





import argparse
import json
import logging
import os
import sys
from unittest.mock import patch

from transformers.testing_utils import TestCasePlus, get_gpu_count, slow


snake_case 				=       [
    os.path.join(os.path.dirname(__file__), dirname)
    for dirname in [
        """text-classification""",
        """language-modeling""",
        """summarization""",
        """token-classification""",
        """question-answering""",
    ]
]
sys.path.extend(SRC_DIRS)


if SRC_DIRS is not None:
      import run_clm_flax
      import run_flax_glue
      import run_flax_ner
      import run_mlm_flax
      import run_qa
      import run_summarization_flax
      import run_ta_mlm_flax


logging.basicConfig(level=logging.DEBUG)

snake_case 				=       logging.getLogger()

def 							SCREAMING_SNAKE_CASE__       (  )      ->						Optional[Any]:
  _lowercase							= argparse.ArgumentParser()
  parser.add_argument('-f'     )
  _lowercase							= parser.parse_args()
  return args.f

def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :Optional[Any]			,							snake_case__  :List[Any]="eval"     )      ->						Any:
  _lowercase							= os.path.join(snake_case__			,							F"""{split}_results.json"""     )
  if os.path.exists(snake_case__     ):
    with open(snake_case__			,							'r'     ) as f:
      return json.load(snake_case__     )
  raise ValueError(F"""can't find {path}"""     )


snake_case 				=       logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)







class 				A_				(     UpperCAmelCase	):







       """simple docstring"""





       def    __UpperCAmelCase (    self	:	Any  )						->					Any:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_glue.py
            --model_name_or_path distilbert-base-uncased
            --output_dir {tmp_dir}
            --train_file ./tests/fixtures/tests_samples/MRPC/train.csv
            --validation_file ./tests/fixtures/tests_samples/MRPC/dev.csv
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --learning_rate=1e-4
            --eval_steps=2
            --warmup_steps=2
            --seed=42
            --max_seq_length=128
            """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_flax_glue.main()
           _lowercase							= get_results(__A  )
           self.assertGreaterEqual(result['eval_accuracy']						,0.75  )







       @slow
       def    __UpperCAmelCase (    self	:	Union[str, Any]  )						->					Dict:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_clm_flax.py
            --model_name_or_path distilgpt2
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --block_size 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_clm_flax.main()
           _lowercase							= get_results(__A  )
           self.assertLess(result['eval_perplexity']						,100  )







       @slow
       def    __UpperCAmelCase (    self	:	List[str]  )						->					int:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_summarization.py
            --model_name_or_path t5-small
            --train_file tests/fixtures/tests_samples/xsum/sample.json
            --validation_file tests/fixtures/tests_samples/xsum/sample.json
            --test_file tests/fixtures/tests_samples/xsum/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=8
            --do_train
            --do_eval
            --do_predict
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
            --predict_with_generate
        """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_summarization_flax.main()
           _lowercase							= get_results(__A						,split='test'  )
           self.assertGreaterEqual(result['test_rouge1']						,10  )
           self.assertGreaterEqual(result['test_rouge2']						,2  )
           self.assertGreaterEqual(result['test_rougeL']						,7  )
           self.assertGreaterEqual(result['test_rougeLsum']						,7  )







       @slow
       def    __UpperCAmelCase (    self	:	str  )						->					int:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_mlm.py
            --model_name_or_path distilroberta-base
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --logging_steps 2 --eval_steps 2
            --do_train
            --do_eval
            --num_train_epochs=1
        """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_mlm_flax.main()
           _lowercase							= get_results(__A  )
           self.assertLess(result['eval_perplexity']						,42  )







       @slow
       def    __UpperCAmelCase (    self	:	Optional[Any]  )						->					Dict:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_t5_mlm_flax.py
            --model_name_or_path t5-small
            --train_file ./tests/fixtures/sample_text.txt
            --validation_file ./tests/fixtures/sample_text.txt
            --do_train
            --do_eval
            --max_seq_length 128
            --per_device_train_batch_size 4
            --per_device_eval_batch_size 4
            --num_train_epochs 2
            --logging_steps 2 --eval_steps 2
            --output_dir {tmp_dir}
            --overwrite_output_dir
            """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_ta_mlm_flax.main()
           _lowercase							= get_results(__A  )
           self.assertGreaterEqual(result['eval_accuracy']						,0.42  )







       @slow
       def    __UpperCAmelCase (    self	:	str  )						->					Union[str, Any]:
         # with so little data distributed training needs more epochs to get the score on par with 0/1 gpu
         _lowercase							= 7 if get_gpu_count() > 1 else 2

         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_flax_ner.py
            --model_name_or_path bert-base-uncased
            --train_file tests/fixtures/tests_samples/conll/sample.json
            --validation_file tests/fixtures/tests_samples/conll/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --do_train
            --do_eval
            --warmup_steps=2
            --learning_rate=2e-4
            --logging_steps 2 --eval_steps 2
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=2
            --num_train_epochs={epochs}
            --seed 7
        """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_flax_ner.main()
           _lowercase							= get_results(__A  )
           self.assertGreaterEqual(result['eval_accuracy']						,0.75  )
           self.assertGreaterEqual(result['eval_f1']						,0.3  )







       @slow
       def    __UpperCAmelCase (    self	:	Dict  )						->					str:
         _lowercase							= self.get_auto_remove_tmp_dir()
         _lowercase							= F"""
            run_qa.py
            --model_name_or_path bert-base-uncased
            --version_2_with_negative
            --train_file tests/fixtures/tests_samples/SQUAD/sample.json
            --validation_file tests/fixtures/tests_samples/SQUAD/sample.json
            --output_dir {tmp_dir}
            --overwrite_output_dir
            --num_train_epochs=3
            --warmup_steps=2
            --do_train
            --do_eval
            --logging_steps 2 --eval_steps 2
            --learning_rate=2e-4
            --per_device_train_batch_size=2
            --per_device_eval_batch_size=1
        """.split()

         with patch.object(__A						,'argv'						,__A  ):
           run_qa.main()
           _lowercase							= get_results(__A  )
           self.assertGreaterEqual(result['eval_f1']						,30  )
           self.assertGreaterEqual(result['eval_exact']						,30  )






def 							SCREAMING_SNAKE_CASE__       (  snake_case__  :str			,							snake_case__  :int     )      ->						list[str]:
  return [sentence[i : i + ngram_size] for i in range(len(snake_case__     ) - ngram_size + 1     )]


if __name__ == "__main__":
      from doctest import testmod

      testmod()