Add graph mode static quantization tutorial

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