





"""simple docstring"""



import unittest

from datasets import load_dataset

from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers

from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase      ,				unittest.TestCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							str							=					None
				SCREAMING_SNAKE_CASE_:							List[str]							=					BloomTokenizerFast
				SCREAMING_SNAKE_CASE_:							List[str]							=					BloomTokenizerFast
				SCREAMING_SNAKE_CASE_:							Any							=					True
				SCREAMING_SNAKE_CASE_:							List[Any]							=					False
				SCREAMING_SNAKE_CASE_:							Optional[int]							=					"tokenizer_file"
				SCREAMING_SNAKE_CASE_:							str							=					{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "pad_token": "<pad>"}


				def 				__lowerCamelCase	(					self	:			Tuple  )		->  str:







											"""simple docstring"""




											super().setUp()
											_lowerCAmelCase  	=			BloomTokenizerFast.from_pretrained('bigscience/tokenizer'  )
											tokenizer.save_pretrained(self.tmpdirname  )


				def 				__lowerCamelCase	(					self	:			List[str]				,     **UpperCAmelCase_	:			Any  )		->  Optional[Any]:







											"""simple docstring"""




											kwargs.update(self.special_tokens_map  )
											return BloomTokenizerFast.from_pretrained(self.tmpdirname				,     **UpperCAmelCase_  )


				def 				__lowerCamelCase	(					self	:			List[Any]  )		->  str:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_rust_tokenizer()

											_lowerCAmelCase  	=			['The quick brown fox</s>', 'jumps over the lazy dog</s>']
											_lowerCAmelCase  	=			[[2_175, 23_714, 73_173, 144_252, 2], [77, 132_619, 3_478, 368, 109_586, 35_433, 2]]

											_lowerCAmelCase  	=			tokenizer.batch_encode_plus(UpperCAmelCase_  )['input_ids']
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )

											_lowerCAmelCase  	=			tokenizer.batch_decode(UpperCAmelCase_  )
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )


				def 				__lowerCamelCase	(					self	:			Any				,     UpperCAmelCase_	:			List[str]=6  )		->  Any:







											"""simple docstring"""




											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																		with self.subTest(F"""{tokenizer.__class__.__name__} ({pretrained_name})"""  ):
																									_lowerCAmelCase  	=			self.rust_tokenizer_class.from_pretrained(UpperCAmelCase_				,     **UpperCAmelCase_  )
																									# tokenizer_r.pad_token = None # Hotfixing padding = None
																									# Simple input
																									_lowerCAmelCase  	=			'This is a simple input'
																									_lowerCAmelCase  	=			['This is a simple input 1', 'This is a simple input 2']
																									_lowerCAmelCase  	=			('This is a simple input', 'This is a pair')
																									_lowerCAmelCase  	=			[
																									    ('This is a simple input 1', 'This is a simple input 2'),
																									    ('This is a simple pair 1', 'This is a simple pair 2'),
																									]

																									# Simple input tests
																									try:
																																tokenizer_r.encode(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )

																																tokenizer_r.batch_encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.encode(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																																tokenizer_r.batch_encode_plus(UpperCAmelCase_				,     max_length=UpperCAmelCase_  )
																									except ValueError:
																																self.fail('Bloom Tokenizer should be able to deal with padding'  )

																									_lowerCAmelCase  	=			None  # Hotfixing padding = None
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Simple input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Simple input
																									self.assertRaises(
																									    UpperCAmelCase_				,     tokenizer_r.batch_encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'				,     )

																									# Pair input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Pair input
																									self.assertRaises(UpperCAmelCase_				,     tokenizer_r.encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'  )

																									# Pair input
																									self.assertRaises(
																									    UpperCAmelCase_				,     tokenizer_r.batch_encode_plus				,     UpperCAmelCase_				,     max_length=UpperCAmelCase_				,     padding='max_length'				,     )


				def 				__lowerCamelCase	(					self	:			str  )		->  Any:







											"""simple docstring"""




											_lowerCAmelCase  	=			self.get_rust_tokenizer()
											_lowerCAmelCase  	=			load_dataset('xnli'				,     'all_languages'				,     split='test'				,     streaming=UpperCAmelCase_  )

											_lowerCAmelCase  	=			next(iter(UpperCAmelCase_  )  )['premise']  # pick up one data
											_lowerCAmelCase  	=			list(sample_data.values()  )

											_lowerCAmelCase  	=			list(map(tokenizer.encode				,     UpperCAmelCase_  )  )
											_lowerCAmelCase  	=			[tokenizer.decode(UpperCAmelCase_				,     clean_up_tokenization_spaces=UpperCAmelCase_  ) for x in output_tokens]
											self.assertListEqual(UpperCAmelCase_				,     UpperCAmelCase_  )







				def 				__lowerCamelCase	(					self	:			Tuple  )		->  List[Any]:







											"""simple docstring"""




											self.assertGreaterEqual(len(self.tokenizer_class.pretrained_vocab_files_map  )				,     1  )
											self.assertGreaterEqual(len(list(self.tokenizer_class.pretrained_vocab_files_map.values()  )[0]  )				,     1  )








"""simple docstring"""



import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict

from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase							)
class        _SCREAMING_SNAKE_CASE  (  UpperCAmelCase							):






				'''simple docstring'''



				SCREAMING_SNAKE_CASE_:							str							=					field(default="image-classification"      ,				metadata={"include_in_asdict_even_if_is_default": True}							)
				SCREAMING_SNAKE_CASE_:							ClassVar[Features]							=					Features({"image": Image()}							)
				SCREAMING_SNAKE_CASE_:							ClassVar[Features]							=					Features({"labels": ClassLabel}							)
				SCREAMING_SNAKE_CASE_:							str							=					"image"
				SCREAMING_SNAKE_CASE_:							str							=					"labels"


				def 				__lowerCamelCase	(					self	:			str				,     UpperCAmelCase_	:			Optional[Any]  )		->  Dict:







											"""simple docstring"""




											if self.label_column not in features:
																		raise ValueError(F"""Column {self.label_column} is not present in features."""  )
											if not isinstance(features[self.label_column]				,     UpperCAmelCase_  ):
																		raise ValueError(F"""Column {self.label_column} is not a ClassLabel."""  )
											_lowerCAmelCase  	=			copy.deepcopy(self  )
											_lowerCAmelCase  	=			self.label_schema.copy()
											_lowerCAmelCase  	=			features[self.label_column]
											_lowerCAmelCase  	=			label_schema
											return task_template







				@property
				def 				__lowerCamelCase	(					self	:			Union[str, Any]  )		->  Dict[str, str]:







											"""simple docstring"""




											return {
											    self.image_column: "image",
											    self.label_column: "labels",
											}






