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Say the mini-batch has $N$ samples $(x, y)$,

how will tensorflow utilize this $N$ samples to train the network.

  1. Will it do $N$ forward loop for each sample independently?
  2. Will it do $N$ backward propagation and $N$ weights update for each sample independently?
  3. Or will it average the loss from $N$ samples and then do only 1 weights update?
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  1. Loss is computed for each sample and then averaged over the entire mini-batch and the weights are updated once. Check this video (start from 6:11) for details.
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