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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 blur_input_each_step():
 """Minimizing this objective is equivelant to blurring input each step. Optimizing (-k)*blur_input_each_step() is equivelant to: input <- (1-k)*input + k*blur(input) An operation that was used in early feature visualization work. See Nguyen, et al., 2015. """

  def inner(T):
    t_input = T("input")
    t_input_blurred = tf.stop_gradient(_tf_blur(t_input))
    return 0.5*tf.reduce_sum((t_input - t_input_blurred)**2)
  return inner