


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 			lowerCamelCase_		(			_SCREAMING_SNAKE_CASE       ,  unittest.TestCase   ):





				"""simple docstring"""







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



				def   lowerCAmelCase__		(						self     ):
								super().setUp()
								SCREAMING_SNAKE_CASE__     							=				BloomTokenizerFast.from_pretrained("bigscience/tokenizer"     )
								tokenizer.save_pretrained(self.tmpdirname     )



				def   lowerCAmelCase__		(						self       ,		**UpperCAmelCase__     ):
								kwargs.update(self.special_tokens_map     )
								return BloomTokenizerFast.from_pretrained(self.tmpdirname       ,		**A_     )



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.get_rust_tokenizer()

								SCREAMING_SNAKE_CASE__     							=				["The quick brown fox</s>", "jumps over the lazy dog</s>"]
								SCREAMING_SNAKE_CASE__     							=				[[2175, 2_3714, 7_3173, 14_4252, 2], [77, 13_2619, 3478, 368, 10_9586, 3_5433, 2]]

								SCREAMING_SNAKE_CASE__     							=				tokenizer.batch_encode_plus(A_     )["input_ids"]
								self.assertListEqual(A_       ,		A_     )

								SCREAMING_SNAKE_CASE__     							=				tokenizer.batch_decode(A_     )
								self.assertListEqual(A_       ,		A_     )



				def   lowerCAmelCase__		(						self       ,		UpperCAmelCase__=6     ):
								for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
												with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''     ):
																SCREAMING_SNAKE_CASE__     							=				self.rust_tokenizer_class.from_pretrained(A_       ,		**A_     )
																# tokenizer_r.pad_token = None # Hotfixing padding = None
																# Simple input
																SCREAMING_SNAKE_CASE__     							=				"This is a simple input"
																SCREAMING_SNAKE_CASE__     							=				["This is a simple input 1", "This is a simple input 2"]
																SCREAMING_SNAKE_CASE__     							=				("This is a simple input", "This is a pair")
																SCREAMING_SNAKE_CASE__     							=				[
																    ("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(A_       ,		max_length=A_     )
																				tokenizer_r.encode_plus(A_       ,		max_length=A_     )

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

																SCREAMING_SNAKE_CASE__     							=				None  # Hotfixing padding = None
																self.assertRaises(A_       ,		tokenizer_r.encode       ,		A_       ,		max_length=A_       ,		padding="max_length"     )

																# Simple input
																self.assertRaises(A_       ,		tokenizer_r.encode_plus       ,		A_       ,		max_length=A_       ,		padding="max_length"     )

																# Simple input
																self.assertRaises(
																    A_       ,		tokenizer_r.batch_encode_plus       ,		A_       ,		max_length=A_       ,		padding="max_length"       ,		)

																# Pair input
																self.assertRaises(A_       ,		tokenizer_r.encode       ,		A_       ,		max_length=A_       ,		padding="max_length"     )

																# Pair input
																self.assertRaises(A_       ,		tokenizer_r.encode_plus       ,		A_       ,		max_length=A_       ,		padding="max_length"     )

																# Pair input
																self.assertRaises(
																    A_       ,		tokenizer_r.batch_encode_plus       ,		A_       ,		max_length=A_       ,		padding="max_length"       ,		)



				def   lowerCAmelCase__		(						self     ):
								SCREAMING_SNAKE_CASE__     							=				self.get_rust_tokenizer()
								SCREAMING_SNAKE_CASE__     							=				load_dataset("xnli"       ,		"all_languages"       ,		split="test"       ,		streaming=A_     )

								SCREAMING_SNAKE_CASE__     							=				next(iter(A_     )     )["premise"]  # pick up one data
								SCREAMING_SNAKE_CASE__     							=				list(sample_data.values()     )

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






				def   lowerCAmelCase__		(						self     ):
								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"""






from transformers import BertTokenizerFast

from .custom_tokenization import CustomTokenizer


class 			lowerCamelCase_		(			lowercase   ):





				"""simple docstring"""







				_lowerCAmelCase      :      List[Any]      							=					CustomTokenizer
				pass
