


indices = torch.tensor([9, 6, 5, 7, 8, 8, 9, 2, 8, 6, 6, 9, 1, 6, 8, 8, 3, 2, 3, 6, 3, 6, 5, 7, 0, 8, 4, 6, 5, 8, 2, 3])
      >>> offsets = torch.tensor([0, 19, 20, 28, 28, 32])
      >>> output = m(indices, offsets)
      >>> print(output.size())
      torch.Size([5, 12])



classmethod from_float(mod)
  Create a quantized embedding_bag module from a float module

  Parameters:
     **mod** (*Module*) -- a float module, either produced by
     torch.ao.quantization utilities or provided by user
