Add graph mode static quantization tutorial (pytorch#1070)

* Add TorchScript fork/join tutorial

* Add note about zipfile format in serialization tutorial

* Profiler recipe (pytorch#1019)

* Profiler recipe

Summary:
Adding a recipe for profiler

Test Plan:
make html-noplot

* [mobile] Mobile Perf Recipe

* Minor syntax edits to mobile perf recipe

* Remove built files

* [android] android native app recipe

* [mobile_perf][recipe] Add ChannelsLast recommendation

* Adding distributed pipeline parallel tutorial

* Add async execution tutorials

* Fix code block in pipeline tutorial

* Adding an Overview Page for PyTorch Distributed (pytorch#1056)

* Adding an Overview Page for PyTorch Distributed

* Let existing PT Distributed tutorials link to the overview page

* Add a link to AMP

* Address Comments

* Remove unnecessary dist.barrier()

* [Mobile Perf Recipe] Add the benchmarking part for iOS (pytorch#1055)

* [Mobile Perf Recipe] Add the benchmarking part for iOS

* [Mobile Perf Recipe] Add the benchmarking part for iOS

Co-authored-by: Jessica Lin <jplin@fb.com>

* Graph mode static quantization tutorial

* RPC profiling recipe (pytorch#1068)

* Initial commit

* Update

* Complete most of recipe

* Add image

* Link image

* Remove extra file

* update

* Update

* update

* Push latest changes from master into release/1.6 (pytorch#1074)

* Update feature classification labels

* Update NVidia -> Nvidia

* Bring back default filename_pattern so that by default we run all galleries.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Add prototype_source directory

* Add prototype directory

* Add prototype

* Remove extra "done"

* Add REAME.txt

* Update for prototype instructions

* Update for prototype feature

* refine torchvision_tutorial doc for windows

* Update neural_style_tutorial.py (pytorch#1059)

Updated the mistake in the Loading Images Section.

* torch_script_custom_ops restructure (pytorch#1057)

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Port custom ops tutorial to new registration API, increase testability.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Kill some other occurrences of RegisterOperators

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Update README.md

* Make torch_script_custom_classes tutorial runnable

I also fixed some warnings in the tutorial, and fixed some minor bitrot
(e.g., torch::script::Module to torch::jit::Module)

I also added some missing quotes around some bash expansions.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Update torch_script_custom_classes to use TORCH_LIBRARY (pytorch#1062)

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

Co-authored-by: Edward Z. Yang <ezyang@fb.com>
Co-authored-by: Yang Gu <yangu@microsoft.com>
Co-authored-by: Hritik Bhandari <bhandari.hritik@gmail.com>

* Tutorial for DDP + RPC (pytorch#1071)

* Update feature classification labels

* Update NVidia -> Nvidia

* Bring back default filename_pattern so that by default we run all galleries.

Signed-off-by: Edward Z. Yang <ezyang@fb.com>

* Tutorial for DDP + RPC.

Summary: Based on example from pytorch/examples#800

* Add to main section

Summary:

Test Plan:

Reviewers:

Subscribers:

Tasks:

Tags:

* Added separate code file and used literalinclude

Summary:

Test Plan:

Reviewers:

Subscribers:

Tasks:

Tags:

Co-authored-by: Jessica Lin <jplin@fb.com>
Co-authored-by: Edward Z. Yang <ezyang@fb.com>
Co-authored-by: pritam <pritam.damania@fb.com>

* Make RPC profiling recipe into prototype tutorial (pytorch#1078)

* Add RPC tutorial

* Update to include recipes

* Graph mode static quantization tutorial

Co-authored-by: James Reed <jamesreed@fb.com>
Co-authored-by: Jessica Lin <jplin@fb.com>
Co-authored-by: ilia-cher <30845429+ilia-cher@users.noreply.github.com>
Co-authored-by: Ivan Kobzarev <ivankobzarev@fb.com>
Co-authored-by: Shen Li <shenli@devfair017.maas>
Co-authored-by: Shen Li <cs.shenli@gmail.com>
Co-authored-by: Tao Xu <taox@fb.com>
Co-authored-by: Rohan Varma <rvarm1@fb.com>
Co-authored-by: Edward Z. Yang <ezyang@fb.com>
Co-authored-by: Yang Gu <yangu@microsoft.com>
Co-authored-by: Hritik Bhandari <bhandari.hritik@gmail.com>
Co-authored-by: Pritam Damania <9958665+pritamdamania87@users.noreply.github.com>
Co-authored-by: pritam <pritam.damania@fb.com>

Makefile

@@ -43,6 +43,7 @@ download:
 	mkdir -p advanced_source/data
 	mkdir -p beginner_source/data
 	mkdir -p intermediate_source/data
+	mkdir -p prototype_source/data
 
 	# transfer learning tutorial data
 	wget -N https://download.pytorch.org/tutorial/hymenoptera_data.zip -P $(DATADIR)
@@ -100,6 +101,14 @@ download:
 	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/imagenet_1k.zip -P $(DATADIR)
 	unzip $(ZIPOPTS) $(DATADIR)/imagenet_1k.zip -d advanced_source/data/
 
+	# Download model for prototype_source/graph_mode_static_quantization_tutorial.py
+	wget -N https://download.pytorch.org/models/resnet18-5c106cde.pth -P $(DATADIR)
+	cp $(DATADIR)/resnet18-5c106cde.pth prototype_source/data/resnet18_pretrained_float.pth
+
+	# Download dataset for prototype_source/graph_mode_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 prototype_source/data/
+
 docs:
 	make download
 	make html

prototype_source/README.txt

@@ -3,3 +3,7 @@ Prototype Tutorials
 1. distributed_rpc_profiling.rst
      Profiling PyTorch RPC-Based Workloads
      https://github.com/pytorch/tutorials/blob/release/1.6/prototype_source/distributed_rpc_profiling.rst
+
+2. graph_mode_static_quantization_tutorial.py
+	   Graph Mode Post Training Static Quantization in PyTorch
+	   https://pytorch.org/tutorials/prototype/graph_mode_static_quantization_tutorial.html