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* Initial support for Unitxt datasets in LM Eval Harness

See  https://github.com/IBM/unitxt



The script 'generate_yamls.py' creates LM Eval Harness yaml files corresponding to Unitxt datasets specified in the 'unitxt_datasets' file.

The glue code required to register Unitxt metrics is in 'unitxt_wrapper.py'.

* Added dataset loading check to generate_yaml

Improved error messages.

* Speed up generate_yaml

Added printouts and improved error message

* Added output printout

* Simplified integration of unitxt datasets

Store all the common yaml configuration in a yaml include shared by all datasets of the same task.

* Post code review comments - part 1

1. Made sure include files don't end wth 'yaml' so they won't be marked as tasks
2. Added more datasets and tasks (NER, GEC)
3. Added README

* Post code review comments - part 2

1. Added install unitxt install option in pyproject.toml:
pip install 'lm_eval[unitxt]'
2. Added a check that unitxt is installed and print a clear error message if not

* Commited missing pyproject change

* Added documentation on adding datasets

* More doc changes

* add unitxt extra to readme

* run precommit

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Co-authored-by: haileyschoelkopf <hailey@eleuther.ai>

* fix auto-batch size bug for seq2seq models

* alphabetize task + group tables ; fix eval tracker bug

* fix eval tracker bug

* add Hendrycks MATH (no sympy checking) variant

* add readmes for MATH tasks

* Added fewshot sampling seeds to evaluator.simple_evaluate signature

Way to control seed of fewshot sampling
may help with #1591

* Added ability for custom sampler for ConfigurableTask

May be set in config like
```
fewshot_config:
  sampler: !function utils.MyFewshotSampler
```

* explicitly set fewshot random generator seed for HFLM generate_until_task test

* add backward compatibility for three args seed setup

* save seeds info to logs/reports

* remove echo parameter in OpenAI completions API

* remove context length parameter doc string