[GitHub] [incubator-mxnet] QueensGambit edited a comment on issue #17827: [Numpy] Bugfix of slice operator export (MXNet to ONNX)

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QueensGambit edited a comment on issue #17827: [Numpy] Bugfix of slice operator export (MXNet to ONNX)
URL: https://github.com/apache/incubator-mxnet/pull/17827#issuecomment-615874810
 
 
   Hello @RuRo, great to see that you have been working on the shape inference issue.
   Surprisingly, I didn't receive any notification for your PR and only noticed it after you mentioned it.
   Passing `graph_shapes` as a dict is a working solution but is cumbersome for deep models with changing shape sizes.
   I noticed that there is existing functionality for inferring the out-shapes of a symbol object.
   For instance you can plot the model structure including all shapes of each layer like this:
   ```python
       display(mx.viz.plot_network(
           symbol,
           shape={'data':(input_shape)},
           node_attrs={"shape":"oval","fixedsize":"false"}
       ))
   ```
   The corresponding code for inferring the shapes looks like this:
   ```python
       internals = symbol.get_internals()
       input_name = "data"
       _, out_shapes, _ = internals.infer_shape(**{input_name: input_shape})
   ```
   This way you would only require `input_name` as an additional parameter which could be set to `"data"` by default.
   Do you want to update your code or should I do it?

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