code: def _tf_ag_dataset_all(iterable):
      # check and make sure iterable.element_spec only consists of one
      # element of tf.bool.
      specs = nest.flatten(iterable.element_spec)
      if len(specs) != 1 or specs[0].dtype != dtypes.bool:
          raise ValueError(
              'in graph mode, the "all" builtin only supports datasets '
              "that return bool scalars; got: {}".format(
                  iterable.element_spec
              )
          )
      ds = iterable.filter(math_ops.logical_not)
      ds = ds.take(1)
      ds = ds.reduce(
          constant_op.constant(True, dtype=dtypes.bool), lambda _, y: y
      )
      return ds
  
imports: from tensorflow.python.autograph.operators import control_flow
  from tensorflow.python.autograph.operators import py_builtins
  from tensorflow.python.data.experimental.ops import take_while_ops
  from tensorflow.python.data.ops import dataset_ops
  from tensorflow.python.framework import constant_op
  from tensorflow.python.framework import dtypes
  from tensorflow.python.framework import ops
  from tensorflow.python.ops import array_ops
  from tensorflow.python.ops import cond
  from tensorflow.python.ops import control_flow_assert
  from tensorflow.python.ops import gen_string_ops
  from tensorflow.python.ops import math_ops
  from tensorflow.python.util import nest
label_desc: Use image node_id 10 for calling a global function with example usage: _tf_ag_dataset_all(iterable) and returns: ds