'''simple docstring'''





import tempfile
import unittest

from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
    get_tests_dir,
    nested_simplify,
    require_sentencepiece,
    require_tokenizers,
    require_torch,
)

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE_:     Tuple  =get_tests_dir('fixtures/test_sentencepiece.model')


if is_torch_available():
    from transformers.models.plbart.modeling_plbart import shift_tokens_right

SCREAMING_SNAKE_CASE_:     int  =5_00_03
SCREAMING_SNAKE_CASE_:     Any  =5_00_02




@require_sentencepiece
@require_tokenizers
class        __A      ( UpperCamelCase__		,	unittest.TestCase	):
    a__       :						Union[str, Any]          =  PLBartTokenizer
    a__       :						Union[str, Any]          =  None
    a__       :						Tuple          =  False



    def 					_lowercase						(self    :    int ):
         super().setUp()

         # We have a SentencePiece fixture for testing
         UpperCAmelCase_           =   PLBartTokenizer(__a   ,			language_codes="base"   ,			keep_accents=__a )
         tokenizer.save_pretrained(self.tmpdirname )



    def 					_lowercase						(self    :    List[str] ):
         UpperCAmelCase_           =   PLBartTokenizer(__a   ,			language_codes="base"   ,			keep_accents=__a )

         UpperCAmelCase_           =   tokenizer.tokenize("This is a test" )
         self.assertListEqual(__a   ,			["▁This", "▁is", "▁a", "▁t", "est"] )

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__a )   ,			[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,			)

         UpperCAmelCase_           =   tokenizer.tokenize("I was born in 92000, and this is falsé." )
         self.assertListEqual(
             __a   ,			[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "9",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "é",
                 ".",
             ]   ,			)
         UpperCAmelCase_           =   tokenizer.convert_tokens_to_ids(__a )
         self.assertListEqual(
             __a   ,			[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]   ,			)

         UpperCAmelCase_           =   tokenizer.convert_ids_to_tokens(__a )
         self.assertListEqual(
             __a   ,			[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "<unk>",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "<unk>",
                 ".",
             ]   ,			)

         UpperCAmelCase_           =   tokenizer.vocab_size
         UpperCAmelCase_           =   [tokenizer.convert_ids_to_tokens(__a ) for x in range(end - 4   ,			__a )]

         self.assertListEqual(__a   ,			["__java__", "__python__", "__en_XX__", "<mask>"] )

         UpperCAmelCase_           =   "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
         UpperCAmelCase_           =   tokenizer(__a ).input_ids
         self.assertEqual(
             tokenizer.decode(__a   ,			skip_special_tokens=__a   ,			clean_up_tokenization_spaces=__a )   ,			__a   ,			)






    def 					_lowercase						(self    :    List[str] ):
         UpperCAmelCase_           =   PLBartTokenizer(__a   ,			language_codes="multi"   ,			keep_accents=__a )

         UpperCAmelCase_           =   tokenizer.tokenize("This is a test" )
         self.assertListEqual(__a   ,			["▁This", "▁is", "▁a", "▁t", "est"] )

         self.assertListEqual(
             tokenizer.convert_tokens_to_ids(__a )   ,			[value + tokenizer.fairseq_offset for value in [285, 46, 10, 170, 382]]   ,			)

         UpperCAmelCase_           =   tokenizer.tokenize("I was born in 92000, and this is falsé." )
         self.assertListEqual(
             __a   ,			[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "9",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "é",
                 ".",
             ]   ,			)
         UpperCAmelCase_           =   tokenizer.convert_tokens_to_ids(__a )
         self.assertListEqual(
             __a   ,			[
                 value + tokenizer.fairseq_offset
                 for value in [8, 21, 84, 55, 24, 19, 7, 2, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 2, 4]
             ]   ,			)

         UpperCAmelCase_           =   tokenizer.convert_ids_to_tokens(__a )
         self.assertListEqual(
             __a   ,			[
                 SPIECE_UNDERLINE + "I",
                 SPIECE_UNDERLINE + "was",
                 SPIECE_UNDERLINE + "b",
                 "or",
                 "n",
                 SPIECE_UNDERLINE + "in",
                 SPIECE_UNDERLINE + "",
                 "<unk>",
                 "2",
                 "0",
                 "0",
                 "0",
                 ",",
                 SPIECE_UNDERLINE + "and",
                 SPIECE_UNDERLINE + "this",
                 SPIECE_UNDERLINE + "is",
                 SPIECE_UNDERLINE + "f",
                 "al",
                 "s",
                 "<unk>",
                 ".",
             ]   ,			)
         UpperCAmelCase_           =   tokenizer.vocab_size
         UpperCAmelCase_           =   [tokenizer.convert_ids_to_tokens(__a ) for x in range(end - 7   ,			__a )]

         self.assertListEqual(
             __a   ,			["__java__", "__python__", "__en_XX__", "__javascript__", "__php__", "__ruby__", "__go__"] )
         UpperCAmelCase_           =   "java.lang.Exception, python.lang.Exception, javascript, php, ruby, go"
         UpperCAmelCase_           =   tokenizer(__a ).input_ids
         self.assertEqual(
             tokenizer.decode(__a   ,			skip_special_tokens=__a   ,			clean_up_tokenization_spaces=__a )   ,			__a   ,			)




@require_torch
@require_sentencepiece
@require_tokenizers
class        __A      ( unittest.TestCase	):
    a__       :						str          =  """uclanlp/plbart-python-en_XX"""
    a__       :						List[str]          =  [
        """def maximum(a,b,c):NEW_LINE_INDENTreturn max([a,b,c])""",
        """def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])""",
    ]
    a__       :						Tuple          =  [
        """Returns the maximum value of a b c.""",
        """Sums the values of a b c.""",
    ]
    a__       :						Optional[int]          =  [
        134,
        5_452,
        33_460,
        33_441,
        33_463,
        33_465,
        33_463,
        33_449,
        988,
        20,
        33_456,
        19,
        33_456,
        771,
        39,
        4_258,
        889,
        3_318,
        33_441,
        33_463,
        33_465,
        33_463,
        33_449,
        2_471,
        2,
        PYTHON_CODE,
    ]



    @classmethod
    def 					_lowercase						(cls    :    Optional[int] ):
         UpperCAmelCase_           =   PLBartTokenizer.from_pretrained(
             cls.checkpoint_name   ,			language_codes="base"   ,			src_lang="python"   ,			tgt_lang="en_XX" )
         UpperCAmelCase_           =   1
         return cls



    def 					_lowercase						(self    :    Union[str, Any] ):
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__java__"]   ,			50001 )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__python__"]   ,			50002 )
         self.assertEqual(self.tokenizer.fairseq_tokens_to_ids["__en_XX__"]   ,			50003 )



    def 					_lowercase						(self    :    Tuple ):
         UpperCAmelCase_           =   self.tokenizer.batch_encode_plus(self.src_text ).input_ids[0]
         self.assertListEqual(self.expected_src_tokens   ,			__a )



    def 					_lowercase						(self    :    Dict ):
         self.assertIn(__a   ,			self.tokenizer.all_special_ids )
         UpperCAmelCase_           =   [EN_CODE, 9037, 33442, 57, 752, 153, 14, 56, 18, 9, 2]
         UpperCAmelCase_           =   self.tokenizer.decode(__a   ,			skip_special_tokens=__a )
         UpperCAmelCase_           =   self.tokenizer.decode(generated_ids[1:]   ,			skip_special_tokens=__a )
         self.assertEqual(__a   ,			__a )
         self.assertNotIn(self.tokenizer.eos_token   ,			__a )



    def 					_lowercase						(self    :    int ):
         UpperCAmelCase_           =   ["def sum(a,b,c):NEW_LINE_INDENTreturn sum([a,b,c])" * 20]
         self.assertIsInstance(src_text[0]   ,			__a )
         UpperCAmelCase_           =   10
         UpperCAmelCase_           =   self.tokenizer(__a   ,			max_length=__a   ,			truncation=__a ).input_ids[0]
         self.assertEqual(ids[-2]   ,			2 )
         self.assertEqual(ids[-1]   ,			__a )
         self.assertEqual(len(__a )   ,			__a )



    def 					_lowercase						(self    :    str ):
         self.assertListEqual(self.tokenizer.convert_tokens_to_ids(["<mask>", "__java__"] )   ,			[50004, 50001] )



    def 					_lowercase						(self    :    int ):
         UpperCAmelCase_           =   tempfile.mkdtemp()
         UpperCAmelCase_           =   self.tokenizer.fairseq_tokens_to_ids
         self.tokenizer.save_pretrained(__a )
         UpperCAmelCase_           =   PLBartTokenizer.from_pretrained(__a )
         self.assertDictEqual(new_tok.fairseq_tokens_to_ids   ,			__a )



    @require_torch
    def 					_lowercase						(self    :    str ):
         UpperCAmelCase_           =   self.tokenizer(self.src_text   ,			text_target=self.tgt_text   ,			padding=__a   ,			return_tensors="pt" )
         UpperCAmelCase_           =   shift_tokens_right(batch["labels"]   ,			self.tokenizer.pad_token_id )

         # fairseq batch: https://gist.github.com/sshleifer/cba08bc2109361a74ac3760a7e30e4f4
         self.assertEqual(batch.input_ids[1][-2:].tolist()   ,			[2, PYTHON_CODE] )
         self.assertEqual(batch.decoder_input_ids[1][0]   ,			__a )
         self.assertEqual(batch.decoder_input_ids[1][-1]   ,			2 )
         self.assertEqual(batch.labels[1][-2:].tolist()   ,			[2, EN_CODE] )



    @require_torch
    def 					_lowercase						(self    :    Optional[Any] ):
         UpperCAmelCase_           =   self.tokenizer(
             self.src_text   ,			text_target=self.tgt_text   ,			padding=__a   ,			truncation=__a   ,			max_length=len(self.expected_src_tokens )   ,			return_tensors="pt"   ,			)
         UpperCAmelCase_           =   shift_tokens_right(batch["labels"]   ,			self.tokenizer.pad_token_id )

         self.assertIsInstance(__a   ,			__a )

         self.assertEqual((2, 26)   ,			batch.input_ids.shape )
         self.assertEqual((2, 26)   ,			batch.attention_mask.shape )
         UpperCAmelCase_           =   batch.input_ids.tolist()[0]
         self.assertListEqual(self.expected_src_tokens   ,			__a )
         self.assertEqual(2   ,			batch.decoder_input_ids[0, -1] )  # EOS
         # Test that special tokens are reset
         self.assertEqual(self.tokenizer.prefix_tokens   ,			[] )
         self.assertEqual(self.tokenizer.suffix_tokens   ,			[self.tokenizer.eos_token_id, PYTHON_CODE] )



    def 					_lowercase						(self    :    Optional[int] ):
         UpperCAmelCase_           =   self.tokenizer(self.src_text   ,			padding=__a   ,			truncation=__a   ,			max_length=3   ,			return_tensors="pt" )
         UpperCAmelCase_           =   self.tokenizer(
             text_target=self.tgt_text   ,			padding=__a   ,			truncation=__a   ,			max_length=10   ,			return_tensors="pt" )
         UpperCAmelCase_           =   targets["input_ids"]
         UpperCAmelCase_           =   shift_tokens_right(__a   ,			self.tokenizer.pad_token_id )

         self.assertEqual(batch.input_ids.shape[1]   ,			3 )
         self.assertEqual(batch.decoder_input_ids.shape[1]   ,			10 )






    @require_torch
    def 					_lowercase						(self    :    List[Any] ):
         UpperCAmelCase_           =   self.tokenizer._build_translation_inputs(
             "A test"   ,			return_tensors="pt"   ,			src_lang="en_XX"   ,			tgt_lang="java" )

         self.assertEqual(
             nested_simplify(__a )   ,			{
                 # A, test, EOS, en_XX
                 "input_ids": [[150, 242, 2, 50003]],
                 "attention_mask": [[1, 1, 1, 1]],
                 # java
                 "forced_bos_token_id": 50001,
             }   ,			)







from __future__ import annotations

import random

# Maximum size of the population.  Bigger could be faster but is more memory expensive.
_UpperCamelCase 			=		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.
_UpperCamelCase 			=		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.
_UpperCamelCase 			=		0.4
# Just a seed to improve randomness required by the algorithm.
random.seed(random.randint(0, 1000))







def 		_lowercase (     lowercase__   ,	lowercase__						):
      __lowerCAmelCase					:						List[str]					=					len([g for position, g in enumerate(lowercase__						) if g == main_target[position]]						)
      return (item, float(lowercase__						))







def 		_lowercase (     lowercase__   ,	lowercase__						):
      __lowerCAmelCase					:						str					=					random.randint(0   ,	len(lowercase__						) - 1						)
      __lowerCAmelCase					:						int					=					parent_a[:random_slice] + parent_a[random_slice:]
      __lowerCAmelCase					:						Dict					=					parent_a[:random_slice] + parent_a[random_slice:]
      return (child_a, child_a)







def 		_lowercase (     lowercase__   ,	lowercase__						):
      __lowerCAmelCase					:						List[str]					=					list(lowercase__						)
      if random.uniform(0   ,	1						) < MUTATION_PROBABILITY:
            __lowerCAmelCase					:						int					=					random.choice(lowercase__						)
      return "".join(lowercase__						)







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__   ,	):
      __lowerCAmelCase					:						str					=					[]
      # Generate more children proportionally to the fitness score.
      __lowerCAmelCase					:						str					=					int(parent_a[1] * 1_0_0						) + 1
      __lowerCAmelCase					:						Optional[Any]					=					1_0 if child_n >= 1_0 else child_n
      for _ in range(lowercase__						):
            __lowerCAmelCase					:						List[Any]					=					population_score[random.randint(0   ,	lowercase__						)][0]

            __lowerCAmelCase,							__lowerCAmelCase					:						Dict					=					crossover(parent_a[0]   ,	lowercase__						)
            # Append new string to the population list.
            pop.append(mutate(lowercase__   ,	lowercase__						)						)
            pop.append(mutate(lowercase__   ,	lowercase__						)						)
      return pop







def 		_lowercase (     lowercase__   ,	lowercase__   ,	lowercase__ = True						):

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

      # Generate random starting population.
      __lowerCAmelCase					:						List[Any]					=					[]
      for _ in range(lowercase__						):
            population.append(''''''.join([random.choice(lowercase__						) for i in range(len(lowercase__						)						)]						)						)

      # Just some logs to know what the algorithms is doing.
      __lowerCAmelCase,							__lowerCAmelCase					:						Tuple					=					0, 0

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

            # 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.
            __lowerCAmelCase					:						Any					=					[evaluate(lowercase__   ,	lowercase__						) for item in population]

            # Check if there is a matching evolution.
            __lowerCAmelCase					:						Union[str, Any]					=					sorted(lowercase__   ,	key=lambda lowercase__						: x[1]   ,	reverse=lowercase__						)
            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 % 1_0 == 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.
            __lowerCAmelCase					:						Tuple					=					population[: int(N_POPULATION / 3						)]
            population.clear()
            population.extend(lowercase__						)
            # Normalize population score to be between 0 and 1.
            __lowerCAmelCase					:						List[Any]					=					[
                (item, score / len(lowercase__						)) for item, score in population_score
            ]

            # This is selection
            for i in range(lowercase__						):
                  population.extend(select(population_score[int(lowercase__						)]   ,	lowercase__   ,	lowercase__						)						)
                  # 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(lowercase__						) > N_POPULATION:
                        break


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


