Comments (12)
Hi ! Thanks for reporting this issue with wikicorpus
, we implemented a fix in huggingface/datasets#2844
from lightseq.
Maybe you can try to change this line?
from lightseq.
I already downloaded the dataset to disk using https://github.com/NVIDIA/DeepLearningExamples/blob/master/PyTorch/LanguageModeling/BERT/data/create_datasets_from_start.sh. I am wondering how to use those data ? Thanks !
from lightseq.
I got following error with dataset "wikicorpus"
CMD: python3.7 -m torch.distributed.launch
--nproc_per_node=1
$THIS_DIR/run_ner.py
--model_name_or_path bert-large-uncased
--dataset_name wikicorpus
--dataset_config_name raw_en
--output_dir ./test-ner-no-wikicorpus
--cache_dir ./cache-wikicorpus
--do_train
--do_eval
--num_train_epochs 1
Error message:
Downloading and preparing dataset wikicorpus/raw_en (download: 1.25 GiB, generated: 3.16 GiB, post-processed: Unknown size, total: 4.41 GiB) to ./cache-wikicorpus/wikicorpus/raw_en/0.0.0/8665d716c08f102e87fdbb711326cbdf12c7ce810962819f1c71ca294d722774...
Downloading: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1.35G/1.35G [15:12<00:00, 1.48MB/s]
Traceback (most recent call last):
File "/usr/local/lib/python3.7/dist-packages/datasets/builder.py", line 1103, in _prepare_split
writer.write(example, key)
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 342, in write
self.check_duplicate_keys()
File "/usr/local/lib/python3.7/dist-packages/datasets/arrow_writer.py", line 353, in check_duplicate_keys
raise DuplicatedKeysError(key)
datasets.keyhash.DuplicatedKeysError: FAILURE TO GENERATE DATASET !
Found duplicate Key: 519
Keys should be unique and deterministic in nature
During handling of the above exception, another exception occurred:
from lightseq.
It seems a dataset error, not lightseq's error. Anyway, you can try to delete the cache.
from lightseq.
I tried several times, but the error is same, could you have a look ?
from lightseq.
I tried several times, but the error is same, could you have a look ?
You can check huggingface/datasets#2552
from lightseq.
Hi! I run the example:
sh examples/training/huggingface/run_ner.sh
but get the error:
RuntimeError: CUDA out of memory. Tried to allocate 50.00 MiB (GPU 0; 15.78 GiB total capacity; 7.21 GiB already allocated; 45.75 MiB free; 7.53 GiB reserved in total by PyTorch)
0%|
How can I solve it?
from lightseq.
when I set per_device_train_batch_size=1, get the error:
File "/usr/local/python3.7.0/lib/python3.7/site-packages/lightseq/training/ops/pytorch/transformer_encoder_layer.py", line 288, in forward
assert bs == encoder_padding_mask.size(0) and sl == encoder_padding_mask.size(1)
AssertionError
from lightseq.
This error is caused by the wrong padding mask shape, anyway, batch_size=1 is not usual.
If you encounter GPU out of memory, besides decreasing your batch_size, remember to set smaller max_batch_tokens in lightseq layer config, it will also influence GPU memory usage
from lightseq.
When I set max_batch_tokens=1024 in ls_hf_transformer_encoder_layer.py, I still get the following error:
f"Batch token numbers {bs * sl} exceeds the limit {self.config.max_batch_tokens}."
ValueError: Batch token numbers 1344 exceeds the limit 1024.
May I change this place?
from lightseq.
from lightseq.
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from lightseq.