class_docstr: Implementation for https://arxiv.org/pdf/1712.05884.pdf
class_docstr_tok: ["Implementation","for","https",":","\/\/arxiv.org\/pdf\/1712.05884.pdf"]
code: def add_args(parser):
      # encoder
      parser.add_argument("--encoder-dropout", type=float)
      parser.add_argument("--encoder-embed-dim", type=int)
      parser.add_argument("--encoder-conv-layers", type=int)
      parser.add_argument("--encoder-conv-kernel-size", type=int)
      parser.add_argument("--encoder-lstm-layers", type=int)
      # decoder
      parser.add_argument("--attention-dim", type=int)
      parser.add_argument("--attention-conv-dim", type=int)
      parser.add_argument("--attention-conv-kernel-size", type=int)
      parser.add_argument("--prenet-dropout", type=float)
      parser.add_argument("--prenet-layers", type=int)
      parser.add_argument("--prenet-dim", type=int)
      parser.add_argument("--postnet-dropout", type=float)
      parser.add_argument("--postnet-layers", type=int)
      parser.add_argument("--postnet-conv-dim", type=int)
      parser.add_argument("--postnet-conv-kernel-size", type=int)
      parser.add_argument("--init-attn-c", type=str)
      parser.add_argument(
          "--attention-use-cumprob", action="store_true"
      )
      parser.add_argument("--zoneout", type=float)
      parser.add_argument("--decoder-lstm-layers", type=int)
      parser.add_argument("--decoder-lstm-dim", type=int)
      parser.add_argument("--output-frame-dim", type=int)
  
imports: import logging
  import torch
  from torch import nn
  from torch.nn import functional
  from fairseq.models import FairseqEncoder, FairseqEncoderDecoderModel, FairseqIncrementalDecoder, register_model, register_model_architecture
  from fairseq.modules import LSTMCellWithZoneOut, LocationAttention
label_desc: Use image node_id 1 for calling the Tacotron2Model obj's underlying member method code with example usage: obj.add_args(parser) without return types