code: def unpack_kernel_and_bias(weights):
      """Returns `kernel`, `bias` tuple."""
      if isinstance(weights, collections.abc.Mapping):
          kernel = weights.get("kernel", None)
          bias = weights.get("bias", None)
      elif len(weights) == 1:
          kernel, bias = weights, None
      elif len(weights) == 2:
          kernel, bias = weights
      else:
          raise ValueError(
              "Unable to unpack weights: {}.".format(weights)
          )
      return kernel, bias
  
imports: import collections
  import tensorflow.compat.v2
  from tensorflow_probability.python import random
  from tensorflow_probability.python.distributions import distribution
  from tensorflow_probability.python.distributions import independent
  from tensorflow_probability.python.distributions import mvn_diag
  from tensorflow_probability.python.distributions import normal
  from tensorflow_probability.python.experimental.nn import layers
  from tensorflow_probability.python.internal import prefer_static
  from tensorflow_probability.python.util.seed_stream import SeedStream
label_desc: Use image node_id 1 for calling a global function with example usage: unpack_kernel_and_bias(weights) and returns: kernel,  bias