From c7eff4f78c2eb4221c78d1c078bfc6c9fe6b6186 Mon Sep 17 00:00:00 2001 From: Catherine Lee Date: Thu, 8 Sep 2022 11:34:19 -0700 Subject: [PATCH] quiet wget --- Makefile | 28 ++++++++++++++-------------- 1 file changed, 14 insertions(+), 14 deletions(-) diff --git a/Makefile b/Makefile index 0f3bde6aadb..8c21384967c 100644 --- a/Makefile +++ b/Makefile @@ -33,7 +33,7 @@ download: # NOTE: Please consider using the Step1 and one of Step2 for new dataset, # [something] should be replaced with the actual value. - # Step1. DOWNLOAD: wget -N [SOURCE_FILE] -P $(DATADIR) + # Step1. DOWNLOAD: wget -nv -N [SOURCE_FILE] -P $(DATADIR) # Step2-1. UNZIP: unzip -o $(DATADIR)/[SOURCE_FILE] -d [*_source/data/] # Step2-2. UNTAR: tar -xzf $(DATADIR)/[SOURCE_FILE] -C [*_source/data/] # Step2-3. AS-IS: cp $(DATADIR)/[SOURCE_FILE] [*_source/data/] @@ -46,18 +46,18 @@ download: mkdir -p prototype_source/data # transfer learning tutorial data - wget -N https://download.pytorch.org/tutorial/hymenoptera_data.zip -P $(DATADIR) + wget -nv -N https://download.pytorch.org/tutorial/hymenoptera_data.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/hymenoptera_data.zip -d beginner_source/data/ # nlp tutorial data - wget -N https://download.pytorch.org/tutorial/data.zip -P $(DATADIR) + wget -nv -N https://download.pytorch.org/tutorial/data.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/data.zip -d intermediate_source/ # This will unzip all files in data.zip to intermediate_source/data/ folder # data loader tutorial - wget -N https://download.pytorch.org/tutorial/faces.zip -P $(DATADIR) + wget -nv -N https://download.pytorch.org/tutorial/faces.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/faces.zip -d beginner_source/data/ - wget -N https://download.pytorch.org/models/tutorials/4000_checkpoint.tar -P $(DATADIR) + wget -nv -N https://download.pytorch.org/models/tutorials/4000_checkpoint.tar -P $(DATADIR) cp $(DATADIR)/4000_checkpoint.tar beginner_source/data/ # neural style images @@ -66,40 +66,40 @@ download: cp -r _static/img/neural-style/ advanced_source/data/images/ # Download dataset for beginner_source/dcgan_faces_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/img_align_celeba.zip -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/img_align_celeba.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/img_align_celeba.zip -d beginner_source/data/celeba # Download dataset for beginner_source/hybrid_frontend/introduction_to_hybrid_frontend_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/iris.data -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/iris.data -P $(DATADIR) cp $(DATADIR)/iris.data beginner_source/data/ # Download dataset for beginner_source/chatbot_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/cornell_movie_dialogs_corpus_v2.zip -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/cornell_movie_dialogs_corpus_v2.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/cornell_movie_dialogs_corpus_v2.zip -d beginner_source/data/ # Download dataset for beginner_source/audio_classifier_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/UrbanSound8K.tar.gz -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/UrbanSound8K.tar.gz -P $(DATADIR) tar $(TAROPTS) -xzf $(DATADIR)/UrbanSound8K.tar.gz -C ./beginner_source/data/ # Download model for beginner_source/fgsm_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/lenet_mnist_model.pth -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/lenet_mnist_model.pth -P $(DATADIR) cp $(DATADIR)/lenet_mnist_model.pth ./beginner_source/data/lenet_mnist_model.pth # Download model for advanced_source/dynamic_quantization_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth -P $(DATADIR) cp $(DATADIR)/word_language_model_quantize.pth advanced_source/data/word_language_model_quantize.pth # Download data for advanced_source/dynamic_quantization_tutorial.py - wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/wikitext-2.zip -P $(DATADIR) + wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/wikitext-2.zip -P $(DATADIR) unzip $(ZIPOPTS) $(DATADIR)/wikitext-2.zip -d advanced_source/data/ # Download model for advanced_source/static_quantization_tutorial.py - wget -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR) + wget -nv -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR) cp $(DATADIR)/mobilenet_v2-b0353104.pth advanced_source/data/mobilenet_pretrained_float.pth # Download model for prototype_source/graph_mode_static_quantization_tutorial.py - wget -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR) + wget -nv -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR) cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth