code: def _generate_diag_tapes(
      tape, idx, diag_recipes, add_unshifted, tapes, coeffs
  ):
      """Create the required parameter-shifted tapes for a single diagonal entry of
      the Hessian using precomputed second-order shift rules."""
      # pylint: disable=too-many-arguments
      # Obtain the recipe for the diagonal.
      c, m, s = diag_recipes[idx].T
      if s[0] == 0 and m[0] == 1.0:
          # Extract the unshifted coefficient, if the first shift (multiplier) equals 0 (1).
          if add_unshifted:
              # Add the unshifted tape if it has not been added yet and is required
              # because f0 was not provided (both captured by add_unshifted).
              tapes.insert(0, tape)
              add_unshifted = False
          unshifted_coeff = c[0]
          c, m, s = c[1:], m[1:], s[1:]
      else:
          unshifted_coeff = None
  
      # Create the shifted tapes for the diagonal entry and store them along with coefficients
      new_tapes = generate_shifted_tapes(tape, idx, s, m)
      tapes.extend(new_tapes)
      coeffs.append(c)
  
      return add_unshifted, unshifted_coeff
  
imports: import itertools
  import warnings
  from functools import partial
  from typing import Sequence, Callable
  import numpy
  import pennylane
  from pennylane.measurements import ProbabilityMP, StateMP, VarianceMP
  from pennylane.transforms import transform
  from .general_shift_rules import _combine_shift_rules, generate_multishifted_tapes, generate_shifted_tapes
  from .gradient_transform import find_and_validate_gradient_methods
  from .parameter_shift import _get_operation_recipe
  from .hessian_transform import _process_jacs
label_desc: Use image node_id 4 for calling a global function with example usage: _generate_diag_tapes(tape, idx, diag_recipes, add_unshifted, tapes, coeffs) and returns: add_unshifted,  unshifted_coeff