code: def _smallest_size_at_least(height, width, resize_min):
      resize_min = tf.cast(resize_min, tf.float32)
  
      # Convert to floats to make subsequent calculations go smoothly.
      height, width = tf.cast(height, tf.float32), tf.cast(
          width, tf.float32
      )
  
      smaller_dim = tf.minimum(height, width)
      scale_ratio = resize_min / smaller_dim
  
      # Convert back to ints to make heights and widths that TF ops will accept.
      new_height = tf.cast(height * scale_ratio, tf.int32)
      new_width = tf.cast(width * scale_ratio, tf.int32)
  
      return new_height, new_width
  
imports: from zoo.orca import init_orca_context, stop_orca_context
  import os
  import argparse
  import tensorflow
label_desc: Use image node_id 4 for calling a global function with example usage: _smallest_size_at_least(height, width, resize_min) and returns: new_height,  new_width