Merge branch 'master' into holly1238-patch-1

Author: holly1238

beginner_source/saving_loading_models.py

@@ -227,6 +227,42 @@
 # normalization layers to evaluation mode before running inference.
 # Failing to do this will yield inconsistent inference results.
 #
+# Export/Load Model in TorchScript Format
+# ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+#
+# One common way to do inference with a trained model is to use
+# `TorchScript <https://pytorch.org/docs/stable/jit.html>`__, an intermediate
+# representation of a PyTorch model that can be run in Python as well as in a
+# high performance environment like C++. TorchScript is actually the recommended model format
+# for scaled inference and deployment.
+#
+# .. note::
+#    Using the TorchScript format, you will be able to load the exported model and
+#    run inference without defining the model class.
+#
+# **Export:**
+#
+# .. code:: python
+#
+#    model_scripted = torch.jit.script(model) # Export to TorchScript
+#    model_scripted.save('model_scripted.pt') # Save
+#
+# **Load:**
+#
+# .. code:: python
+#
+#    model = torch.jit.load('model_scripted.pt')
+#    model.eval()
+#
+# Remember that you must call ``model.eval()`` to set dropout and batch
+# normalization layers to evaluation mode before running inference.
+# Failing to do this will yield inconsistent inference results.
+#
+# For more information on TorchScript, feel free to visit the dedicated
+# `tutorials <https://pytorch.org/tutorials/beginner/Intro_to_TorchScript_tutorial.html>`__.
+# You will get familiar with the tracing conversion and learn how to
+# run a TorchScript module in a `C++ environment <https://pytorch.org/tutorials/advanced/cpp_export.html>`__.
+
 
 
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