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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 cos_distance(t1, t2, epsilon=1e-12, name=None):
 """Cos distance between t1 and t2 and caps the gradient of the Square Root. Args: t1: A tensor t2: A tensor that can be multiplied by t1. epsilon: A lower bound value for the distance. The square root is used as the normalizer. name: Optional name for this op. Returns: The cos distance between t1 and t2. """

  with tf.name_scope(name, 'cos_distance', [t1, t2]) as scope:
    t1 = tf.convert_to_tensor(t1, name='t1')
    t2 = tf.convert_to_tensor(t2, name='t2')
    x_inv_norm = tf.rsqrt(tf.maximum(length_squared(t1) * length_squared(t2),
                                     epsilon))
    return tf.subtract(1.0, dot_product(t1, t2) * x_inv_norm, name=scope)