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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def clip_by_value(t, clip_value_min, clip_value_max, name=None):
 """ A wrapper for clip_by_value that casts the clipping range if needed. """

  def cast_clip(clip):
    """
    Cast clipping range argument if needed.
    """
    if t.dtype in (tf.float32, tf.float64):
      if hasattr(clip, 'dtype'):
        # Convert to tf dtype in case this is a numpy dtype
        clip_dtype = tf.as_dtype(clip.dtype)
        if clip_dtype != t.dtype:
          return tf.cast(clip, t.dtype)
    return clip

  clip_value_min = cast_clip(clip_value_min)
  clip_value_max = cast_clip(clip_value_max)

  return tf.clip_by_value(t, clip_value_min, clip_value_max, name)