How are the weights getting calculated as follows: -
weight = 1. / class_sample_count.float()
As per the above logic, the data points with label 0 (which form 99% of the data) have lower probability of being chosen, right? Please point out to me if I am wrong. I tried looking into WeightedRandomSampler documentation but am still confused. Thanks.