sxjscience opened a new pull request #17683: Fix reverse shape inference in LayerNorm URL: https://github.com/apache/incubator-mxnet/pull/17683 Fix https://github.com/apache/incubator-mxnet/issues/17654. Now, the user will see an error message if the `in_channels` does not match with the corresponding dimension in the input After the PR, the following will raise an error ```python import mxnet as mx from mxnet.gluon import nn net = nn.LayerNorm(in_channels=10) net.initialize() net.hybridize() out = net(mx.nd.ones((2, 11))) # Trigger the error ``` Error: ``` MXNetError: MXNetError: Error in operator layernorm0_layernorm0: Shape inconsistent, Provided = [10], inferred shape=[11] ```
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