altanh commented on code in PR #10969:
URL: https://github.com/apache/tvm/pull/10969#discussion_r848709195
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python/tvm/relay/op/transform.py:
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@@ -836,7 +836,7 @@ def broadcast_to(data, shape):
The resulting tensor.
"""
if isinstance(shape, Constant):
- shape = list(shape.data.numpy())
+ shape = [int(i) for i in shape.data.numpy()]
Review Comment:
It's possible, although the default handler for a python list of ints would
hit the same problem. In either case, I'll push a proper fix for the reduction
schedule on CUDA (forcibly cast the extent to `int32`, since that's needed for
CUDA anyway if I understand correctly).
Do you think I should wrap ints using numpy `int64` to avoid this problem?
I'm slightly worried it will break assumptions elsewhere.
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