code: def dataset_is_infinite(dataset):
      """True if the passed dataset is infinite."""
      if ops.executing_eagerly_outside_functions():
          return math_ops.equal(
              cardinality.cardinality(dataset), cardinality.INFINITE
          )
      else:
          dataset_size = K.get_session().run(
              cardinality.cardinality(dataset)
          )
          return dataset_size == cardinality.INFINITE
  
imports: import collections
  import copy
  import numpy
  from tensorflow.python.data.experimental.ops import cardinality
  from tensorflow.python.distribute.coordinator import cluster_coordinator
  from tensorflow.python.eager import context
  from tensorflow.python.framework import composite_tensor
  from tensorflow.python.framework import ops
  from tensorflow.python.framework import sparse_tensor
  from tensorflow.python.framework import tensor
  from tensorflow.python.framework import tensor_shape
  from tensorflow.python.framework import tensor_util
  from tensorflow.python.framework import type_spec
  from tensorflow.python.keras import backend
  from tensorflow.python.keras.engine import keras_tensor
  from tensorflow.python.keras.utils import object_identity
  from tensorflow.python.keras.utils import tf_contextlib
  from tensorflow.python.ops import math_ops
  from tensorflow.python.ops import variables
  from tensorflow.python.ops.ragged import ragged_tensor
  from tensorflow.python.ops.ragged import ragged_tensor_value
  from tensorflow.python.util import nest
label_desc: Use image node_id 19 for calling a global function with example usage: dataset_is_infinite(dataset) and returns: math_ops, unknown