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Posted to commits@tvm.apache.org by GitBox <gi...@apache.org> on 2022/11/03 14:45:44 UTC

[GitHub] [tvm] wzh99 opened a new pull request, #13280: [Relay] Add tensor rank check for `nn.instance_norm`

wzh99 opened a new pull request, #13280:
URL: https://github.com/apache/tvm/pull/13280

This PR adds a rank check for input tensor in type inference of `nn.instance_norm`. I explain the reasons as follows:

First, according to the definition of [Instance Normalization](https://paperswithcode.com/method/instance-normalization), it only normalizes the data dimensions. Therefore, the input tensor must be of at least rank 3, and otherwise the operator will not produce meaningful results.

Second, `nn.instance_norm` with tensor rank less than 2 leads to a problem in the `SimplifyInference` optimization pass. This pass finds the reduced axes before converting the operator to its lower-level computation definition:
https://github.com/apache/tvm/blob/f15afd225140e2a501b8b6aa2def0fd94d31bc54/src/relay/transforms/simplify_inference.cc#L149-L152
If the rank of the input tensor is less than 3, `reduced_axes` is empty. According to `GetRealAxis`, all the dimensions are reduced:
https://github.com/apache/tvm/blob/f15afd225140e2a501b8b6aa2def0fd94d31bc54/include/tvm/topi/reduction.h#L67-L70
This is problematic because we do not actually want batch and `axis` dimensions to be reduced.

cc @masahi

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[GitHub] [tvm] masahi merged pull request #13280: [Relay] Add tensor rank check for `nn.instance_norm`

Posted by GitBox <gi...@apache.org>.

masahi merged PR #13280:
URL: https://github.com/apache/tvm/pull/13280


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[GitHub] [tvm] tvm-bot commented on pull request #13280: [Relay] Add tensor rank check for `nn.instance_norm`

Posted by GitBox <gi...@apache.org>.

tvm-bot commented on PR #13280:
URL: https://github.com/apache/tvm/pull/13280#issuecomment-1302223553

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