quantization_example - RandomSampler is used when epoch_size!=0. epoch_size=0.1 means...
[jacinto-ai/pytorch-jacinto-ai-devkit.git] / run_classification.sh
1 # Summary of commands - uncomment one and run this script
2 #### For the datasets in sections marked as "Automatic Download", dataset will be downloaded automatically downloaded before training begins. For "Manual Download", it is expected that it is manually downloaded and kept in the folder specified agaianst the --data_path option.
4 ## =====================================================================================
5 ## Training
6 ## =====================================================================================
7 ## Cifar100 Classification (Automatic Download)
8 #### Training with MobileNetV2
9 #python ./scripts/train_classification_main.py --dataset_name cifar100_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/cifar100_classification --img_resize 32 --img_crop 32 --rand_scale 0.5 1.0 --strides 1 1 1 2 2
11 ## Cifar10 Classification (Automatic Download)
12 #### Training with MobileNetV2
13 #python ./scripts/train_classification_main.py --dataset_name cifar10_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/cifar10_classification --img_resize 32 --img_crop 32 --rand_scale 0.5 1.0 --strides 1 1 1 2 2
15 ## ImageNet Classification (Automatic Download)
16 #### Training with MobileNetV2
17 #python ./scripts/train_classification_main.py --dataset_name imagenet_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/imagenet_classification
19 ## ImageNet Classification (Manual Download)
20 #### Training with MobileNetV2
21 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/image_folder_classification
22 #### Training with MobileNetV2 - Small Resolution
23 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/image_folder_classification --img_resize 146 --img_crop 128 --batch_size 1024 --lr 0.2 --workers 16
24 #### Training with MobileNetV2 with 2x channels and expansion factor of 2
25 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name mobilenetv2_tv_x2_t2 --data_path ./data/datasets/image_folder_classification --batch_size 256
27 ### Training with ResNet50
28 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name resnet50_x1 --data_path ./data/datasets/image_folder_classification
29 ### Training with ResNet50 - with half the number of channels - so roughly 1/4 the complexity
30 #python ./scripts/train_classification_main.py --dataset_name image_folder_classification --model_name resnet50_xp5 --data_path ./data/datasets/image_folder_classification
32 ## =====================================================================================
33 ## Validation
34 ## =====================================================================================
35 #### cifar100 Validation - populate the pretrained model path below in ??
36 #python ./scripts/train_classification_main.py --phase validation --dataset_name cifar100_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/cifar100_classification --img_resize 32 --img_crop 32 \
37 #--pretrained=???
39 #### cifar10 Validation - populate the pretrained model path below in ??
40 #python ./scripts/train_classification_main.py --phase validation --dataset_name cifar10_classification --model_name mobilenetv2_tv_x1 --data_path ./data/datasets/cifar10_classification --img_resize 32 --img_crop 32 \
41 #--pretrained=???
43 #### Validation - populate the pretrained model path below in ?? or use https://download.pytorch.org/models/resnet50-19c8e357.pth for resnet50_x1
44 #python ./scripts/train_classification_main.py --phase validation --dataset_name image_folder_classification --model_name resnet50_x1 --data_path ./data/datasets/image_folder_classification \
45 #--pretrained https://download.pytorch.org/models/resnet50-19c8e357.pth
47 #### Validation - populate the pretrained model path below in ?? or use https://download.pytorch.org/models/mobilenet_v2-b0353104.pth for mobilenetv2_tv_x1
48 #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 \
49 #--pretrained https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
51 #### Validation - populate the pretrained model path below in ?? for resnet50_xp5
52 #python ./scripts/train_classification_main.py --phase validation --dataset_name image_folder_classification --model_name resnet50_xp5 --data_path ./data/datasets/image_folder_classification \
53 #--pretrained ./data/modelzoo/pytorch/image_classification/imagenet1k/jacinto_ai/resnet50-0.5_2018-07-23_12-10-23.pth