



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


__lowerCamelCase         =			[
    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)

__lowerCamelCase         =			logging.getLogger()







def    _snake_case (       )     ->     str:






      '''simple docstring'''







      UpperCAmelCase_  :	Any				      =		argparse.ArgumentParser()
      parser.add_argument("-f"    )
      UpperCAmelCase_  :	List[str]				      =		parser.parse_args()
      return args.f







def    _snake_case (       __snake_case					,  __snake_case="eval"    )     ->     Any:






      '''simple docstring'''







      UpperCAmelCase_  :	Any				      =		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}"""    )


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





class   snake_case_ (lowercase__  ):




       """simple docstring"""






       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Tuple				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	List[str]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_flax_glue.main()
                   UpperCAmelCase_  :	Tuple				      =		get_results(lowercase)
                   self.assertGreaterEqual(result["eval_accuracy"]     ,0.75)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	str				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	List[str]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_clm_flax.main()
                   UpperCAmelCase_  :	int				      =		get_results(lowercase)
                   self.assertLess(result["eval_perplexity"]     ,100)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[Any]				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	Optional[int]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_summarization_flax.main()
                   UpperCAmelCase_  :	Dict				      =		get_results(lowercase     ,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  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	List[str]				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	Optional[Any]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_mlm_flax.main()
                   UpperCAmelCase_  :	int				      =		get_results(lowercase)
                   self.assertLess(result["eval_perplexity"]     ,42)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Tuple				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	Optional[int]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_ta_mlm_flax.main()
                   UpperCAmelCase_  :	int				      =		get_results(lowercase)
                   self.assertGreaterEqual(result["eval_accuracy"]     ,0.42)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	str				      =		7 if get_gpu_count() > 1 else 2

             UpperCAmelCase_  :	List[Any]				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	List[Any]				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_flax_ner.main()
                   UpperCAmelCase_  :	Any				      =		get_results(lowercase)
                   self.assertGreaterEqual(result["eval_accuracy"]     ,0.75)
                   self.assertGreaterEqual(result["eval_f1"]     ,0.3)



       @slow
       def  A_   (     self):

             """simple docstring"""





             UpperCAmelCase_  :	Tuple				      =		self.get_auto_remove_tmp_dir()
             UpperCAmelCase_  :	Any				      =		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(lowercase     ,"argv"     ,lowercase):
                   run_qa.main()
                   UpperCAmelCase_  :	List[Any]				      =		get_results(lowercase)
                   self.assertGreaterEqual(result["eval_f1"]     ,30)
                   self.assertGreaterEqual(result["eval_exact"]     ,30)





def    _snake_case (       __snake_case					,  __snake_case    )     ->     str:






      '''simple docstring'''







      if a < 0 or b < 0:
            raise ValueError("the value of both inputs must be positive"    )

      UpperCAmelCase_  :	List[Any]				      =		str(bin(__snake_case    )    )[2:]  # remove the leading "0b"
      UpperCAmelCase_  :	int				      =		str(bin(__snake_case    )    )[2:]  # remove the leading "0b"

      UpperCAmelCase_  :	Optional[int]				      =		max(len(__snake_case    )					,  len(__snake_case    )    )

      return "0b" + "".join(
          str(int(char_a == "1" and char_b == "1"    )    )
          for char_a, char_b in zip(a_binary.zfill(__snake_case    )					,  b_binary.zfill(__snake_case    )    )    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()
