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per_device instead of per_gpu/error thrown when argument unknown (#4618)

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* per_device instead of per_gpu/error thrown when argument unknown

* [docs] Restore examples.md symlink

* Correct absolute links so that symlink to the doc works correctly

* Update src/transformers/hf_argparser.py

Co-authored-by: Julien Chaumond <chaumond@gmail.com>

* Warning + reorder

* Docs

* Style

* not for squad

Co-authored-by: Julien Chaumond <chaumond@gmail.com>
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Lysandre Debut
2020-05-27 11:36:55 -04:00
committed by GitHub
parent 1381b6d01d
commit 6a17688021
10 changed files with 73 additions and 686 deletions
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examples/README.md
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@@ -16,17 +16,17 @@ This is still a work-in-progress – in particular documentation is still sparse
| Task | Example datasets | Trainer support | TFTrainer support | pytorch-lightning | Colab
|---|---|:---:|:---:|:---:|:---:|
| [**`language-modeling`**](./language-modeling) | Raw text | ✅ | - | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb)
| [**`text-classification`**](./text-classification) | GLUE, XNLI | ✅ | ✅ | ✅ | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/trainer/01_text_classification.ipynb)
| [**`token-classification`**](./token-classification) | CoNLL NER | ✅ | ✅ | ✅ | -
| [**`multiple-choice`**](./multiple-choice) | SWAG, RACE, ARC | ✅ | ✅ | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ViktorAlm/notebooks/blob/master/MPC_GPU_Demo_for_TF_and_PT.ipynb)
| [**`question-answering`**](./question-answering) | SQuAD | - | ✅ | - | -
| [**`text-generation`**](./text-generation) | - | - | - | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/02_how_to_generate.ipynb)
| [**`distillation`**](./distillation) | All | - | - | - | -
| [**`summarization`**](./summarization) | CNN/Daily Mail | - | - | - | -
| [**`translation`**](./translation) | WMT | - | - | - | -
| [**`bertology`**](./bertology) | - | - | - | - | -
| [**`adversarial`**](./adversarial) | HANS | - | - | - | -
| [**`language-modeling`**](https://github.com/huggingface/transformers/tree/master/examples/language-modeling) | Raw text | ✅ | - | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/01_how_to_train.ipynb)
| [**`text-classification`**](https://github.com/huggingface/transformers/tree/master/examples/text-classification) | GLUE, XNLI | ✅ | ✅ | ✅ | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/trainer/01_text_classification.ipynb)
| [**`token-classification`**](https://github.com/huggingface/transformers/tree/master/examples/token-classification) | CoNLL NER | ✅ | ✅ | ✅ | -
| [**`multiple-choice`**](https://github.com/huggingface/transformers/tree/master/examples/multiple-choice) | SWAG, RACE, ARC | ✅ | ✅ | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ViktorAlm/notebooks/blob/master/MPC_GPU_Demo_for_TF_and_PT.ipynb)
| [**`question-answering`**](https://github.com/huggingface/transformers/tree/master/examples/question-answering) | SQuAD | - | ✅ | - | -
| [**`text-generation`**](https://github.com/huggingface/transformers/tree/master/examples/text-generation) | - | - | - | - | [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/huggingface/blog/blob/master/notebooks/02_how_to_generate.ipynb)
| [**`distillation`**](https://github.com/huggingface/transformers/tree/master/examples/distillation) | All | - | - | - | -
| [**`summarization`**](https://github.com/huggingface/transformers/tree/master/examples/summarization) | CNN/Daily Mail | - | - | - | -
| [**`translation`**](https://github.com/huggingface/transformers/tree/master/examples/translation) | WMT | - | - | - | -
| [**`bertology`**](https://github.com/huggingface/transformers/tree/master/examples/bertology) | - | - | - | - | -
| [**`adversarial`**](https://github.com/huggingface/transformers/tree/master/examples/adversarial) | HANS | - | - | - | -
<br>
@@ -57,7 +57,7 @@ When using Tensorflow, TPUs are supported out of the box as a `tf.distribute.Str
When using PyTorch, we support TPUs thanks to `pytorch/xla`. For more context and information on how to setup your TPU environment refer to Google's documentation and to the
very detailed [pytorch/xla README](https://github.com/pytorch/xla/blob/master/README.md).
In this repo, we provide a very simple launcher script named [xla_spawn.py](./xla_spawn.py) that lets you run our example scripts on multiple TPU cores without any boilerplate.
In this repo, we provide a very simple launcher script named [xla_spawn.py](https://github.com/huggingface/transformers/tree/master/examples/xla_spawn.py) that lets you run our example scripts on multiple TPU cores without any boilerplate.
Just pass a `--num_cores` flag to this script, then your regular training script with its arguments (this is similar to the `torch.distributed.launch` helper for torch.distributed).
For example for `run_glue`: