code: def update_transformer_hparams_for_music(hparams):
      """Updates hparams for symbolic music modeling problems."""
      hparams.shared_embedding_and_softmax_weights = False
      hparams.symbol_modality_num_shards = 1
      hparams.label_smoothing = 0.0
  
      hparams.layer_prepostprocess_dropout = 0.1
      hparams.attention_dropout = 0.1
      hparams.relu_dropout = 0.1
  
      hparams.max_length = 0
      hparams.batch_size = 2048
  
      hparams.sampling_method = "random"
      hparams.summarize_vars = True
  
      # For local attention.
      hparams.add_hparam("block_length", 512)
  
      # For decoding.
      hparams.add_hparam("decode_output_dir", "/tmp/")
  
      # For multi-embedding aggregation in melody & performance autoencoder
      hparams.add_hparam("aggregation", "sum")
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from tensor2tensor.models import transformer
  from tensor2tensor.utils import registry
label_desc: Use image node_id 1 for calling a global function with example usage: update_transformer_hparams_for_music(hparams) without return types