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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 noam_norm(x, epsilon=1.0, name=None):
 """One version of layer normalization."""

  with tf.name_scope(name, default_name="noam_norm", values=[x]):
    shape = x.get_shape()
    ndims = len(shape)
    return (tf.nn.l2_normalize(x, ndims - 1, epsilon=epsilon) * tf.sqrt(
        to_float(shape[-1])))