code: def static_num_frequencies(frequency_multipliers):
      """Statically known number of frequencies. Raises if not possible."""
  
      frequency_multipliers = tf.convert_to_tensor(
          frequency_multipliers, name="frequency_multipliers"
      )
  
      num_frequencies = tf.compat.dimension_value(
          dimension=frequency_multipliers.shape[0]
      )
  
      if num_frequencies is None:
          raise ValueError(
              "The number of frequencies must be statically known. Saw "
              "`frequency_multipliers` with shape {}".format(
                  frequency_multipliers.shape
              )
          )
  
      return num_frequencies
  
imports: import numpy
  import tensorflow.compat.v2
  from tensorflow_probability.python.bijectors import chain
  from tensorflow_probability.python.bijectors import scale
  from tensorflow_probability.python.bijectors import softplus
  from tensorflow_probability.python.distributions import linear_gaussian_ssm
  from tensorflow_probability.python.distributions import lognormal
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.internal import dtype_util
  from tensorflow_probability.python.sts.internal import util
  from tensorflow_probability.python.sts.structural_time_series import Parameter
  from tensorflow_probability.python.sts.structural_time_series import StructuralTimeSeries
label_desc: Use image node_id 2 for calling a global function with example usage: static_num_frequencies(frequency_multipliers) and returns: num_frequencies