6e58890709c68a24c2773cb744804362aef4a23b,dnc/memory.py,Memory,allocate,#Memory#Any#Any#,83

Before Change

    // essential for correct scaling of allocation_weights to prevent memory pollution
    // during write operations
    // https://discuss.pytorch.org/t/cumprod-exclusive-true-equivalences/2614/8
    v = var(T.ones(batch_size, 1))
    if self.gpu_id != -1:
      v = v.cuda(self.gpu_id)
    cat_sorted_usage = T.cat((v, sorted_usage), 1)[:, :-1]
    prod_sorted_usage = fake_cumprod(cat_sorted_usage, self.gpu_id)

    sorted_allocation_weights = (1 - sorted_usage) * prod_sorted_usage.squeeze()

After Change

    // cumprod with exclusive=True
    // https://discuss.pytorch.org/t/cumprod-exclusive-true-equivalences/2614/8
    v = var(sorted_usage.data.new(batch_size, 1).fill_(1))
    cat_sorted_usage = T.cat((v, sorted_usage), 1)
    prod_sorted_usage = T.cumprod(cat_sorted_usage, 1)[:, :-1]

Instances