Embedding
class torch.nn.Embedding(num_embeddings, embedding_dim, padding_idx=None, max_norm=None, norm_type=2.0, scale_grad_by_freq=False, sparse=False, _weight=None, _freeze=False, device=None, dtype=None)
A simple lookup table that stores embeddings of a fixed dictionary
   and size.
This module is often used to store word embeddings and retrieve
   them using indices. The input to the module is a list of indices,
   and the output is the corresponding word embeddings.
Parameters:
      * num_embeddings (int) -- size of the dictionary of
        embeddings
  * **embedding_dim** (*int*) -- the size of each embedding vector

  * **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". For
    a newly constructed Embedding, the embedding vector at
