code: def _check_fun(fun, d, *args, **kwargs):
      """Check shapes."""
      want_shape = d.shape
      d = fun(d, *args, **kwargs)
      if not isinstance(d, np.ndarray):
          raise TypeError("Return value must be an ndarray")
      if d.shape != want_shape:
          raise ValueError(
              f"Return data must have shape {want_shape} not {d.shape}"
          )
      return d
  
imports: from collections import Counter
  from copy import deepcopy
  from functools import partial
  from math import gcd
  import numpy
  from scipy import fft, signal
  from scipy.stats import f
  from ._fiff.pick import _picks_to_idx
  from ._ola import _COLA
  from .cuda import _fft_multiply_repeated, _fft_resample, _setup_cuda_fft_multiply_repeated, _setup_cuda_fft_resample, _smart_pad
  from .parallel import parallel_func
  from .utils import _check_option, _check_preload, _ensure_int, _pl, _validate_type, logger, sum_squared, verbose, warn
label_desc: Use image node_id 33 for calling a global function with example usage: _check_fun(fun, d) and returns: d