code: def get_dilation_rates(hparams, width):
      """Get a list of valid dilation rates.
  
      Args:
        hparams: HParams.
        width: spatial dimension. Ensures that the effective filter size is
               not larger than the spatial dimension.
      Returns:
        allowed_dilations: A list of dilation rates.
      """
      # dil_rate=1 means no dilation.
      allowed_dilations = [[1] * 5]
      apply_dilations = hparams.get("latent_apply_dilations", False)
      dilation_rates = hparams.get("latent_dilation_rates", [1, 3])
      if apply_dilations:
          for rate in dilation_rates:
              # k + (k - 1) * rate but k is harcoded to be 3 everywhere.
              filter_size = 3 + 2 * rate
              if filter_size <= width:
                  curr_dilation = [1, 1, rate + 1, rate + 1, 1]
                  allowed_dilations.append(curr_dilation)
      return allowed_dilations
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import functools
  import numpy
  import scipy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.layers import common_video
  from tensor2tensor.utils import contrib
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
  import tensorflow_probability
label_desc: Use image node_id 26 for calling a global function with example usage: get_dilation_rates(hparams, width) and returns: allowed_dilations