Adding 2 new quant tutorials

Makefile

@@ -96,7 +96,7 @@ download:
 	# Download dataset for advanced_source/static_quantization_tutorial.py
 	wget -N https://s3.amazonaws.com/pytorch-tutorial-assets/imagenet_1k.zip -P $(DATADIR)
 	unzip -q -o $(DATADIR)/imagenet_1k.zip -d advanced_source/data/
-
+	
 
 docs:
 	make download

beginner_source/transfer_learning_tutorial.py

@@ -334,3 +334,12 @@ def visualize_model(model, num_images=6):
 
 plt.ioff()
 plt.show()
+
+######################################################################
+# Further Learning
+# -----------------
+#
+# If you would like to learn more about the applications of transfer learning,
+# checkout our `Quantized Transfer Learning for Computer Vision Tutorial <https://pytorch.org/tutorials/intermediate/quantized_transfer_learning.html>`_.
+#
+

index.rst

@@ -247,6 +247,18 @@ Quantization (experimental)
     :figure: /_static/img/qat.png
     :description: :doc:`advanced/static_quantization_tutorial`
 
+.. customgalleryitem::
+    :tooltip: Perform quantized transfer learning with feature extractor
+    :description: :doc:`/intermediate/quantized_transfer_learning_tutorial`
+    :figure: /_static/img/quantized_transfer_learning.png
+
+.. customgalleryitem::
+  :tooltip: Convert a well-known state-of-the-art model like BERT into dynamic quantized model
+  :description: :doc:`/intermediate/dynamic_quantization_bert_tutorial`
+  :figure: /_static/img/bert.png
+
+
+
 .. raw:: html
 
     <div style='clear:both'></div>
@@ -328,7 +340,7 @@ PyTorch Fundamentals In-Depth
    beginner/text_sentiment_ngrams_tutorial
    beginner/torchtext_translation_tutorial
    beginner/transformer_tutorial
-   
+
 .. toctree::
    :maxdepth: 2
    :includehidden:
@@ -385,6 +397,8 @@ PyTorch Fundamentals In-Depth
 
    advanced/dynamic_quantization_tutorial
    advanced/static_quantization_tutorial
+   intermediate/quantized_transfer_learning_tutorial
+   intermediate/dynamic_quantization_bert_tutorial
 
 .. toctree::
    :maxdepth: 2