code: def _process_jacs(jac, qhess):
      """
      Combine the classical and quantum jacobians
      """
      # Check for a Jacobian equal to the identity matrix.
      if not qml.math.is_abstract(jac):
          shape = qml.math.shape(jac)
          is_square = len(shape) == 2 and shape[0] == shape[1]
          if is_square and qml.math.allclose(
              jac, qml.numpy.eye(shape[0])
          ):
              return qhess if len(qhess) > 1 else qhess[0]
  
      hess = []
      for qh in qhess:
          if not isinstance(qh, tuple) or not isinstance(qh[0], tuple):
              # single parameter case
              qh = qml.math.expand_dims(qh, [0, 1])
          else:
              # multi parameter case
              qh = qml.math.stack([qml.math.stack(row) for row in qh])
  
          jac_ndim = len(qml.math.shape(jac))
  
          # The classical jacobian has shape (num_params, num_qnode_args)
          # The quantum Hessian has shape (num_params, num_params, output_shape)
          # contracting the quantum Hessian with the classical jacobian twice gives
          # a result with shape (num_qnode_args, num_qnode_args, output_shape)
  
          qh_indices = "ab..."
  
          # contract the first axis of the jacobian with the first and second axes of the Hessian
          first_jac_indices = f"a{ABC[2:2 + jac_ndim - 1]}"
          second_jac_indices = (
              f"b{ABC[2 + jac_ndim - 1:2 + 2 * jac_ndim - 2]}"
          )
  
          result_indices = f"{ABC[2:2 + 2 * jac_ndim - 2]}..."
          qh = qml.math.einsum(
              f"{qh_indices},{first_jac_indices},{second_jac_indices}->{result_indices}",
              qh,
              jac,
              jac,
          )
  
          hess.append(qh)
  
      return tuple(hess) if len(hess) > 1 else hess[0]
  
file_path: pennylane/pennylane/gradients/hessian_transform.py
imports: import warnings
  from string import ascii_letters
  import pennylane
  from pennylane.transforms.tape_expand import expand_invalid_trainable
label_desc: Use image node_id 1 for calling a global function with example usage: _process_jacs(jac, qhess) and returns: unknown, unknown