def forward()

in level_replay/model.py [0:0]


    def forward(self, input):
        if self.padding == "VALID":
            return F.conv2d(
                input,
                self.weight,
                self.bias,
                self.stride,
                padding=0,
                dilation=self.dilation,
                groups=self.groups,
            )
        rows_odd, padding_rows = self._compute_padding(input, dim=0)
        cols_odd, padding_cols = self._compute_padding(input, dim=1)
        if rows_odd or cols_odd:
            input = F.pad(input, [0, cols_odd, 0, rows_odd])

        return F.conv2d(
            input,
            self.weight,
            self.bias,
            self.stride,
            padding=(padding_rows // 2, padding_cols // 2),
            dilation=self.dilation,
            groups=self.groups,
        )