code: def assert_no_tape_batching(tape, transform_name):
      """Check whether a tape is broadcasted and raise an error if this is the case.
  
      Args:
          tape (`~.QuantumScript`): measurements to analyze
          transform_name (str): Name of the gradient transform that queries the tape
      """
      if tape.batch_size is not None:
          raise NotImplementedError(
              f"Computing the gradient of broadcasted tapes with the {transform_name} "
              "gradient transform is currently not supported. See #4462 for details."
          )
  
imports: from functools import partial
  import warnings
  import pennylane
  from pennylane.transforms.tape_expand import expand_invalid_trainable
  from pennylane.measurements import MutualInfoMP, StateMP, VarianceMP, VnEntropyMP, ProbabilityMP
label_desc: Use image node_id 4 for calling a global function with example usage: assert_no_tape_batching(tape, transform_name) without return types