'''simple docstring'''


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__					:      Optional[Any]				      =  [
    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__					:      int				      =  logging.getLogger()


def  _lowerCamelCase   (				):
     UpperCAmelCase_							:       Dict       =				argparse.ArgumentParser()
     parser.add_argument('-f'       )
     UpperCAmelCase_							:       str       =				parser.parse_args()
     return args.f


def  _lowerCamelCase   (				lowerCamelCase_ :							str     ,					lowerCamelCase_ :							Tuple="eval"       ):
     UpperCAmelCase_							:       str       =				os.path.join(lowerCamelCase_     ,					F'''{split}_results.json'''       )
     if os.path.exists(lowerCamelCase_       ):
          with open(lowerCamelCase_     ,					'r'       ) as f:
               return json.load(lowerCamelCase_       )
     raise ValueError(F'''can\'t find {path}'''       )


snake_case__					:      List[str]				      =  logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)






class 					__SCREAMING_SNAKE_CASE						(	lowerCamelCase_	):







  '''simple docstring'''






  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[Any]       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       Union[str, Any]       =				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(snake_case_				,		'argv'				,		snake_case_						):
            run_flax_glue.main()
            UpperCAmelCase_							:       List[str]       =				get_results(snake_case_						)
            self.assertGreaterEqual(result['eval_accuracy']				,		0.75						)


  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       Dict       =				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(snake_case_				,		'argv'				,		snake_case_						):
            run_clm_flax.main()
            UpperCAmelCase_							:       Optional[Any]       =				get_results(snake_case_						)
            self.assertLess(result['eval_perplexity']				,		1_0_0						)


  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       List[Any]       =				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(snake_case_				,		'argv'				,		snake_case_						):
            run_summarization_flax.main()
            UpperCAmelCase_							:       Any       =				get_results(snake_case_				,		split='test'						)
            self.assertGreaterEqual(result['test_rouge1']				,		1_0						)
            self.assertGreaterEqual(result['test_rouge2']				,		2						)
            self.assertGreaterEqual(result['test_rougeL']				,		7						)
            self.assertGreaterEqual(result['test_rougeLsum']				,		7						)


  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       str       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       str       =				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(snake_case_				,		'argv'				,		snake_case_						):
            run_mlm_flax.main()
            UpperCAmelCase_							:       Union[str, Any]       =				get_results(snake_case_						)
            self.assertLess(result['eval_perplexity']				,		4_2						)


  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       List[str]       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       Union[str, Any]       =				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(snake_case_				,		'argv'				,		snake_case_						):
            run_ta_mlm_flax.main()
            UpperCAmelCase_							:       Dict       =				get_results(snake_case_						)
            self.assertGreaterEqual(result['eval_accuracy']				,		0.42						)


  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       Optional[Any]       =				7 if get_gpu_count() > 1 else 2

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






  @slow
  def _UpperCamelCase					(			self						):




       '''simple docstring'''

       UpperCAmelCase_							:       int       =				self.get_auto_remove_tmp_dir()
       UpperCAmelCase_							:       Optional[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(snake_case_				,		'argv'				,		snake_case_						):
            run_qa.main()
            UpperCAmelCase_							:       Union[str, Any]       =				get_results(snake_case_						)
            self.assertGreaterEqual(result['eval_f1']				,		3_0						)
            self.assertGreaterEqual(result['eval_exact']				,		3_0						)







'''simple docstring'''


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     UpperCAmelCase_							:       Optional[int]       =				[0] * len(lowerCamelCase_       )

     for i in range(1     ,					len(lowerCamelCase_       )       ):
          # use last results for better performance - dynamic programming
          UpperCAmelCase_							:       List[Any]       =				prefix_result[i - 1]
          while j > 0 and input_string[i] != input_string[j]:
               UpperCAmelCase_							:       str       =				prefix_result[j - 1]

          if input_string[i] == input_string[j]:
               j += 1
          UpperCAmelCase_							:       Any       =				j

     return prefix_result


def  _lowerCamelCase   (				lowerCamelCase_ :							str       ):



     """simple docstring"""





     return max(prefix_function(lowerCamelCase_       )       )


if __name__ == "__main__":
 import doctest

 doctest.testmod()






