code: def _broadcast_arrays(*args: ArrayLike) -> list[Array]:
      """Like Numpy's broadcast_arrays but doesn't return views."""
      shapes = [np.shape(arg) for arg in args]
      if not shapes or all(
          core.definitely_equal_shape(shapes[0], s) for s in shapes
      ):
          return [lax.asarray(arg) for arg in args]
      result_shape = lax.broadcast_shapes(*shapes)
      return [_broadcast_to(arg, result_shape) for arg in args]
  
imports: from __future__ import annotations
  from collections.abc import Sequence
  from functools import partial
  import re
  import textwrap
  from typing import Any, Callable, NamedTuple, TypeVar
  import warnings
  from jax._src import api
  from jax._src import config
  from jax._src import core
  from jax._src import dtypes
  from jax._src.lax import lax
  from jax._src.util import safe_zip, safe_map
  from jax._src.typing import Array, ArrayLike, DimSize, DType, DTypeLike, Shape
  import numpy
label_desc: Use image node_id 20 for calling a global function with example usage: _broadcast_arrays() and returns: unknown, unknown