code: def get_glow_hparams(self):
      hparams = glow.glow_hparams()
      hparams.add_hparam("mode", tf_estimator.ModeKeys.TRAIN)
      hparams.add_hparam("num_cond_latents", 1)
      hparams.add_hparam("latent_architecture", "glow_resnet")
      # Use latent skip connections
      hparams.add_hparam("model_input", False)
      hparams.add_hparam("latent_apply_dilations", False)
      hparams.add_hparam("latent_skip", True)
      hparams.add_hparam("latent_encoder_depth", 2)
      hparams.add_hparam("latent_encoder_width", 256)
      hparams.add_hparam("latent_pre_output_channels", 256)
      hparams.add_hparam("latent_dist_encoder", "conv_net")
      hparams.add_hparam("latent_time_filter_size", 3)
      hparams.add_hparam("latent_activation", "relu")
      hparams.add_hparam("latent_dropout", 0.0)
      hparams.add_hparam("latent_noise", 0.0)
      return hparams
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  import tempfile
  from absl.testing import parameterized
  import numpy
  from six.moves import range
  from six.moves import zip
  from tensor2tensor.models.research import glow
  from tensor2tensor.models.research import glow_ops
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import hparam
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 1 for calling the GlowOpsTest obj's underlying member method code with example usage: obj.get_glow_hparams() and returns: hparams