code: def make_taco2_args(**kwargs):
      defaults = dict(
          use_speaker_embedding=False,
          spk_embed_dim=None,
          embed_dim=32,
          elayers=1,
          eunits=32,
          econv_layers=2,
          econv_filts=5,
          econv_chans=32,
          dlayers=2,
          dunits=32,
          prenet_layers=2,
          prenet_units=32,
          postnet_layers=2,
          postnet_filts=5,
          postnet_chans=32,
          output_activation=None,
          atype="location",
          adim=32,
          aconv_chans=16,
          aconv_filts=5,
          cumulate_att_w=True,
          use_batch_norm=True,
          use_concate=True,
          use_residual=False,
          dropout_rate=0.5,
          zoneout_rate=0.1,
          reduction_factor=1,
          threshold=0.5,
          maxlenratio=5.0,
          minlenratio=0.0,
          use_cbhg=False,
          spc_dim=None,
          cbhg_conv_bank_layers=4,
          cbhg_conv_bank_chans=32,
          cbhg_conv_proj_filts=3,
          cbhg_conv_proj_chans=32,
          cbhg_highway_layers=4,
          cbhg_highway_units=32,
          cbhg_gru_units=32,
          use_masking=True,
          use_weighted_masking=False,
          bce_pos_weight=1.0,
          use_guided_attn_loss=False,
          guided_attn_loss_sigma=0.4,
          guided_attn_loss_lambda=1.0,
      )
      defaults.update(kwargs)
      return defaults
  
file_path: espnet/test/test_e2e_tts_tacotron2.py
imports: from __future__ import division, print_function
  from argparse import Namespace
  import numpy
  import pytest
  import torch
  from espnet.nets.pytorch_backend.e2e_tts_tacotron2 import Tacotron2
  from espnet.nets.pytorch_backend.nets_utils import pad_list
label_desc: Use image node_id 1 for calling a global function with example usage: make_taco2_args() and returns: defaults