Packing of pruned model with 65% sparsity

TensorFlow General Discussion
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We have designed a custom packer to pack the sparsity in pruned models for specific target hardwares. After pruning, when the model is exported to .h5 format, the size of model is dropping significantly.

  1. Why is this the case as the number of weights are still same(though 65% are 0s) and precision is float32 ?
  2. Is there any compression inherently happening in storing the data in h5 format ?
  3. If there is some compression/sparsity packing happening while saving the model in h5, how can we stop it so it retains the original size of the model ?

Thanks in advance. :blush: