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make wget less verbose #2032

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Sep 8, 2022
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28 changes: 14 additions & 14 deletions Makefile
Original file line number Diff line number Diff line change
Expand Up @@ -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/]
Expand All @@ -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
Expand All @@ -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


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