[libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0):  terminate called after throwing an instance of 'google::protobuf::FatalException'   what():  CHECK failed: (index) >= (0):  Aborted
CONTRIBUTOR
I remember also getting the same issue for several other translation datasets like all the iwslt2017 group, this is blokcing me and I really need to fix it and I was wondering if you have an idea on this. @lhoestq  thanks,. 
2020-12-08T09:50:02Z
https://github.com/huggingface/datasets/issues/1286#issuecomment-740511949
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2020-12-08T09:50:02Z
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CONTRIBUTOR
maybe there is an empty line or something inside these datasets? could you tell me why this is happening? thanks 
2020-12-08T10:04:32Z
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MEMBER
I just checked and the wmt16 en-ro doesn't have empty lines
```python
from datasets import load_dataset

d = load_dataset("wmt16", "ro-en", split="train")
len(d)  # 610320
len(d.filter(lambda x: len(x["translation"]["en"].strip()) > 0))  # 610320
len(d.filter(lambda x: len(x["translation"]["ro"].strip()) > 0))  # 610320
# also tested for split="validation" and "test"
```

Can you open an issue on the `transformers` repo ? also cc @sgugger 
2020-12-09T11:30:31Z
https://github.com/huggingface/datasets/issues/1286#issuecomment-741713165
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2020-12-09T11:31:45Z
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CONTRIBUTOR
Hi @lhoestq 
I am not really sure which part is causing this, to me this is more related to dataset library as this is happening for some of the datassets below please find the information to reprodcue the bug, this is really blocking me and I appreciate your help


## Environment info
- `transformers` version: 3.5.1
- Platform: GPU
- Python version: 3.7 
- PyTorch version (GPU?): 1.0.4
- Tensorflow version (GPU?): - 
- Using GPU in script?: - 
- Using distributed or parallel set-up in script?: - 

### Who can help
 tokenizers: @mfuntowicz
 Trainer: @sgugger
 TextGeneration: @TevenLeScao 
 nlp datasets: [different repo](https://github.com/huggingface/nlp)
 rust tokenizers: [different repo](https://github.com/huggingface/tokenizers)
 examples/seq2seq: @patil-suraj

## Information
Hi
I am testing seq2seq model with T5 on different datasets and this is always getting the following bug, this is really blocking me as this fails for many datasets. could you have a look please? thanks  

```
[libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): 
terminate called after throwing an instance of 'google::protobuf::FatalException'
  what():  CHECK failed: (index) >= (0): 
Aborted

```

To reproduce the error please run on 1 GPU:
```
git clone git@github.com:rabeehk/debug-seq2seq.git
python setup.py develop 
cd seq2seq 
python finetune_t5_trainer.py temp.json

```

Full output of the program:

```
(internship) rkarimi@vgnh008:/idiap/user/rkarimi/dev/debug-seq2seq/seq2seq$ python finetune_t5_trainer.py temp.json 
2020-12-12 15:38:16.234542: W tensorflow/stream_executor/platform/default/dso_loader.cc:60] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2020-12-12 15:38:16.234598: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
12/12/2020 15:38:32 - WARNING - __main__ -   Process rank: -1, device: cuda:0, n_gpu: 1, distributed training: False, 16-bits training: False
12/12/2020 15:38:32 - INFO - __main__ -   Training/evaluation parameters Seq2SeqTrainingArguments(output_dir='outputs/test', overwrite_output_dir=True, do_train=True, do_eval=True, do_predict=False, evaluate_during_training=False, evaluation_strategy=<EvaluationStrategy.NO: 'no'>, prediction_loss_only=False, per_device_train_batch_size=64, per_device_eval_batch_size=64, per_gpu_train_batch_size=None, per_gpu_eval_batch_size=None, gradient_accumulation_steps=1, eval_accumulation_steps=None, learning_rate=0.01, weight_decay=0.0, adam_beta1=0.9, adam_beta2=0.999, adam_epsilon=1e-08, max_grad_norm=1.0, num_train_epochs=2, max_steps=-1, warmup_steps=500, logging_dir='runs/Dec12_15-38-32_vgnh008', logging_first_step=True, logging_steps=200, save_steps=200, save_total_limit=1, no_cuda=False, seed=42, fp16=False, fp16_opt_level='O1', local_rank=-1, tpu_num_cores=None, tpu_metrics_debug=False, debug=False, dataloader_drop_last=False, eval_steps=200, dataloader_num_workers=0, past_index=-1, run_name='outputs/test', disable_tqdm=False, remove_unused_columns=True, label_names=None, load_best_model_at_end=False, metric_for_best_model=None, greater_is_better=None, label_smoothing=0.1, sortish_sampler=False, predict_with_generate=True, adafactor=False, encoder_layerdrop=None, decoder_layerdrop=None, dropout=None, attention_dropout=None, lr_scheduler='linear', fixed_length_emb=None, encoder_projection=None, encoder_pooling=None, projection_length=None, only_projection_bottleneck=False, concat_projection_token=False, gcs_bucket='ruse-xcloud-bucket', temperature=10, train_adapters=True, do_finetune=True, parametric_task_embedding=False, eval_output_dir='outputs/finetune-adapter/test-n-1-lr-1e-02-e-20')
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'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.weight_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_up_sampler.bias_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.weight_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.0.bias', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.weight', 'decoder.block.5.layer.2.adapter_controller.meta_down_sampler.bias_generator.1.bias', 'decoder.block.5.layer.2.adapter_controller.post_layer_norm.weight', 'decoder.block.5.layer.2.adapter_controller.post_layer_norm.bias']
You should probably TRAIN this model on a down-stream task to be able to use it for predictions and inference.
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
12/12/2020 15:38:44 - INFO - filelock -   Lock 140079090376272 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
12/12/2020 15:38:44 - INFO - filelock -   Lock 140079090376272 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
Using custom data configuration default
12/12/2020 15:38:44 - INFO - filelock -   Lock 140082549312272 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:44 - INFO - filelock -   Lock 140082549312272 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:44 - INFO - filelock -   Lock 140082549365648 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Reusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)
12/12/2020 15:38:44 - INFO - filelock -   Lock 140082549365648 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Loading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-6810ece2a440c3be.arrow
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549560848 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549560848 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
Using custom data configuration default
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549560848 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549560848 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549365200 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Reusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)
12/12/2020 15:38:45 - INFO - filelock -   Lock 140082549365200 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Loading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-9a2822394a3a4e34.arrow
12/12/2020 15:38:45 - INFO - seq2seq.metrics.metrics -   selected metric <function build_compute_metrics_fn.<locals>.classification_metrics at 0x7f66b464cc20> for task boolq
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -   ***** Running training *****
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Num examples = 10
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Num Epochs = 2
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Instantaneous batch size per device = 64
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Total train batch size (w. parallel, distributed & accumulation) = 64
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Gradient Accumulation steps = 1
12/12/2020 15:38:45 - INFO - seq2seq.trainers.trainer -     Total optimization steps = 2
{'loss': 529.79443359375, 'learning_rate': 2e-05, 'epoch': 1.0}                                                                                                                                           
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00,  2.37it/s]12/12/2020 15:38:46 - INFO - seq2seq.trainers.trainer -   

Training completed. Do not forget to share your model on huggingface.co/models =)


{'epoch': 2.0}                                                                                                                                                                                            
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:00<00:00,  2.43it/s]
12/12/2020 15:38:46 - INFO - seq2seq.trainers.trainer -   Saving model checkpoint to outputs/test
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
cahce dir  /idiap/temp/rkarimi/cache_home_1/datasets
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079084929680 acquired on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079084929680 released on /idiap/home/rkarimi/.cache/huggingface/datasets/4c7b1146606607c193d1ef601d8d0c134521b2ac59f61ee98c09119be925ee16.7ad892de9d7f1b4f9dfc598ef31e4a398a7224176bc9a3110e0e2075ff943e8f.py.lock
Using custom data configuration default
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079084929360 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079084929360 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079085355216 acquired on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Reusing dataset boolq (/idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534)
12/12/2020 15:38:59 - INFO - filelock -   Lock 140079085355216 released on /idiap/temp/rkarimi/cache_home_1/datasets/_idiap_temp_rkarimi_cache_home_1_datasets_boolq_default_0.1.0_1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534.lock
Loading cached processed dataset at /idiap/temp/rkarimi/cache_home_1/datasets/boolq/default/0.1.0/1fcfdc6f36dc89a2245ffbbd5248ab33890594b50396731ebc78411bdd2ca534/cache-164dd1d57e9fa69a.arrow
12/12/2020 15:38:59 - INFO - seq2seq.metrics.metrics -   selected metric <function build_compute_metrics_fn.<locals>.classification_metrics at 0x7f66b40c67a0> for task boolq
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -   ***** Running training *****
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Num examples = 1
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Num Epochs = 2
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Instantaneous batch size per device = 64
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Total train batch size (w. parallel, distributed & accumulation) = 64
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Gradient Accumulation steps = 1
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Total optimization steps = 2
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Continuing training from checkpoint, will skip to saved global_step
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Continuing training from epoch 2
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Continuing training from global step 2
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -     Will skip the first 0 steps in the first epoch
  0%|                                                                                                                                                                               | 0/2 [00:00<?, ?it/s]12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -   

Training completed. Do not forget to share your model on huggingface.co/models =)


{'epoch': 2.0}                                                                                                                                                                                            
  0%|                                                                                                                                                                               | 0/2 [00:00<?, ?it/s]
12/12/2020 15:38:59 - INFO - seq2seq.trainers.trainer -   Saving model checkpoint to outputs/finetune-adapter/test-n-1-lr-1e-02-e-20/boolq
12/12/2020 15:39:07 - INFO - seq2seq.utils.utils -   using task specific params for boolq: {'max_length': 3}
12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer -   ***** Running Evaluation *****
12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer -     Num examples = 3269
12/12/2020 15:39:07 - INFO - seq2seq.trainers.trainer -     Batch size = 64
100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 52/52 [00:12<00:00,  4.86it/s][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): 
terminate called after throwing an instance of 'google::protobuf::FatalException'
  what():  CHECK failed: (index) >= (0): 
Aborted
```




2020-12-12T14:44:58Z
https://github.com/huggingface/datasets/issues/1286#issuecomment-743766276
https://api.github.com/repos/huggingface/datasets/issues/1286
MDEyOklzc3VlQ29tbWVudDc0Mzc2NjI3Ng==
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2020-12-12T14:44:58Z
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CONTRIBUTOR
solved see https://github.com/huggingface/transformers/issues/9079?_pjax=%23js-repo-pjax-container 
2020-12-12T16:22:34Z
https://github.com/huggingface/datasets/issues/1286#issuecomment-743779423
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Hii please follow me
2020-12-12T19:36:21Z
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Hi
I am getting this error when evaluating on wmt16-ro-en using finetune_trainer.py of huggingface repo. thank for your help

{'epoch': 20.0}                                                                                                                                             
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 20/20 [00:16<00:00,  1.22it/s]
12/08/2020 10:41:19 - INFO - seq2seq.trainers.trainer -   Saving model checkpoint to outputs/experiment/joint/finetune/lr-2e-5
12/08/2020 10:41:24 - INFO - __main__ -   {'wmt16-en-ro': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1998), 'qnli': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 5462), 'scitail': Dataset(features: {'src_texts': Value(dtype='string', id=None), 'task': Value(dtype='string', id=None), 'tgt_texts': Value(dtype='string', id=None)}, num_rows: 1303)}
12/08/2020 10:41:24 - INFO - __main__ -   *** Evaluate ***
12/08/2020 10:41:24 - INFO - seq2seq.utils.utils -   using task specific params for wmt16-en-ro: {'max_length': 300, 'num_beams': 4}
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer -   ***** Running Evaluation *****
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer -     Num examples = 1998
12/08/2020 10:41:24 - INFO - seq2seq.trainers.trainer -     Batch size = 64
100%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 32/32 [00:37<00:00,  1.19s/it][libprotobuf FATAL /sentencepiece/src/../third_party/protobuf-lite/google/protobuf/repeated_field.h:1505] CHECK failed: (index) >= (0): 
terminate called after throwing an instance of 'google::protobuf::FatalException'
  what():  CHECK failed: (index) >= (0): 
Aborted
