(shape, stddev=0.01)
return tf.Variable(tf.truncated_normal(shape, stddev=stddev))
@return A weight layer with the given shape and standard deviation. Initialized with a
            truncated normal distribution.
def w(shape, stddev=0.01):
    """
    @return A weight layer with the given shape and standard deviation. Initialized with a
            truncated normal distribution.
    """
    return tf.Variable(tf.truncated_normal(shape, stddev=stddev))
def w ( shape , stddev = 0.01 ) : return tf . Variable ( tf . truncated_normal ( shape , stddev = stddev ) )