I am trying to use longt5 for summarizing task
I am using this script
and this model
I am getting this error
Traceback (most recent call last):
File “/cephfs/home/arij/Memory-transformer-with-hierarchical-attention_MLM/Summarization/run_summarization_notrainer-Copy1.py”, line 947, in
main()
File “/cephfs/home/arij/Summarization/run_summarization_notrainer-Copy1.py”, line 821, in main
outputs = model(**batch)
File “/home/arij/anaconda3/envs/lib/python3.9/site-packages/torch/nn/modules/module.py”, line 1190, in _call_impl
return forward_call(*input, **kwargs)
File “/home/arij/anaconda3/envs/lib/python3.9/site-packages/torch/nn/parallel/distributed.py”, line 1026, in forward
if torch.is_grad_enabled() and self.reducer._rebuild_buckets():
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 passing the keyword argumentfind_unused_parameters=True
totorch.nn.parallel.DistributedDataParallel
, and by
making sure allforward
function outputs participate in calculating loss.
If you already have done the above, then the distributed data parallel module wasn’t able to locate the output tensors in the return value of your module’sforward
function. Please include the loss function and the structure of the return value offorward
of your module when reporting this issue (e.g. list, dict, iterable).
Parameters which did not receive grad for rank 1: encoder.block.0.layer.0.TransientGlobalSelfAttention.global_relative_attention_bias.weight
Parameter indices which did not receive grad for rank 1: 6