Xia Qiaolin - 优快云

错误提示：RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. This error indicates that your module has parameters that were not used in producing loss. You can enable unused parameter detection by (1) passing

Pytorch DDP would fail when using the parameters directly to calculate the loss.These are my scripts:# train.py:class Model(nn.Module): def __init__(self, params): ... self.xnli_proj = nn.Linear(dim, 3)...model = Model(params)output = model.x

Since PyTorch seems to adopt lazy way of initializing workers, this means that the actual file opening has to happen inside of thegetitemfunction of the Dataset wrapper.https://discuss.pytorch.org...

1. Pytorch's CPU's and GPU's seeds are independent. So set/save/load them independentlyhttps://discuss.pytorch.org/t/are-gpu-and-cpu-random-seeds-independent/1422. If you use randomness on several...