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Merge branch 'main' into csl/fix_isolation_macs
2 parents 91e1705 + 876c563 commit 17251ef

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.ci/docker/requirements.txt

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# Refer to ./jenkins/build.sh for tutorial build instructions
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sphinx==5.3.0
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sphinx-gallery==0.11.1
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sphinx-gallery==0.17.1
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sphinx-reredirects==0.1.4
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sphinx-design==0.4.0
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docutils==0.16
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torchx
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torchrl==0.7.2
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tensordict==0.7.2
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ax-platform>=0.4.0
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# For ax_multiobjective_nas_tutorial.py
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ax-platform>=0.4.0,<0.5.0
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nbformat>=5.9.2
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datasets
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transformers

Makefile

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wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/cornell_movie_dialogs_corpus_v2.zip -P $(DATADIR)
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unzip $(ZIPOPTS) $(DATADIR)/cornell_movie_dialogs_corpus_v2.zip -d beginner_source/data/
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# Download model for advanced_source/dynamic_quantization_tutorial.py
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wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/word_language_model_quantize.pth -P $(DATADIR)
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cp $(DATADIR)/word_language_model_quantize.pth advanced_source/data/word_language_model_quantize.pth
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# Download data for advanced_source/dynamic_quantization_tutorial.py
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wget -nv -N https://s3.amazonaws.com/pytorch-tutorial-assets/wikitext-2.zip -P $(DATADIR)
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unzip $(ZIPOPTS) $(DATADIR)/wikitext-2.zip -d advanced_source/data/
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# Download model for advanced_source/static_quantization_tutorial.py
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wget -nv -N https://download.pytorch.org/models/mobilenet_v2-b0353104.pth -P $(DATADIR)
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cp $(DATADIR)/mobilenet_v2-b0353104.pth advanced_source/data/mobilenet_pretrained_float.pth
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# Download model for prototype_source/graph_mode_static_quantization_tutorial.py
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wget -nv -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
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cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth
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# Download PennFudanPed dataset for intermediate_source/torchvision_tutorial.py
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wget https://www.cis.upenn.edu/~jshi/ped_html/PennFudanPed.zip -P $(DATADIR)
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unzip -o $(DATADIR)/PennFudanPed.zip -d intermediate_source/data/
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custom_directives.py

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if 'intro' in self.options:
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intro = self.options['intro'][:195] + '...'
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else:
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_, blocks = sphinx_gallery.gen_rst.split_code_and_text_blocks(abs_fname)
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block_parser = sphinx_gallery.gen_rst.BlockParser(abs_fname, {"filetype_parsers": {}})
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_, blocks, _ = block_parser.split_code_and_text_blocks(abs_fname)
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intro, _ = sphinx_gallery.gen_rst.extract_intro_and_title(abs_fname, blocks[0][1])
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thumbnail_rst = ''

prototype_source/README.txt

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Profiling PyTorch RPC-Based Workloads
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https://github.com/pytorch/tutorials/blob/main/prototype_source/distributed_rpc_profiling.rst
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2. graph_mode_static_quantization_tutorial.py
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Graph Mode Post Training Static Quantization in PyTorch
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https://pytorch.org/tutorials/prototype/graph_mode_static_quantization_tutorial.html
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3. graph_mode_dynamic_bert_tutorial.rst
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Graph Mode Dynamic Quantization on BERT
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https://github.com/pytorch/tutorials/blob/main/prototype_source/graph_mode_dynamic_bert_tutorial.rst
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4. numeric_suite_tutorial.py
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PyTorch Numeric Suite Tutorial
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https://github.com/pytorch/tutorials/blob/main/prototype_source/numeric_suite_tutorial.py
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5. torchscript_freezing.py
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2. torchscript_freezing.py
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Model Freezing in TorchScript
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https://github.com/pytorch/tutorials/blob/main/prototype_source/torchscript_freezing.py
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6. vulkan_workflow.rst
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3. vulkan_workflow.rst
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Vulkan Backend User Workflow
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https://pytorch.org/tutorials/intermediate/vulkan_workflow.html
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7. fx_graph_mode_ptq_static.rst
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FX Graph Mode Post Training Static Quantization
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https://pytorch.org/tutorials/prototype/fx_graph_mode_ptq_static.html
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8. fx_graph_mode_ptq_dynamic.py
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FX Graph Mode Post Training Dynamic Quantization
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https://pytorch.org/tutorials/prototype/fx_graph_mode_ptq_dynamic.html
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9. fx_graph_mode_quant_guide.py
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FX Graph Mode Quantization User Guide
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https://pytorch.org/tutorials/prototype/fx_graph_mode_quant_guide.html
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10 flight_recorder_tutorial.rst
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https://pytorch.org/tutorials/prototype/vulkan_workflow.html
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4. flight_recorder_tutorial.rst
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Flight Recorder User Guide
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https://pytorch.org/tutorials/prototype/flight_recorder_tutorial.html
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11 python_extension_autoload.rst
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5. python_extension_autoload.rst
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Autoloading Out-of-Tree Extension
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https://pytorch.org/tutorials/prototype/python_extension_autoload.html

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