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Makefile
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# Minimal makefile for Sphinx documentation
#
# Locale
export LC_ALL=C
# You can set these variables from the command line.
SPHINXOPTS ?=
SPHINXBUILD = sphinx-build
SPHINXPROJ = PyTorchTutorials
SOURCEDIR = .
BUILDDIR = _build
DATADIR = _data
GH_PAGES_SOURCES = $(SOURCEDIR) Makefile
ZIPOPTS ?= -qo
TAROPTS ?=
# Put it first so that "make" without argument is like "make help".
help:
@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
.PHONY: help Makefile docs
# Catch-all target: route all unknown targets to Sphinx using the new
# "make mode" option. $(O) is meant as a shortcut for $(SPHINXOPTS).
%: Makefile
@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O) -v
download:
# IMPORTANT NOTE: Please make sure your dataset is downloaded to *_source/data folder,
# otherwise CI might silently break.
# 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)
# 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/]
# make data directories
mkdir -p $(DATADIR)
mkdir -p advanced_source/data
mkdir -p beginner_source/data
mkdir -p intermediate_source/data
# transfer learning tutorial data
wget -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)
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)
unzip $(ZIPOPTS) $(DATADIR)/faces.zip -d beginner_source/data/
wget -N https://download.pytorch.org/models/tutorials/4000_checkpoint.tar -P $(DATADIR)
cp $(DATADIR)/4000_checkpoint.tar beginner_source/data/
# neural style images
rm -rf advanced_source/data/images/ || true
mkdir -p advanced_source/data/images/
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)
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)
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.zip -P $(DATADIR)
unzip $(ZIPOPTS) $(DATADIR)/cornell_movie_dialogs_corpus.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)
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)
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)
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)
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)
cp $(DATADIR)/mobilenet_v2-b0353104.pth advanced_source/data/mobilenet_pretrained_float.pth
# Download dataset for advanced_source/static_quantization_tutorial.py
wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/imagenet_1k.zip -P $(DATADIR)
unzip $(ZIPOPTS) $(DATADIR)/imagenet_1k.zip -d advanced_source/data/
docs:
make download
make html
rm -rf docs
cp -r $(BUILDDIR)/html docs
touch docs/.nojekyll
html-noplot:
make clean
$(SPHINXBUILD) -D plot_gallery=0 -b html $(SPHINXOPTS) "$(SOURCEDIR)" "$(BUILDDIR)/html"
# bash .jenkins/remove_invisible_code_block_batch.sh "$(BUILDDIR)/html"
@echo
@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
clean-cache:
make clean
rm -rf advanced beginner intermediate recipes