I have everything as in the demo notebook. When the optimization level is higher than -O2, the crash is more. The backtrace information is usually incomplete or even missing. It seems it is raising the exception because the other processes are not joining, but I have not a clue why. The error message shows Program terminated with signal SIGSEGV. usr/local/lib/python3.6/dist-packages/torch/multiprocessing/spawn.py in join(self, timeout)ġ07 "process %d terminated with signal %s" %Įxception: process 2 terminated with signal SIGSEGV usr/local/lib/python3.6/dist-packages/torch/multiprocessing/spawn.py in start_processes(fn, args, nprocs, join, daemon, start_method)ġ57 # Loop on join until it returns True or raises an exception. usr/local/lib/python3.6/dist-packages/torch_xla/distributed/xla_multiprocessing.py in spawn(fn, args, nprocs, join, daemon, start_method) > 777 xmp.spawn(self.tpu_train, args=(model,), nprocs=self.num_tpu_cores, start_method=start_method) usr/local/lib/python3.6/dist-packages/pytorch_lightning/trainer/trainer.py in fit(self, model, train_dataloader, val_dataloaders)
> 153 self.fit(model, train_dataloader=train_dataloader) usr/local/lib/python3.6/dist-packages/pytorch_lightning/trainer/lr_finder.py in lr_find(self, model, train_dataloader, min_lr, max_lr, num_training, mode, num_accumulation_steps) Exception Traceback (most recent call last)
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