





'''simple docstring'''


from __future__ import annotations

import random

# Maximum size of the population.  Bigger could be faster but is more memory expensive.
a__			:					List[str]       						=						200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be smaller than N_POPULATION.
a__			:					Tuple       						=						50
# Probability that an element of a generation can mutate, changing one of its genes.
# This will guarantee that all genes will be used during evolution.
a__			:					Any       						=						0.4
# Just a seed to improve randomness required by the algorithm.
random.seed(random.randint(0, 1_000))
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			str			,	SCREAMING_SNAKE_CASE_ :			str )							->     tuple[str, float]:

       """simple docstring"""


       UpperCAmelCase  =						len([g for position, g in enumerate(SCREAMING_SNAKE_CASE_ ) if g == main_target[position]] )
       return (item, float(SCREAMING_SNAKE_CASE_ ))
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			str			,	SCREAMING_SNAKE_CASE_ :			str )							->     tuple[str, str]:

       """simple docstring"""


       UpperCAmelCase  =						random.randint(0			,	len(SCREAMING_SNAKE_CASE_ ) - 1 )
       UpperCAmelCase  =						parent_a[:random_slice] + parent_a[random_slice:]
       UpperCAmelCase  =						parent_a[:random_slice] + parent_a[random_slice:]
       return (child_a, child_a)
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			str			,	SCREAMING_SNAKE_CASE_ :			list[str] )							->     str:

       """simple docstring"""


       UpperCAmelCase  =						list(SCREAMING_SNAKE_CASE_ )
       if random.uniform(0			,	1 ) < MUTATION_PROBABILITY:
              UpperCAmelCase  =						random.choice(SCREAMING_SNAKE_CASE_ )
       return "".join(SCREAMING_SNAKE_CASE_ )
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			tuple[str, float]			,	SCREAMING_SNAKE_CASE_ :			list[tuple[str, float]]			,	SCREAMING_SNAKE_CASE_ :			list[str]			,	)							->     list[str]:

       """simple docstring"""


       UpperCAmelCase  =						[]
       # Generate more children proportionally to the fitness score.
       UpperCAmelCase  =						int(parent_a[1] * 100 ) + 1
       UpperCAmelCase  =						10 if child_n >= 10 else child_n
       for _ in range(SCREAMING_SNAKE_CASE_ ):
              UpperCAmelCase  =						population_score[random.randint(0			,	SCREAMING_SNAKE_CASE_ )][0]

              UpperCAmelCase,					UpperCAmelCase  =						crossover(parent_a[0]			,	SCREAMING_SNAKE_CASE_ )
              # Append new string to the population list.
              pop.append(mutate(SCREAMING_SNAKE_CASE_			,	SCREAMING_SNAKE_CASE_ ) )
              pop.append(mutate(SCREAMING_SNAKE_CASE_			,	SCREAMING_SNAKE_CASE_ ) )
       return pop
def       __snake_case		( SCREAMING_SNAKE_CASE_ :			str			,	SCREAMING_SNAKE_CASE_ :			list[str]			,	SCREAMING_SNAKE_CASE_ :			bool = True )							->     tuple[int, int, str]:

       """simple docstring"""


       if N_POPULATION < N_SELECTED:
              UpperCAmelCase  =						f"{N_POPULATION} must be bigger than {N_SELECTED}"
              raise ValueError(SCREAMING_SNAKE_CASE_ )
       # Verify that the target contains no genes besides the ones inside genes variable.
       UpperCAmelCase  =						sorted({c for c in target if c not in genes} )
       if not_in_genes_list:
              UpperCAmelCase  =						f"{not_in_genes_list} is not in genes list, evolution cannot converge"
              raise ValueError(SCREAMING_SNAKE_CASE_ )

       # Generate random starting population.
       UpperCAmelCase  =						[]
       for _ in range(SCREAMING_SNAKE_CASE_ ):
              population.append(''''''.join([random.choice(SCREAMING_SNAKE_CASE_ ) for i in range(len(SCREAMING_SNAKE_CASE_ ) )] ) )

       # Just some logs to know what the algorithms is doing.
       UpperCAmelCase,					UpperCAmelCase  =						0, 0

       # This loop will end when we find a perfect match for our target.
       while True:
              generation += 1
              total_population += len(SCREAMING_SNAKE_CASE_ )

              # Random population created. Now it's time to evaluate.

              # Adding a bit of concurrency can make everything faster,
              #
              # import concurrent.futures
              # population_score: list[tuple[str, float]] = []
              # with concurrent.futures.ThreadPoolExecutor(
              #                                   max_workers=NUM_WORKERS) as executor:
              #     futures = {executor.submit(evaluate, item) for item in population}
              #     concurrent.futures.wait(futures)
              #     population_score = [item.result() for item in futures]
              #
              # but with a simple algorithm like this, it will probably be slower.
              # We just need to call evaluate for every item inside the population.
              UpperCAmelCase  =						[evaluate(SCREAMING_SNAKE_CASE_			,	SCREAMING_SNAKE_CASE_ ) for item in population]

              # Check if there is a matching evolution.
              UpperCAmelCase  =						sorted(SCREAMING_SNAKE_CASE_			,	key=lambda SCREAMING_SNAKE_CASE_ : x[1]			,	reverse=SCREAMING_SNAKE_CASE_ )
              if population_score[0][0] == target:
                     return (generation, total_population, population_score[0][0])

              # Print the best result every 10 generation.
              # Just to know that the algorithm is working.
              if debug and generation % 10 == 0:
                     print(
                         f"\nGeneration: {generation}"
                         f"\nTotal Population:{total_population}"
                         f"\nBest score: {population_score[0][1]}"
                         f"\nBest string: {population_score[0][0]}" )

              # Flush the old population, keeping some of the best evolutions.
              # Keeping this avoid regression of evolution.
              UpperCAmelCase  =						population[: int(N_POPULATION / 3 )]
              population.clear()
              population.extend(SCREAMING_SNAKE_CASE_ )
              # Normalize population score to be between 0 and 1.
              UpperCAmelCase  =						[
                  (item, score / len(SCREAMING_SNAKE_CASE_ )) for item, score in population_score
              ]

              # This is selection
              for i in range(SCREAMING_SNAKE_CASE_ ):
                     population.extend(select(population_score[int(SCREAMING_SNAKE_CASE_ )]			,	SCREAMING_SNAKE_CASE_			,	SCREAMING_SNAKE_CASE_ ) )
                     # Check if the population has already reached the maximum value and if so,
                     # break the cycle.  If this check is disabled, the algorithm will take
                     # forever to compute large strings, but will also calculate small strings in
                     # a far fewer generations.
                     if len(SCREAMING_SNAKE_CASE_ ) > N_POPULATION:
                            break


if __name__ == "__main__":
    a__			:					int       						=						(
        'This is a genetic algorithm to evaluate, combine, evolve, and mutate a string!'
    )
    a__			:					Dict       						=						list(
        ' ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklm'
        'nopqrstuvwxyz.,;!?+-*#@^\'èéòà€ù=)(&%$£/\\'
    )
    a__						,		a__						,		a__			:					Optional[int]       						=						basic(target_str, genes_list)
    print(
        F"""\nGeneration: {generation}\nTotal Population: {population}\nTarget: {target}"""
    )









import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path

from requests.exceptions import HTTPError

from transformers.utils import (
    CONFIG_NAME,
    FLAX_WEIGHTS_NAME,
    TF2_WEIGHTS_NAME,
    TRANSFORMERS_CACHE,
    WEIGHTS_NAME,
    cached_file,
    get_file_from_repo,
    has_file,
)


a__: Union[str, Any]							   =						'hf-internal-testing/tiny-random-bert'
a__: Optional[int]							   =						os.path.join(TRANSFORMERS_CACHE, 'models--hf-internal-testing--tiny-random-bert')
a__: List[str]							   =						'9b8c223d42b2188cb49d29af482996f9d0f3e5a6'




class        SCREAMING_SNAKE_CASE__					(		unittest.TestCase ):



 def 							UpperCamelCase     (				self					):
        A__		   =		cached_file(__lowerCamelCase,__lowerCamelCase					)
        # Should have downloaded the file in here
        self.assertTrue(os.path.isdir(__lowerCamelCase					)					)
        # Cache should contain at least those three subfolders:
        for subfolder in ["blobs", "refs", "snapshots"]:
               self.assertTrue(os.path.isdir(os.path.join(__lowerCamelCase,__lowerCamelCase					)					)					)
        with open(os.path.join(__lowerCamelCase,'''refs''','''main'''					)					) as f:
               A__		   =		f.read()
        self.assertEqual(__lowerCamelCase,os.path.join(__lowerCamelCase,'''snapshots''',__lowerCamelCase,__lowerCamelCase					)					)
        self.assertTrue(os.path.isfile(__lowerCamelCase					)					)

        # File is cached at the same place the second time.
        A__		   =		cached_file(__lowerCamelCase,__lowerCamelCase					)
        self.assertEqual(__lowerCamelCase,__lowerCamelCase					)

        # Using a specific revision to test the full commit hash.
        A__		   =		cached_file(__lowerCamelCase,__lowerCamelCase,revision='''9b8c223'''					)
        self.assertEqual(__lowerCamelCase,os.path.join(__lowerCamelCase,'''snapshots''',__lowerCamelCase,__lowerCamelCase					)					)



 def 							UpperCamelCase     (				self					):
        with self.assertRaisesRegex(__lowerCamelCase,'''is not a valid model identifier'''					):
               A__		   =		cached_file('''tiny-random-bert''',__lowerCamelCase					)

        with self.assertRaisesRegex(__lowerCamelCase,'''is not a valid git identifier'''					):
               A__		   =		cached_file(__lowerCamelCase,__lowerCamelCase,revision='''aaaa'''					)

        with self.assertRaisesRegex(__lowerCamelCase,'''does not appear to have a file named'''					):
               A__		   =		cached_file(__lowerCamelCase,'''conf'''					)



 def 							UpperCamelCase     (				self					):
        with self.assertRaisesRegex(__lowerCamelCase,'''does not appear to have a file named'''					):
               A__		   =		cached_file(__lowerCamelCase,'''conf'''					)

        with open(os.path.join(__lowerCamelCase,'''refs''','''main'''					)					) as f:
               A__		   =		f.read()
        self.assertTrue(os.path.isfile(os.path.join(__lowerCamelCase,'''.no_exist''',__lowerCamelCase,'''conf'''					)					)					)

        A__		   =		cached_file(__lowerCamelCase,'''conf''',_raise_exceptions_for_missing_entries=__lowerCamelCase					)
        self.assertIsNone(__lowerCamelCase					)

        A__		   =		cached_file(__lowerCamelCase,'''conf''',local_files_only=__lowerCamelCase,_raise_exceptions_for_missing_entries=__lowerCamelCase					)
        self.assertIsNone(__lowerCamelCase					)

        A__		   =		mock.Mock()
        A__		   =		500
        A__		   =		{}
        A__		   =		HTTPError
        A__		   =		{}

        # Under the mock environment we get a 500 error when trying to reach the tokenizer.
        with mock.patch('''requests.Session.request''',return_value=__lowerCamelCase					) as mock_head:
               A__		   =		cached_file(__lowerCamelCase,'''conf''',_raise_exceptions_for_connection_errors=__lowerCamelCase					)
               self.assertIsNone(__lowerCamelCase					)
               # This check we did call the fake head request
               mock_head.assert_called()



 def 							UpperCamelCase     (				self					):
        self.assertTrue(has_file('''hf-internal-testing/tiny-bert-pt-only''',__lowerCamelCase					)					)
        self.assertFalse(has_file('''hf-internal-testing/tiny-bert-pt-only''',__lowerCamelCase					)					)
        self.assertFalse(has_file('''hf-internal-testing/tiny-bert-pt-only''',__lowerCamelCase					)					)



 def 							UpperCamelCase     (				self					):
        # `get_file_from_repo` returns None if the file does not exist
        self.assertIsNone(get_file_from_repo('''bert-base-cased''','''ahah.txt'''					)					)

        # The function raises if the repository does not exist.
        with self.assertRaisesRegex(__lowerCamelCase,'''is not a valid model identifier'''					):
               get_file_from_repo('''bert-base-case''',__lowerCamelCase					)

        # The function raises if the revision does not exist.
        with self.assertRaisesRegex(__lowerCamelCase,'''is not a valid git identifier'''					):
               get_file_from_repo('''bert-base-cased''',__lowerCamelCase,revision='''ahaha'''					)

        A__		   =		get_file_from_repo('''bert-base-cased''',__lowerCamelCase					)
        # The name is the cached name which is not very easy to test, so instead we load the content.
        A__		   =		json.loads(open(__lowerCamelCase,'''r'''					).read()					)
        self.assertEqual(config['''hidden_size'''],768					)




 def 							UpperCamelCase     (				self					):
        with tempfile.TemporaryDirectory() as tmp_dir:
               A__		   =		Path(__lowerCamelCase					) / '''a.txt'''
               filename.touch()
               self.assertEqual(get_file_from_repo(__lowerCamelCase,'''a.txt'''					),str(__lowerCamelCase					)					)

               self.assertIsNone(get_file_from_repo(__lowerCamelCase,'''b.txt'''					)					)





