Update onnx creation with dynamic batch size option

docs/source/creators/creators_example_onnx_model.rst

@@ -31,7 +31,7 @@ Steps based on `EXPORTING A MODEL FROM PYTORCH TO ONNX AND RUNNING IT USING ONNX
     x = torch.rand(1, INP_CHANNEL, INP_HEIGHT, INP_WIDTH) # eg. torch.rand([1, 3, 256, 256])
     _ = model(x)
 
-* Step 3. Call export function
+* Step 3a. Call export function with static batch_size=1:
 
   .. code-block:: 
 
@@ -44,6 +44,20 @@ Steps based on `EXPORTING A MODEL FROM PYTORCH TO ONNX AND RUNNING IT USING ONNX
                     output_names=['output'],
                     do_constant_folding=False)
 
+* Step 3b. Call export function with dynamic batch_size:
+
+  .. code-block:: 
+
+    torch.onnx.export(model,
+                    x,  # model input
+                    'model.onnx',  # where to save the model
+                    export_params=True,
+                    opset_version=15,
+                    input_names=['input'],
+                    output_names=['output'],
+                    dynamic_axes={'input': {0: 'batch_size'},  # variable lenght axes
+                                  'output': {0: 'batch_size'}})
+
 ================
 Tensorflow/Keras
 ================
@@ -63,3 +77,9 @@ Steps based on the `tensorflow-onnx <https://github.com/onnx/tensorflow-onnx>`_
   .. code-block:: 
 
     python -m tf2onnx.convert --saved-model YOUR_MODEL_CHECKPOINT_PATH --output model.onnx --opset 15
+
+===============================================
+Update ONNX model to support dynamic batch size
+===============================================
+
+To convert model to support dynamic batch size, you need to update :code:`model.onnx` file. You can do it manually using `this <https://github.com/onnx/onnx/issues/2182#issuecomment-881752539>` script. Please note that the script is not perfect and may not work for all models.