code: def timesteps(self, horizon: int) -> tf.Tensor:
          '''Returns the input tensor for the given `horizon`.'''
          start, limit, delta = horizon - 1, -1, -1
          timesteps_range = tf.range(start, limit, delta, dtype=tf.float32)
          timesteps_range = tf.expand_dims(timesteps_range, -1)
          batch_timesteps = tf.stack([timesteps_range] * self.batch_size)
          return batch_timestepf timesteps(self, horizon: int) -> tf.Tensor:
          '''Returns the input tensor for the given `horizon`.'''
          start, limit, delta = horizon - 1, -1, -1
          timesteps_range = tf.range(start, limit, delta, dtype=tf.float32)
          timesteps_range = tf.expand_dims(timesteps_range, -1)
          batch_timesteps = tf.stack([timesteps_range] * self.batch_size)
          return batch_timesteps
docs: Returns the input tensor for the given `horizon`.