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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 reset_parameters(self, init_weight):
 """ Sets initial random values for trainable parameters. """

        stdv = 1. / math.sqrt(self.num_units)
        self.linear_att.data.uniform_(-init_weight, init_weight)

        if self.normalize:
            self.normalize_scalar.data.fill_(stdv)
            self.normalize_bias.data.zero_()