code: def in_top_k(targets, predictions, k):
      targets = targets[..., None]
      topk_values = top_k(predictions, k)[0]
      targets_values = jnp.take_along_axis(
          predictions, targets, axis=-1
      )
      mask = targets_values >= topk_values
      return jnp.any(mask, axis=1)
  
imports: import math
  import jax
  import jax.numpy
  from keras.backend import standardize_dtype
  from keras.backend.jax.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: jnp