performing a weighted reduction as specified by "mode". If
   "per_sample_weights" is passed, the only supported "mode" is
   ""sum"", which computes a weighted sum according to
   "per_sample_weights".
Parameters:
      * num_embeddings (int) -- size of the dictionary of
        embeddings
  * **embedding_dim** (*int*) -- the size of each embedding vector

  * **max_norm** (*float**, **optional*) -- If given, each
    embedding vector with norm larger than "max_norm" is
    renormalized to have norm "max_norm".

  * **norm_type** (*float**, **optional*) -- The p of 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
