def forward(self, input):
        """Input ought to have dimension (N, C_in, L_in), where L_in is the seq_len; here the input is (N, L, C)"""
        emb = self.drop(self.encoder(input))
        y = self.tcn(emb.transpose(1, 2)).transpose(1, 2)
        y = self.decoder(y)
        return y.contiguous()
Input ought to have dimension (N, C_in, L_in), where L_in is the seq_len; here the input is (N, L, C)
TCN/word_cnn/model.py