
from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


_lowerCamelCase	:    Union[str, Any]          =      logging.get_logger(__name__)

_lowerCamelCase	:    Union[str, Any]          =      {'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_lowerCamelCase	:    Any          =      {
    '''vocab_file''': {
        '''allegro/herbert-base-cased''': '''https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''allegro/herbert-base-cased''': '''https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt'''
    },
}

_lowerCamelCase	:    str          =      {'''allegro/herbert-base-cased''': 514}
_lowerCamelCase	:    Dict          =      {}




class        SCREAMING_SNAKE_CASE__					(     UpperCAmelCase ):





	'''simple docstring'''



	_UpperCAmelCase	:		Optional[int]          = VOCAB_FILES_NAMES
	_UpperCAmelCase	:		Optional[Any]          = PRETRAINED_VOCAB_FILES_MAP
	_UpperCAmelCase	:		Optional[int]          = PRETRAINED_INIT_CONFIGURATION
	_UpperCAmelCase	:		Optional[int]          = PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
	_UpperCAmelCase	:		List[Any]          = HerbertTokenizer



	def __init__(  self     :   str      ,  lowercase     :   str=None      ,  lowercase     :   Any=None      ,  lowercase     :   Any=None      ,  lowercase     :   List[Any]="<s>"      ,  lowercase     :   Union[str, Any]="<unk>"      ,  lowercase     :   Optional[Any]="<pad>"      ,  lowercase     :   Union[str, Any]="<mask>"      ,  lowercase     :   str="</s>"      ,  **lowercase     :   List[Any]      ,  ):


				'''simple docstring'''


				super().__init__(
				    lowercase      ,  lowercase      ,  tokenizer_file=lowercase      ,  cls_token=lowercase      ,  unk_token=lowercase      ,  pad_token=lowercase      ,  mask_token=lowercase      ,  sep_token=lowercase      ,  **lowercase      ,  )



	def 			A							(  self     :   Optional[int]      ,  lowercase     :   List[int]      ,  lowercase     :   Optional[List[int]] = None     ):


				'''simple docstring'''


				_snake_case          =      [self.cls_token_id]
				_snake_case          =      [self.sep_token_id]
				if token_ids_a is None:
							return cls + token_ids_a + sep

				return cls + token_ids_a + sep + token_ids_a + sep



	def 			A							(  self     :   Dict      ,  lowercase     :   List[int]      ,  lowercase     :   Optional[List[int]] = None      ,  lowercase     :   bool = False     ):


				'''simple docstring'''


				if already_has_special_tokens:
							return super().get_special_tokens_mask(
							    token_ids_a=lowercase      ,  token_ids_a=lowercase      ,  already_has_special_tokens=lowercase     )

				if token_ids_a is None:
							return [1] + ([0] * len(lowercase     )) + [1]
				return [1] + ([0] * len(lowercase     )) + [1] + ([0] * len(lowercase     )) + [1]



	def 			A							(  self     :   Union[str, Any]      ,  lowercase     :   List[int]      ,  lowercase     :   Optional[List[int]] = None     ):


				'''simple docstring'''


				_snake_case          =      [self.sep_token_id]
				_snake_case          =      [self.cls_token_id]

				if token_ids_a is None:
							return len(cls + token_ids_a + sep     ) * [0]
				return len(cls + token_ids_a + sep     ) * [0] + len(token_ids_a + sep     ) * [1]





	def 			A							(  self     :   str      ,  lowercase     :   str      ,  lowercase     :   Optional[str] = None     ):


				'''simple docstring'''


				_snake_case          =      self._tokenizer.model.save(lowercase      ,  name=lowercase     )
				return tuple(lowercase     )

import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch

from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search

from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS


logging.basicConfig(level=logging.DEBUG)
_lowerCamelCase	:    Union[str, Any]          =      logging.getLogger()






def 	a_		(	__lowercase       :     Path	, __lowercase       :     list			)			->  Tuple:
			_snake_case          =      '\n'.join(__lowercase			)
			Path(__lowercase			).open('w'			).writelines(__lowercase			)


_lowerCamelCase	:    Any          =      '''patrickvonplaten/t5-tiny-random'''
_lowerCamelCase	:    List[Any]          =      '''sshleifer/bart-tiny-random'''
_lowerCamelCase	:    List[Any]          =      '''sshleifer/tiny-mbart'''

_lowerCamelCase	:    Union[str, Any]          =      logging.StreamHandler(sys.stdout)
logger.addHandler(stream_handler)
logging.disable(logging.CRITICAL)  # remove noisy download output from tracebacks




class        SCREAMING_SNAKE_CASE__					(     UpperCAmelCase ):





	'''simple docstring'''



	def 			A							(  self     :   Optional[int]      ,  lowercase     :   int     ):


				'''simple docstring'''


				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     ) / 'utest_input.source'
				_snake_case          =      input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()
				_snake_case          =      [' New York (CNN)When Liana Barrientos was 23 years old, she got married in Westchester County.']
				_dump_articles(lowercase      ,  lowercase     )

				_snake_case          =      str(Path(self.get_auto_remove_tmp_dir()     ) / 'scores.json'     )
				_snake_case          =      'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case          =      f'''
            run_eval_search.py
            {model}
            {input_file_name}
            {output_file_name}
            --score_path {score_path}
            --task {task}
            --num_beams 2
            --length_penalty 2.0
            '''.split()

				with patch.object(lowercase      ,  'argv'      ,  lowercase     ):
							run_generate()
							assert Path(lowercase     ).exists()
							# os.remove(Path(output_file_name))



	def 			A							(  self     :   List[Any]     ):


				'''simple docstring'''


				self.run_eval_tester(lowercase     )



	@parameterized.expand([BART_TINY, MBART_TINY]     )
	@slow
	def 			A							(  self     :   Any      ,  lowercase     :   int     ):


				'''simple docstring'''


				self.run_eval_tester(lowercase     )





	@parameterized.expand([T5_TINY, MBART_TINY]     )
	@slow
	def 			A							(  self     :   Any      ,  lowercase     :   str     ):


				'''simple docstring'''


				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     ) / 'utest_input.source'
				_snake_case          =      input_file_name.parent / 'utest_output.txt'
				assert not output_file_name.exists()

				_snake_case          =      {
				    'en': ['Machine learning is great, isn\'t it?', 'I like to eat bananas', 'Tomorrow is another great day!'],
				    'de': [
				        'Maschinelles Lernen ist großartig, oder?',
				        'Ich esse gerne Bananen',
				        'Morgen ist wieder ein toller Tag!',
				    ],
				}

				_snake_case          =      Path(self.get_auto_remove_tmp_dir()     )
				_snake_case          =      str(tmp_dir / 'scores.json'     )
				_snake_case          =      str(tmp_dir / 'val.target'     )
				_dump_articles(lowercase      ,  text['en']     )
				_dump_articles(lowercase      ,  text['de']     )
				_snake_case          =      'translation_en_to_de' if model == T5_TINY else 'summarization'
				_snake_case          =      f'''
            run_eval_search.py
            {model}
            {str(lowercase     )}
            {str(lowercase     )}
            --score_path {score_path}
            --reference_path {reference_path}
            --task {task}
            '''.split()
				testargs.extend(['--search', 'num_beams=1:2 length_penalty=0.9:1.0']     )

				with patch.object(lowercase      ,  'argv'      ,  lowercase     ):
							with CaptureStdout() as cs:
										run_search()
							_snake_case          =      [' num_beams | length_penalty', model, 'Best score args']
							_snake_case          =      ['Info']
							if "translation" in task:
										expected_strings.append('bleu'     )
							else:
										expected_strings.extend(lowercase     )
							for w in expected_strings:
										assert w in cs.out
							for w in un_expected_strings:
										assert w not in cs.out
							assert Path(lowercase     ).exists()
							os.remove(Path(lowercase     )     )