code: def _get_fx_test_shape(
      y_train: jnp.ndarray, k_test_train: jnp.ndarray, y_axes: Axes
  ) -> tuple[int, ...]:
      if k_test_train is None:
          return y_train.shape
  
      shape = list(k_test_train.shape[::2])
      y_axes = utils.canonicalize_axis(y_axes, y_train)
      for i, c in enumerate(y_train.shape):
          if i in y_axes:
              shape.insert(i, c)
      return tuple(shape)
  
imports: import collections
  from functools import lru_cache
  from typing import Any, Callable, Generator, Iterable, NamedTuple, Optional, Protocol, Union
  import jax
  from jax import grad
  from jax.experimental import ode
  import jax.numpy
  import jax.scipy
  from jax.tree_util import tree_all
  from jax.tree_util import tree_map
  import numpy
  import scipy
  from .utils import dataclasses
  from .utils import utils
  from .utils.typing import Axes
  from .utils.typing import Get
  from .utils.typing import KernelFn
label_desc: Use image node_id 11 for calling a global function with example usage: _get_fx_test_shape(y_train, k_test_train, y_axes) and returns: tuple, y_train