code: def seq2img(
      original_img: jnp.ndarray, features: jnp.ndarray
  ) -> jnp.ndarray:
      """Reshapes 1D sequence to 2D image features."""
      if original_img.shape[1] == original_img.shape[2]:
          h = w = int(np.sqrt(features.shape[1]))
      else:
          stride = np.ceil(
              np.sqrt(
                  original_img.shape[1]
                  * original_img.shape[2]
                  / features.shape[1]
              )
          )
          h = np.ceil(original_img.shape[1] / stride)
          w = np.ceil(original_img.shape[2] / stride)
      return features.reshape(features.shape[0], int(h), int(w), -1)
  
imports: from typing import Any, Dict, List, Optional, Sequence, Tuple, Type, Union
  from absl import logging
  from clu import preprocess_spec
  from flax import core
  import jax
  import jax.numpy
  import numpy
  from scenic.train_lib import train_utils
  import scipy
label_desc: Use image node_id 2 for calling a global function with example usage: seq2img(original_img, features) and returns: features