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Makefile
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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 -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/]
# Run structured downloads first (will also make directories)
python3 .build/download_data.py
# data loader tutorial
wget -nv -N https://download.pytorch.org/tutorial/faces.zip -P $(DATADIR)
unzip $(ZIPOPTS) $(DATADIR)/faces.zip -d beginner_source/data/
unzip $(ZIPOPTS) $(DATADIR)/faces.zip -d recipes_source/recipes/data/
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
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/hybrid_frontend/introduction_to_hybrid_frontend_tutorial.py
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 -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 model for advanced_source/dynamic_quantization_tutorial.py
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 -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 -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 -nv -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth
# Download vocab for beginner_source/flava_finetuning_tutorial.py
wget -nv -N http://dl.fbaipublicfiles.com/pythia/data/vocab.tar.gz -P $(DATADIR)
tar $(TAROPTS) -xzf $(DATADIR)/vocab.tar.gz -C ./beginner_source/data/
# Download dataset for beginner_source/torchtext_custom_dataset_tutorial.py
wget -nv -N https://www.manythings.org/anki/deu-eng.zip -P $(DATADIR)
unzip -o $(DATADIR)/deu-eng.zip -d beginner_source/data/
# Download PennFudanPed dataset for intermediate_source/torchvision_tutorial.py
wget https://www.cis.upenn.edu/~jshi/ped_html/PennFudanPed.zip -P $(DATADIR)
unzip -o $(DATADIR)/PennFudanPed.zip -d intermediate_source/data/
# Download some dataset for beginner_source/translation_transformer.py
python -m spacy download en_core_web_sm
python -m spacy download de_core_news_sm
requirements-minimal:
pip install -r .build/requirements-minimal.txt
requirements-full:
make requirements-minimal
pip install -r .build/requirements-full.txt
docs:
make requirements-full
make download
make html
rm -rf docs
cp -r $(BUILDDIR)/html docs
cp CNAME docs/CNAME
cp robots.txt docs/robots.txt
touch docs/.nojekyll
@echo
@echo "Build finished. The HTML pages are in $(BUILDDIR)/html."
html-noplot:
make requirements-minimal
$(SPHINXBUILD) -D plot_gallery=0 -b html $(SPHINXOPTS) "$(SOURCEDIR)" "$(BUILDDIR)/html"
# bash .jenkins/remove_invisible_code_block_batch.sh "$(BUILDDIR)/html"
@echo
@echo "HTML-ONLY build finished. The HTML pages are in $(BUILDDIR)/html."
clean-cache:
make clean
rm -rf advanced beginner intermediate recipes prototype
# remove additional python files downloaded for torchvision_tutorial.py
rm -f intermediate_source/engine.py intermediate_source/utils.py intermediate_source/transforms.py intermediate_source/coco_eval.py intermediate_source/coco_utils.py