_size 1 --quantize True ## ===================================================================================== ## Post Training Calibration & Quantization - this is fast, but may not always yield best quantized accuracy (not recommended) ## ===================================================================================== # #### Image Classification - Post Training Calibration & Quantization - ResNet50 #python ./scripts/train_classification_main.py --phase calibration --dataset_name image_folder_classification --model_name resnet50_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained https://download.pytorch.org/models/resnet50-19c8e357.pth \ #--batch_size 64 --quantize True --epochs 1 --epoch_size 100 # # #### Image Classification - Post Training Calibration & Quantization - MobileNetV2 #python ./scripts/train_classification_main.py --phase calibration --dataset_name image_folder_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth \ #--batch_size 64 --quantize True --epochs 1 --epoch_size 100 # # #### Image Classification - Post Training Calibration & Quantization for a TOUGH MobileNetV2 pretrained model #python ./scripts/train_classification_main.py --phase calibration --dataset_name image_folder_classification --model_name mobilenetv2_shicai_x1 --data_path ./data/datasets/image_folder_classification \ #--pretrained ./data/modelzoo/pretrained/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.tar \ #--batch_size 64 --quantize True --epochs 1 --epoch_size 100 # # #### Semantic Segmentation - Post Training Calibration & Quantization for MobileNetV2+DeeplabV3Lite #python ./scripts/train_segmentation_main.py --phase calibration --dataset_name cityscapes_segmentation --model_name deeplabv3lite_mobilenetv2_tv --data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \ #--pretrained ./data/modelzoo/semantic_segmentation/cityscapes/deeplabv3lite-mobilenetv2/cityscapes_segmentation_deeplabv3lite-mobilenetv2_2019-06-26-08-59-32.pth \ #--batch_size 12 --quantize True --epochs 1 --epoch_size 100