Is there a technical reason to why strides are not supported for transpose?

TensorFlow General Discussion
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Hi, was recently reading some of the documentation for TF and in tf.transpose  |  TensorFlow v2.16.1 doc I read that tensorflow doesn’t support strides for its views.

In numpy transposes are memory-efficient constant time operations as they simply return a new view of the same data with adjusted strides.

TensorFlow does not support strides, so transpose returns a new tensor with the items permuted.

I was wondering if there a technical reasoning for why its , if it has something to do with hardware support for its Execution providers or it is just a design decision?