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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 the
keyword argument `find_unused_parameters=True` to `torch.nn.parallel.DistributedDataParallel`; (2) making sure all `forward`
function outputs participate in calculating loss. If you already have done the above two steps, then the distributed data parallel
module wasn't able to locate the output tensors in the return value of your module's `forward` function. Please include the loss
function and the structure of the return value of `forward` of your module when reporting this issue (e.g. list, dict, iterable).
Could you let me know if I am missing something while running this command ?
The text was updated successfully, but these errors were encountered:
No need to use distributed multi-GPUs to train, turn off distributed multi-card training (i.e., torch.nn.parallel.DistributedDataParallel() is redundant).
I am getting the following error when I run OadTR train command.
Could you let me know if I am missing something while running this command ?
The text was updated successfully, but these errors were encountered: