4d6aeeca8a6397fb0c2ce1aa0679155c21c6cbbb,pytorch/pytorchcv/models/isqrtcovresnet.py,Triuvec,forward,#Any#Any#,115

Before Change

    @staticmethod
    def forward(ctx, input):
        x = input
        batch_size = x.data.shape[0]
        channels = x.data.shape[1]
        x = x.reshape(batch_size, channels * channels)
        identity = torch.ones(channels, channels).triu().reshape(channels * channels)
        index = identity.nonzero()
        y = torch.zeros(batch_size, channels * (channels + 1) // 2, device=x.device).type(x.dtype)
        y = x[:, index]

After Change

    
    @staticmethod
    def forward(ctx, x):
        batch, cols, rows = x.size()
        assert (cols == rows)
        n = cols
        triuvec_inds = torch.ones(n, n).triu().view(n * n).nonzero()
        // assert (len(triuvec_inds) == n * (n + 1) // 2)

Instances