"input" is 1D. "offsets" determines the starting index
        position of each bag (sequence) in "input".
  * **max_norm** (*float**, **optional*) -- If given, each
    embedding vector with norm larger than "max_norm" is
    renormalized to have norm "max_norm". Note: this will modify
    "weight" in-place.

  * **norm_type** (*float**, **optional*) -- The "p" in the
    "p"-norm to compute for the "max_norm" option. Default "2".

  * **scale_grad_by_freq** (*bool**, **optional*) -- if given,
    this will scale gradients by the inverse of frequency of the
    words in the mini-batch. Default "False". Note: this option is
    not supported when "mode="max"".

  * **mode** (*str**, **optional*) -- ""sum"", ""mean"" or
    ""max"". Specifies the way to reduce the bag. Default:
    ""mean""

  * **sparse** (*bool**, **optional*) -- if "True", gradient
    w.r.t. "weight" will be a sparse tensor. See Notes under
