def init_weights()

in torchmoji/model_def.py [0:0]

• 13 lines of code
• 11 McCabe index (conditional complexity)

    def init_weights(self):
        """
        Here we reproduce Keras default initialization weights for consistency with Keras version
        """
        ih = (param.data for name, param in self.named_parameters() if 'weight_ih' in name)
        hh = (param.data for name, param in self.named_parameters() if 'weight_hh' in name)
        b = (param.data for name, param in self.named_parameters() if 'bias' in name)
        nn.init.uniform(self.embed.weight.data, a=-0.5, b=0.5)
        for t in ih:
            nn.init.xavier_uniform(t)
        for t in hh:
            nn.init.orthogonal(t)
        for t in b:
            nn.init.constant(t, 0)
        if not self.feature_output:
            nn.init.xavier_uniform(self.output_layer[0].weight.data)