code: def broadcast_prefix(
      prefix_tree: PyTree,
      full_tree: PyTree,
      is_leaf: Optional[Callable[[PyTree], bool]] = None,
  ) -> List[Any]:
      """Return a list of broadcasted leaves in ``prefix_tree`` to match the number of leaves in ``full_tree``.
  
      If a ``prefix_tree`` is a prefix of a ``full_tree``, this means the ``full_tree`` can be
      constructed by replacing the leaves of ``prefix_tree`` with appropriate **subtrees**.
  
      This function returns a list of leaves with the same size as ``full_tree``. The leaves are
      replicated from ``prefix_tree``. The number of replicas is determined by the corresponding
      subtree in ``full_tree``.
  
      >>> broadcast_prefix(1, [1, 2, 3])
      [1, 1, 1]
      >>> broadcast_prefix([1, 2, 3], [1, 2, 3])
      [1, 2, 3]
      >>> broadcast_prefix([1, 2, 3], [1, 2, 3, 4])
      Traceback (most recent call last):
          ...
      ValueError: list arity mismatch; expected: 3, got: 4; list: [1, 2, 3, 4].
      >>> broadcast_prefix([1, 2, 3], [1, 2, (3, 4)])
      [1, 2, 3, 3]
      >>> broadcast_prefix([1, 2, 3], [1, 2, {'a': 3, 'b': 4, 'c': (None, 5)}])
      [1, 2, 3, 3, 3, 3]
  
      Args:
          prefix_tree (pytree): A pytree with the same structure as a prefix of ``full_tree``.
          full_tree (pytree): A pytree with the same structure as a suffix of ``prefix_tree``.
          is_leaf (callable, optional): An extra leaf predicate function that will be called at each
              flattening step. The function should have a single argument with signature
              ``is_leaf(node) -> bool``. If it returns :data:`True`, the whole subtree being treated
              as a leaf. Otherwise, the default pytree registry will be used to determine a node is a
              leaf or not. If the function is not specified, the default pytree registry will be used.
  
      Returns:
          A list of leaves in ``prefix_tree`` broadcasted to match the number of leaves in ``full_tree``.
      """
      return optree.broadcast_prefix(
          prefix_tree,
          full_tree,
          is_leaf=is_leaf,
          none_is_leaf=True,
          namespace="torch",
      )
  
imports: import functools
  import warnings
  from typing import Any, Callable, Iterable, List, Optional, overload, Tuple, Type, TypeVar, Union
  import torch
  import optree
  from optree import PyTreeSpec
label_desc: Use image node_id 34 for calling a global function with example usage: broadcast_prefix(prefix_tree, full_tree, is_leaf) and returns: optree