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Implementation for equivalence of tf.moments #14842
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@eric-haibin-lin @reminisce @szha ping for review. |
Great! Is it convenient to support the tensor with arbitrary dimension? Thank you! |
One thing is that usually tensors do not have >5 dims. The kernel can actually handle any # of dims, but we need to modify the mxnet::TShape/Tuple class to enable GPUs to read from mxnet::TShape/Tuple. |
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Would you mind sharing some common use cases for this operator? Thanks!
@eric-haibin-lin The op gives variance of the input on arbitrary axis/axes, so it's technically the |
@eric-haibin-lin @hetong007 Is this good for merge? |
LGTM |
@eric-haibin-lin @szha Can any of you take a final look and help with merging this op? Thanks! |
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@eric-haibin-lin @szha Ping for one more review. |
Description
https://www.tensorflow.org/api_docs/python/tf/nn/moments
Checklist
Essentials
Please feel free to remove inapplicable items for your PR.
Changes
Comments
Related to #11283, pre-requisite of group norm implementation.
Flakiness Check: