code: def _hparams_from_flags():
      """Instantiate hparams based on flags set in FLAGS."""
      keys = """
        dataset quantization_level num_instruments separate_instruments
        crop_piece_len architecture use_sep_conv num_initial_regular_conv_layers
        sep_conv_depth_multiplier num_dilation_blocks dilate_time_only
        repeat_last_dilation_level num_layers num_filters use_residual
        batch_size maskout_method mask_indicates_context optimize_mask_only
        rescale_loss patience corrupt_ratio eval_freq run_id
        num_pointwise_splits interleave_split_every_n_layers
        """.split()
      hparams = lib_hparams.Hyperparameters(
          **dict((key, getattr(FLAGS, key)) for key in keys)
      )
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import time
  from magenta.models.coconet import lib_data
  from magenta.models.coconet import lib_graph
  from magenta.models.coconet import lib_hparams
  from magenta.models.coconet import lib_util
  import numpy
  import six
  from six.moves import range
  from six.moves import zip
  import tensorflow.compat.v1
label_desc: Use image node_id 5 for calling a global function with example usage: _hparams_from_flags() and returns: hparams