[GitHub] [incubator-tvm] masahi commented on a change in pull request #5075: [Torch] Add initial 3D op support and test on Resnet 3D

[GitBox <gi...@apache.org>]

masahi commented on a change in pull request #5075: [Torch] Add initial 3D op support and test on Resnet 3D
URL: https://github.com/apache/incubator-tvm/pull/5075#discussion_r393313322
 
 

 ##########
 File path: python/tvm/relay/frontend/pytorch.py
 ##########
 @@ -183,9 +183,27 @@ def _impl(inputs, input_types):
         data = inputs[0]
         output_size = _infer_shape(inputs[1])
 
+        # returns dummy indices too
         return _op.nn.adaptive_max_pool2d(
             data,
-            output_size=output_size)
+            output_size=output_size), None
+    return _impl
+
+def _adaptive_max_3d():
+    def _impl(inputs, input_types):
+        data = inputs[0]
+        output_size = _infer_shape(inputs[1])
+        # returns dummy indices too
+        return _op.nn.adaptive_max_pool3d(data, output_size=output_size), None
 
 Review comment:
   That is for python layer, after jitting torchscript `aten::adaptive_max_pool3d` (and 2d) op always returns 2 results. If `return_indices` is False, I think the second tensor is empty.
   
   See 
   https://github.com/pytorch/pytorch/blob/master/aten/src/ATen/native/AdaptiveMaxPooling3d.cpp#L421

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