Updates

Author: Thiago Crepaldi

beginner_source/onnx/README.txt

@@ -6,9 +6,9 @@ ONNX
     https://pytorch.org/tutorials/onnx/intro_onnx.html
 
 2. export_simple_model_to_onnx_tutorial.py
-    Export a PyTorch model to ONNX
+    Exporting a PyTorch model to ONNX
     https://pytorch.org/tutorials/beginner/onnx/export_simple_model_to_onnx_tutorial.html
 
 3. onnx_registry_tutorial.py
-    Introduction to ONNX
+    Extending the ONNX Registry
     https://pytorch.org/tutorials/beginner/onnx/onnx_registry_tutorial.html

beginner_source/onnx/export_simple_model_to_onnx_tutorial.py

@@ -1,8 +1,8 @@
 # -*- coding: utf-8 -*-
 """
 `Introduction to ONNX <intro_onnx.html>`_ ||
-**Export a PyTorch model to ONNX** ||
-`Introduction to ONNX Registry <onnx_registry_tutorial.html>`_
+**Exporting a PyTorch model to ONNX** ||
+`Extending the ONNX Registry <onnx_registry_tutorial.html>`_
 
 Export a PyTorch model to ONNX
 ==============================
@@ -168,9 +168,9 @@ def to_numpy(tensor):
 
 onnxruntime_outputs = ort_session.run(None, onnxruntime_input)
 
-######################################################################
+####################################################################
 # 7. Compare the PyTorch results with the ones from the ONNX Runtime
-# -----------------------------------------------------------------
+# ------------------------------------------------------------------
 #
 # The best way to determine whether the exported model is looking good is through numerical evaluation
 # against PyTorch, which is our source of truth.

beginner_source/onnx/intro_onnx.py

@@ -1,7 +1,7 @@
 """
 **Introduction to ONNX** ||
-`Export a PyTorch model to ONNX <export_simple_model_to_onnx_tutorial.html>`_ ||
-`Introduction to ONNX Registry <onnx_registry_tutorial.html>`_
+`Exporting a PyTorch model to ONNX <export_simple_model_to_onnx_tutorial.html>`_ ||
+`Extending the ONNX Registry <onnx_registry_tutorial.html>`_
 
 Introduction to ONNX
 ====================
@@ -37,21 +37,33 @@
 
 The ONNX exporter depends on extra Python packages:
 
-  - `ONNX <https://onnx.ai>`_
-  - `ONNX Script <https://onnxscript.ai>`_
+  - `ONNX <https://onnx.ai>`_ standard library
+  - `ONNX Script <https://onnxscript.ai>`_ library that enables developers to author ONNX operators,
+    functions and models using a subset of Python in an expressive, and yet simple fashion.
 
 They can be installed through `pip <https://pypi.org/project/pip/>`_:
 
-.. note::
-   This tutorial leverages `onnxscript <https://github.com/microsoft/onnxscript#readme>`__
-   to create custom ONNX operators. onnxscript is a Python library that allows users to
-   create custom ONNX operators in Python. It is a prerequisite learning material for
-   this tutorial. Please make sure you have read the onnxscript tutorial before proceeding.
-
 .. code-block:: bash
 
   pip install --upgrade onnx onnxscript
 
+To validate the installation, run the following commands:
+
+.. code-block:: python
+
+  import torch
+  print(torch.__version__)
+
+  import onnxscript
+  print(onnxscript.__version__)
+
+  from onnxscript import opset18  # opset 18 is the latest (and only) supported version for now
+
+  import onnxruntime
+  print(onnxruntime.__version__)
+
+Each `import` must succeed without any errors and the library versions must be printed out.
+
 Further reading
 ---------------