code: def gene_expression_conv_base():
      """Hparams for GeneExpressionConv model."""
      hparams = common_hparams.basic_params1()
  
      batch_size = 10
      output_length = 2048
      inputs_per_output = 128
      chunk_size = 4
      input_length = output_length * inputs_per_output // chunk_size
      hparams.batch_size = input_length * batch_size
  
      hparams.dropout = 0.1
      hparams.add_hparam("num_conv_layers", 4)
      hparams.add_hparam("num_dconv_layers", 7)
      # The product of these pooling windows should match
      # input_length/target_length.
      hparams.add_hparam("pooling_windows", [2, 2, 2, 4])
  
      hparams.hidden_size = 256
      hparams.kernel_width = 20
      hparams.add_hparam("stride", 1)
      return hparams
  
file_path: tensor2tensor/tensor2tensor/models/research/gene_expression.py
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  from six.moves import range
  from tensor2tensor.layers import common_hparams
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  from tensor2tensor.utils import registry
  from tensor2tensor.utils import t2t_model
  import tensorflow.compat.v1
label_desc: Use image node_id 3 for calling a global function with example usage: gene_expression_conv_base() and returns: hparams