pretrained model names update
authorManu Mathew <a0393608@ti.com>
Tue, 12 May 2020 16:13:55 +0000 (21:43 +0530)
committerManu Mathew <a0393608@ti.com>
Wed, 13 May 2020 03:00:29 +0000 (08:30 +0530)
run_quantization.sh
run_quantization_example.sh

index f9882afd0d9dbb4caf7d63f9f9100b6afa8d0cb0..96876974a016f4d7ca25d83554e1391020a7387f 100755 (executable)
 #
 #### Image Classification - Quantization Aware Training - 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/experimental/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.tar \
+#--pretrained ./data/modelzoo/experimental/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.pth \
 #--batch_size 64 --quantize True --epochs 25 --epoch_size 1000 --lr 1e-5 --evaluate_start False
 #
 #
 #### Semantic Segmentation - Quantization Aware Training 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/pytorch/semantic_seg/cityscapes/jacinto_ai/deeplabv3lite_mobilenetv2_tv_768x384_best.pth.tar \
+#--pretrained ./data/modelzoo/pytorch/semantic_seg/cityscapes/jacinto_ai/deeplabv3lite_mobilenetv2_tv_768x384_best.pth \
 #--batch_size 6 --quantize True --epochs 150 --lr 1e-5 --evaluate_start False
 #
 #
 #### Semantic Segmentation - Quantization Aware Training for MobileNetV2+UNetLite
 #python ./scripts/train_segmentation_main.py --dataset_name cityscapes_segmentation --model_name unetlite_pixel2pixel_aspp_mobilenetv2_tv --data_path ./data/datasets/cityscapes/data --img_resize 384 768 --output_size 1024 2048 --gpus 0 1 \
-#--pretrained ./data/modelzoo/pytorch/semantic_seg/cityscapes/jacinto_ai/unet_aspp_mobilenetv2_tv_768x384_best.pth.tar \
+#--pretrained ./data/modelzoo/pytorch/semantic_seg/cityscapes/jacinto_ai/unet_aspp_mobilenetv2_tv_768x384_best.pth \
 #--batch_size 6 --quantize True --epochs 150 --lr 1e-5 --evaluate_start False
 
 ## =====================================================================================
index 213e8b5ac29261985e7ad8fcb0e0bcf354293c8c..4cfe685c8e44c834135d0c278b86084465452acd 100755 (executable)
@@ -23,7 +23,7 @@ declare -A model_pretrained=(
   [mobilenet_v2]=https://download.pytorch.org/models/mobilenet_v2-b0353104.pth
   [resnet50]=https://download.pytorch.org/models/resnet50-19c8e357.pth
   [shufflenet_v2_x1_0]=https://download.pytorch.org/models/shufflenetv2_x1-5666bf0f80.pth
-#  [mobilenetv2_shicai]='./data/modelzoo/experimental/pytorch/others/shicai/MobileNet-Caffe/mobilenetv2_shicai_rgb.tar'
+#  [mobilenetv2_shicai]='./data/modelzoo/pytorch/image_classification/imagenet1k/shicai/mobilenetv2_shicai_rgb.pth'
 )
 
 # ----------------------------------