seer_mer:

This causes difference since normalized = (data - mean) / std = (data - mean) / sqrt(variance),
which therefore causes difference in resulting standardized data, the pytorch version results in data ranging in approximately (-2.1, 2.2), while tensorflow version results in data ranging in approximately (-1.0, 1.1).


You could check the stddev and variance of the resulting tensor and make sure it has a unit variance (=1), which is the purpose of this normalization/standardization step.
I’m not familiar with the TF implementation and don’t know what internally is used.