fix ci

Author: titaiwangms

beginner_source/onnx/export_simple_model_to_onnx_tutorial.py

@@ -174,7 +174,7 @@ def forward(self, x: torch.Tensor):
     "./image_classifier_model.onnx", providers=["CPUExecutionProvider"]
 )
 
-onnxruntime_input = dict(zip(ort_session.get_inputs(), onnx_inputs))
+onnxruntime_input = {input_arg.name: input_value for input_arg, input_value in zip(ort_session.get_inputs(), onnx_inputs)}
 
 # onnxruntime returns a list of outputs
 onnxruntime_outputs = ort_session.run(None, onnxruntime_input)[0]

beginner_source/onnx/intro_onnx.py

@@ -22,7 +22,7 @@
 .. note::
     Currently, you can choose either through `TorchScript https://pytorch.org/docs/stable/jit.html`_ or
     `ExportedProgram https://pytorch.org/docs/stable/export.html`_ to export the model to ONNX by the
-    boolean parameter dynamo in `torch.onnx.export <https://pytorch.org/docs/stable/generated/torch.onnx.export.html>`_.
+    boolean parameter dynamo in `torch.onnx.export <https://pytorch.org/docs/stable/onnx_torchscript.html#torch.onnx.export>`_.
     In this tutorial, we will focus on the ``ExportedProgram`` approach.
 
 When setting ``dynamo=True``, the exporter will use `torch.export <https://pytorch.org/docs/stable/export.html>`_ to capture an ``ExportedProgram``,