[GitHub] [incubator-tvm] jwfromm commented on issue #4271: [Relay][Frontend][ONNX] operator support: DepthToSpace, SpaceToDepth

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jwfromm commented on issue #4271: [Relay][Frontend][ONNX] operator support: DepthToSpace, SpaceToDepth
URL: https://github.com/apache/incubator-tvm/pull/4271#issuecomment-552056942
 
 
   Although your changes to the tests removing the hardcoding are definitely in the right direction, I think we should test the actual values instead of just their shapes. To do this, I recommend making a change from your current testing loop:
   
   ```
   for target, ctx in ctx_list():
       x = np.random.uniform(size=inshape).astype('int32')
       tvm_out = get_tvm_output(model, x, target, ctx, outshape, 'float32')
   tvm.testing.assert_allclose(outshape, tvm_out.shape)
   ```
   to
   ```
   for target, ctx in ctx_list():
       x = np.random.uniform(size=inshape).astype('int32')
       tvm_out = get_tvm_output(model, x, target, ctx, outshape, 'float32')
       onnx_out = get_caffe2_output(model, x, 'int32')
       tvm.testing.assert_allclose(onnx_out, tvm_out)
   ```
   
   That way we can be sure that both the values and shape produced are correct.

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