

"""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


SCREAMING_SNAKE_CASE_					:	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)

SCREAMING_SNAKE_CASE_					:	Any							  =						logging.getLogger()





def  _snake_case     (    ):
     A__										=  argparse.ArgumentParser()
     parser.add_argument("""-f"""			)
     A__										=  parser.parse_args()
     return args.f





def  _snake_case     (    UpperCAmelCase_  :					str					,   UpperCAmelCase_  :					Optional[Any]="eval"			):
     A__										=  os.path.join(UpperCAmelCase_					,   F"""{split}_results.json"""			)
     if os.path.exists(UpperCAmelCase_			):
          with open(UpperCAmelCase_					,   """r"""			) as f:
               return json.load(UpperCAmelCase_			)
     raise ValueError(F"""can't find {path}"""			)


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



class 					a						(       _lowerCamelCase				):



    """simple docstring"""



    def 				UpperCamelCase	(     self: List[str]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_flax_glue.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertGreaterEqual(result["""eval_accuracy"""]    ,						0.75       )

    @slow
    def 				UpperCamelCase	(     self: Optional[Any]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_clm_flax.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertLess(result["""eval_perplexity"""]    ,						1_00       )

    @slow
    def 				UpperCamelCase	(     self: Optional[Any]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_summarization_flax.main()
              A__										=  get_results(UpperCamelCase    ,						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: Union[str, Any]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_mlm_flax.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertLess(result["""eval_perplexity"""]    ,						42       )

    @slow
    def 				UpperCamelCase	(     self: List[Any]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_ta_mlm_flax.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertGreaterEqual(result["""eval_accuracy"""]    ,						0.42       )

    @slow
    def 				UpperCamelCase	(     self: List[str]       ):






         """simple docstring"""


         A__										=  7 if get_gpu_count() > 1 else 2

         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_flax_ner.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertGreaterEqual(result["""eval_accuracy"""]    ,						0.75       )
              self.assertGreaterEqual(result["""eval_f1"""]    ,						0.3       )





    @slow
    def 				UpperCamelCase	(     self: List[Any]       ):






         """simple docstring"""


         A__										=  self.get_auto_remove_tmp_dir()
         A__										=  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(UpperCamelCase    ,						"""argv"""    ,						UpperCamelCase       ):
              run_qa.main()
              A__										=  get_results(UpperCamelCase       )
              self.assertGreaterEqual(result["""eval_f1"""]    ,						30       )
              self.assertGreaterEqual(result["""eval_exact"""]    ,						30       )









"""simple docstring"""



from __future__ import annotations



class 					a						:



    """simple docstring"""



    def __init__(     self: Any    ,						UpperCamelCase: str    ,						UpperCamelCase: str       ):






         """simple docstring"""


         A__			,				A__										=  text, pattern
         A__			,				A__										=  len(UpperCamelCase       ), len(UpperCamelCase       )

    def 				UpperCamelCase	(     self: Dict    ,						UpperCamelCase: str       ):






         """simple docstring"""


         for i in range(self.patLen - 1    ,						-1    ,						-1       ):
              if char == self.pattern[i]:
                   return i
         return -1

    def 				UpperCamelCase	(     self: str    ,						UpperCamelCase: int       ):






         """simple docstring"""


         for i in range(self.patLen - 1    ,						-1    ,						-1       ):
              if self.pattern[i] != self.text[current_pos + i]:
                   return current_pos + i
         return -1





    def 				UpperCamelCase	(     self: List[Any]       ):






         """simple docstring"""


         A__										=  []
         for i in range(self.textLen - self.patLen + 1       ):
              A__										=  self.mismatch_in_text(UpperCamelCase       )
              if mismatch_index == -1:
                   positions.append(UpperCamelCase       )
              else:
                   A__										=  self.match_in_pattern(self.text[mismatch_index]       )
                   A__										=  (
                       mismatch_index - match_index
                   )  # shifting index lgtm [py/multiple-definition]
         return positions

SCREAMING_SNAKE_CASE_					:	List[Any]							  =						'ABAABA'
SCREAMING_SNAKE_CASE_					:	List[Any]							  =						'AB'
SCREAMING_SNAKE_CASE_					:	Union[str, Any]							  =						BoyerMooreSearch(text, pattern)
SCREAMING_SNAKE_CASE_					:	int							  =						bms.bad_character_heuristic()

if len(positions) == 0:
 print('No match found')
else:
 print('Pattern found in following positions: ')
 print(positions)






