* Reorganize example folder
* Continue reorganization
* Change requirements for tests
* Final cleanup
* Finish regroup with tests all passing
* Copyright
* Requirements and readme
* Make a full link for the documentation
* Address review comments
* Apply suggestions from code review
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
* Add symlink
* Reorg again
* Apply suggestions from code review
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Adapt title
* Update to new strucutre
* Remove test
* Update READMEs
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Thomas Wolf <thomwolf@users.noreply.github.com>
* Put models in subfolders
* Styling
* Fix imports in tests
* More fixes in test imports
* Sneaky hidden imports
* Fix imports in doc files
* More sneaky imports
* Finish fixing tests
* Fix examples
* Fix path for copies
* More fixes for examples
* Fix dummy files
* More fixes for example
* More model import fixes
* Is this why you're unhappy GitHub?
* Fix imports in conver command
* Allow tests in examples to use cuda or fp16,if they are available
The tests in examples didn't use the cuda or fp16 even if they where available.
- The text classification example (`run_glue.py`) didn't use the fp16 even if it was available but
the device was take based on the availablity(cuda/cpu).
- The language-modeling example (`run_language_modeling.py`) was having `--no_cuda` argument
which made the test to work without cuda. This example is having issue when running with fp16
thus it not enabled (got an assertion error for perplexity due to it higher value).
- The cuda and fp16 is not enabled for question-answering example (`run_squad.py`) as it is having a
difference in the f1 score.
- The text-generation example (`run_generation.py`) will take the cuda or fp16 whenever it is available.
Resolves some of: #5057
* Unwanted import of is_apex_available was removed
* Made changes to test examples file to have the pass --fp16 only if cuda and apex is avaliable
- run_glue.py: Removed the check for cuda and fp16.
- run_generation.py: Removed the check for cuda and fp16 also removed unwanted flag creation.
* Incorrectly sorted imports fixed
* The model needs to be converted to half precision
* Formatted single line if condition statement to multiline
* The torch_device also needed to be checked before running the test on examples
- The tests in examples which uses cuda should also depend from the USE_CUDA flag,
similarly to the rest of the test suite. Even if we decide to set USE_CUDA to
True by default, setting USE_CUDA to False should result in the examples not using CUDA
* Format some of the code in test_examples file
* The improper import of is_apex_available was sorted
* Formatted the code to keep the style standards
* The comma at the end of list giving a flake8 issue was fixed
* Import sort was fixed
* Removed the clean_test_dir function as its not used right now
* Created using Colaboratory
* [examples] reorganize files
* remove run_tpu_glue.py as superseded by TPU support in Trainer
* Bugfix: int, not tuple
* move files around
