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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):
 """Reinitiate the weight parameters. """


        stdv = 1.0 / math.sqrt(self.num_features)
        self.weight.weight.data.uniform_(-stdv, stdv)
        if self.bias is not None:
            self.bias.data.uniform_(-stdv, stdv)
        if self.padding_idx is not None:
            self.weight.weight.data[self.padding_idx].fill_(0)