dropout probability equal to "dropout". Default: 0
  * **bidirectional** -- If "True", becomes a bidirectional GRU.
    Default: "False"

Inputs: input, h_0
      * input of shape (seq_len, batch, input_size): tensor
        containing the features of the input sequence. The input can
        also be a packed variable length sequence. See
        "torch.nn.utils.rnn.pack_padded_sequence()" for details.
  * **h_0** of shape *(num_layers * num_directions, batch,
    hidden_size)*: tensor containing the initial hidden state for
    each element in the batch. Defaults to zero if not provided.
    If the RNN is bidirectional, num_directions should be 2, else
    it should be 1.

Outputs: output, h_n
      * output of shape (seq_len, batch, num_directions *
        hidden_size): tensor containing the output features h_t from
        the last layer of the GRU, for each t. If a
        "torch.nn.utils.rnn.PackedSequence" has been given as the