Method forward

slowfast/models/uniformerv2_model.py:319–330

(self, x)

        )

    def forward(self, x):
        x = self.conv1(x)  # shape = [*, width, grid, grid]
        N, C, T, H, W = x.shape
        x = x.permute(0, 2, 3, 4, 1).reshape(N * T, H * W, C)
        
        x = torch.cat([self.class_embedding.to(x.dtype) + torch.zeros(x.shape[0], 1, x.shape[-1], dtype=x.dtype, device=x.device), x], dim=1)  # shape = [*, grid ** 2 + 1, width]
        x = x + self.positional_embedding.to(x.dtype)
        x = self.ln_pre(x)

        x = x.permute(1, 0, 2)  # NLD -> LND
        out = self.transformer(x)
        return out


def inflate_weight(weight_2d, time_dim, center=True):