logs as following, thanks
convert squad examples to features: 100%|█████████████████████████████████████████████████████████████████████████| 902/902 [00:00<00:00, 2092.37it/s]
add example index and unique id: 100%|██████████████████████████████████████████████████████████████████████████| 902/902 [00:00<00:00, 439863.06it/s]
06/14/2022 22:26:05 - INFO - main - Number of trainable params: 258,127,108
Selected optimization level O1: Insert automatic casts around Pytorch functions and Tensor methods.
Defaults for this optimization level are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Processing user overrides (additional kwargs that are not None)...
After processing overrides, optimization options are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Warning: multi_tensor_applier fused unscale kernel is unavailable, possibly because apex was installed without --cuda_ext --cpp_ext. Using Python fallback. Original ImportError was: ModuleNotFoundError("No module named 'amp_C'")
06/14/2022 22:26:05 - INFO - main - ***** Running training *****
06/14/2022 22:26:05 - INFO - main - Num examples = 1218
06/14/2022 22:26:05 - INFO - main - Num Epochs = 2
06/14/2022 22:26:05 - INFO - main - Instantaneous batch size per GPU = 48
06/14/2022 22:26:05 - INFO - main - Total train batch size (w. parallel, distributed & accumulation) = 384
06/14/2022 22:26:05 - INFO - main - Gradient Accumulation steps = 1
06/14/2022 22:26:05 - INFO - main - Total optimization steps = 8
Epoch: 0%| | 0/2 [00:00<?, ?it/s]06/14/2022 22:26:05 - INFO - main -
[Epoch 1]
06/14/2022 22:26:05 - INFO - main - Initialize pre-batch of size 2 for Epoch 1
raceback (most recent call last): | 0/4 [00:00<?, ?it/s]
File "train_rc.py", line 593, in
main()
File "train_rc.py", line 537, in main
global_step, tr_loss = train(args, train_dataset, model, tokenizer)
File "train_rc.py", line 222, in train
outputs = model(**inputs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 168, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 178, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 86, in parallel_apply
output.reraise()
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/_utils.py", line 425, in reraise
raise self.exc_type(msg)
StopIteration: Caught StopIteration in replica 0 on device 0.
Original Traceback (most recent call last):
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 61, in _worker
output = module(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd1/zhangyiming/densephrase/DensePhrases/densephrases/encoder.py", line 132, in forward
start, end = self.embed_phrase(input_ids, attention_mask, token_type_ids)
File "/ssd1/zhangyiming/densephrase/DensePhrases/densephrases/encoder.py", line 94, in embed_phrase
outputs = self.phrase_encoder(
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/transformers/modeling_bert.py", line 707, in forward
attention_mask, input_shape, self.device
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/transformers/modeling_utils.py", line 113, in device
return next(self.parameters()).device
StopIteration
logs as following, thanks
convert squad examples to features: 100%|█████████████████████████████████████████████████████████████████████████| 902/902 [00:00<00:00, 2092.37it/s]
add example index and unique id: 100%|██████████████████████████████████████████████████████████████████████████| 902/902 [00:00<00:00, 439863.06it/s]
06/14/2022 22:26:05 - INFO - main - Number of trainable params: 258,127,108
Selected optimization level O1: Insert automatic casts around Pytorch functions and Tensor methods.
Defaults for this optimization level are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Processing user overrides (additional kwargs that are not None)...
After processing overrides, optimization options are:
enabled : True
opt_level : O1
cast_model_type : None
patch_torch_functions : True
keep_batchnorm_fp32 : None
master_weights : None
loss_scale : dynamic
Warning: multi_tensor_applier fused unscale kernel is unavailable, possibly because apex was installed without --cuda_ext --cpp_ext. Using Python fallback. Original ImportError was: ModuleNotFoundError("No module named 'amp_C'")
06/14/2022 22:26:05 - INFO - main - ***** Running training *****
06/14/2022 22:26:05 - INFO - main - Num examples = 1218
06/14/2022 22:26:05 - INFO - main - Num Epochs = 2
06/14/2022 22:26:05 - INFO - main - Instantaneous batch size per GPU = 48
06/14/2022 22:26:05 - INFO - main - Total train batch size (w. parallel, distributed & accumulation) = 384
06/14/2022 22:26:05 - INFO - main - Gradient Accumulation steps = 1
06/14/2022 22:26:05 - INFO - main - Total optimization steps = 8
Epoch: 0%| | 0/2 [00:00<?, ?it/s]06/14/2022 22:26:05 - INFO - main -
[Epoch 1]
06/14/2022 22:26:05 - INFO - main - Initialize pre-batch of size 2 for Epoch 1
raceback (most recent call last): | 0/4 [00:00<?, ?it/s]
File "train_rc.py", line 593, in
main()
File "train_rc.py", line 537, in main
global_step, tr_loss = train(args, train_dataset, model, tokenizer)
File "train_rc.py", line 222, in train
outputs = model(**inputs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 168, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/data_parallel.py", line 178, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 86, in parallel_apply
output.reraise()
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/_utils.py", line 425, in reraise
raise self.exc_type(msg)
StopIteration: Caught StopIteration in replica 0 on device 0.
Original Traceback (most recent call last):
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/parallel/parallel_apply.py", line 61, in _worker
output = module(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd1/zhangyiming/densephrase/DensePhrases/densephrases/encoder.py", line 132, in forward
start, end = self.embed_phrase(input_ids, attention_mask, token_type_ids)
File "/ssd1/zhangyiming/densephrase/DensePhrases/densephrases/encoder.py", line 94, in embed_phrase
outputs = self.phrase_encoder(
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/transformers/modeling_bert.py", line 707, in forward
attention_mask, input_shape, self.device
File "/ssd3/wangxiao/anaconda3/envs/py38/lib/python3.8/site-packages/transformers/modeling_utils.py", line 113, in device
return next(self.parameters()).device
StopIteration