Traceback (most recent call last):


 "/home/bjfu/anaconda3/envs/hsj-torch-gpu16/lib/python3.6/multiprocessing/process.py", line 258, in _bootstrap

self.run()


 "/home/bjfu/anaconda3/envs/hsj-torch-gpu16/lib/python3.6/multiprocessing/process.py", line 93, in run

self._target(*self._args, **self._kwargs)


 "train.py", line 279, in init_processes

torch.cuda.set_device(args.local_rank)


 "/home/bjfu/anaconda3/envs/hsj-torch-gpu16/lib/python3.6/site-packages/torch/cuda/__init__.py", line 281, in set_device

torch._C._cuda_setDevice(device)
RuntimeError: cuda runtime error (101) : invalid device ordinal at /pytorch/torch/csrc/cuda/Module.cpp:59

Traceback (most recent call last):


 "main.py", line 16, in <module>

main(sys.argv[1:])


 "/usr/home/studenti/sp193030/jiant/jiant/__main__.py", line 588, in main

phase="pretrain",


 "/usr/home/studenti/sp193030/jiant/jiant/trainer.py", line 671, in train

all_val_metrics, should_save, new_best = self._validate(n_val, tasks, batch_size)


 "/usr/home/studenti/sp193030/jiant/jiant/trainer.py", line 953, in _validate

task, task_infos, tasks, batch_size, all_val_metrics, n_examples_overall


 "/usr/home/studenti/sp193030/jiant/jiant/trainer.py", line 843, in _calculate_validation_performance

out = self._forward(batch, task=task)


 "/usr/home/studenti/sp193030/jiant/jiant/trainer.py", line 1043, in _forward

model_out = self._model.forward(task, batch)


 "/usr/home/studenti/sp193030/jiant/jiant/models.py", line 855, in forward

out = self._pair_sentence_forward(batch, task, predict)


 "/usr/home/studenti/sp193030/jiant/jiant/models.py", line 1010, in _pair_sentence_forward

logits = classifier(sent, mask, [batch["idx1"], batch["idx2"]])


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__

result = self.forward(*input, **kwargs)


 "/usr/home/studenti/sp193030/jiant/jiant/modules/simple_modules.py", line 149, in forward

logits = self.classifier(final_emb)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__

result = self.forward(*input, **kwargs)


 "/usr/home/studenti/sp193030/jiant/jiant/modules/simple_modules.py", line 83, in forward

logits = self.classifier(seq_emb)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__

result = self.forward(*input, **kwargs)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/container.py", line 92, in forward

input = module(input)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/module.py", line 489, in __call__

result = self.forward(*input, **kwargs)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/modules/linear.py", line 67, in forward

return F.linear(input, self.weight, self.bias)


 "/usr/home/studenti/sp193030/.conda/envs/jiant/lib/python3.6/site-packages/torch/nn/functional.py", line 1352, in linear

ret = torch.addmm(torch.jit._unwrap_optional(bias), input, weight.t())
RuntimeError: size mismatch, m1: [8 x 2048], m2: [1536 x 32] at /opt/conda/conda-bld/pytorch_1549630534704/work/aten/src/THC/generic/THCTensorMathBlas.cu:266
