509453992838a524f6442d4e0f07a034390ae1f7,layers/eight_mile/pytorch/layers.py,ConvEncoderStack,__init__,#ConvEncoderStack#Any#Any#Any#Any#Any#Any#,283

Before Change

        first_layer = ConvEncoder(insz, outsz, filtsz, pdrop, activation)
        subsequent_layer = ResidualBlock(ConvEncoder(outsz, outsz, filtsz, pdrop, activation))
        self.layers = nn.ModuleList([first_layer] + [copy.deepcopy(subsequent_layer) for _ in range(layers - 1)])
        self.output_dim = outsz

    def forward(self, input_bct: torch.Tensor) -> torch.Tensor:

After Change

        self.output_dim = outsz

        conv = Conv1DSame(insz, outsz, filtsz)
        act = get_activation(activation)
        dropout = nn.Dropout(pdrop)

        if hidden_last:
            self.conv = nn.Sequential(BTH2BHT(), conv, act, dropout, BHT2BTH())
        else:
            self.conv = nn.Sequential(conv, act, dropout)

    def forward(self, input: torch.Tensor) -> torch.Tensor:

Instances