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No performance change after Pruning MobilenetV2 based classification model with different Minimum no.of filters

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Hi,
I Pruned a Tensorflow based MobileneV2 classification model using structured pruning (BYOM Approach) with different values for the min.no.of filters per layer - specifically 8 and 16. After retraining both pruned models , I noticed no difference in performance (both accuracy and size seems nearly identical).
Why this happen, and what is the exact role of this parameter in pruning ?

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