"torch.nn.Embedding" for more details regarding sparse
        gradients. Note: this option is not supported when
        "mode="max"".
  * **per_sample_weights** (*Tensor**, **optional*) -- a tensor of
    float / double weights, or None to indicate all weights should
    be taken to be 1. If specified, "per_sample_weights" must have
    exactly the same shape as input and is treated as having the
    same "offsets", if those are not None.

  * **include_last_offset** (*bool**, **optional*) -- if "True",
    the size of offsets is equal to the number of bags + 1. The
    last element is the size of the input, or the ending index
    position of the last bag (sequence).

  * **padding_idx** (*int**, **optional*) -- If specified, the
    entries at "padding_idx" do not contribute to the gradient;
    therefore, the embedding vector at "padding_idx" is not
    updated during training, i.e. it remains as a fixed "pad".
