code: def batch_to_time(value, dilation):
      with tf.name_scope("batch_to_time"):
          shape = tf.shape(value)
          prepared = tf.reshape(value, [dilation, -1, shape[2]])
          transposed = tf.transpose(prepared, perm=[1, 0, 2])
          return tf.reshape(
              transposed,
              [tf.math.divide(shape[0], dilation), -1, shape[2]],
          )
  
file_path: finetune/finetune/custom_ops/indico_tf_ops/python/ra.py
imports: import os
  import math
  import tensorflow
  from finetune.custom_ops.indico_tf_ops.python import indico_ops
label_desc: Use image node_id 3 for calling a global function with example usage: batch_to_time(value, dilation) and returns: tf