Hello,
I get this error ‘TypeError: cannot unpack non-iterable function object’
When trying to run the training which looks as follows:
The mistake seems to be in the line that says Parallel(n_jobs=core_num)(delayed(train)(data_library[prior],data_library[target]))
> # Training
> trg_loss = []
> forward_model.train()
> with torch.set_grad_enabled(True):
> for data_library['20MHz'], data_library['100MHz'], data_library['250MHz'] in training_generator:
> if(core_num>1):
> Parallel(n_jobs=core_num)(delayed(train)(data_library[prior],data_library[target]))
> else:
> new_loss = train(data_library[prior],data_library[target])
> trg_loss.append(new_loss)
> # Parallel(n_jobs=core_num)
> # print(data_library['20MHz'].shape)
> # delayed(train)(data_library[prior],data_library[target])
> print("\nTraining Loss: ", sum(trg_loss).detach().numpy().max()/len(trg_loss))
> FILE.write("\nEpoch "+str(epoch)+": Training Loss = " +str(sum(trg_loss).detach().numpy().max()/len(trg_loss)))
All help is welcome
thanks!