code: def in_top_k(targets, predictions, k):
      targets = targets[:, None]
      topk_values = top_k(predictions, k)[0]
      targets_values = np.take_along_axis(predictions, targets, axis=-1)
      mask = targets_values >= topk_values
      return np.any(mask, axis=-1)
  
imports: import numpy
  from keras.backend import standardize_dtype
  from keras.backend.jax.math import fft
  from keras.backend.jax.math import fft2
  from keras.backend.numpy.core import convert_to_tensor
  from keras.utils.module_utils import scipy
label_desc: Use image node_id 4 for calling a global function with example usage: in_top_k(targets, predictions, k) and returns: np