



"""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      UpperCAmelCase_  (    _UpperCamelCase	,      unittest.TestCase						):
						__SCREAMING_SNAKE_CASE						:       Union[str, Any]								=			None
						__SCREAMING_SNAKE_CASE						:       int								=			BloomTokenizerFast
						__SCREAMING_SNAKE_CASE						:       Dict								=			BloomTokenizerFast
						__SCREAMING_SNAKE_CASE						:       str								=			True
						__SCREAMING_SNAKE_CASE						:       Tuple								=			False
						__SCREAMING_SNAKE_CASE						:       Optional[int]								=			'tokenizer_file'
						__SCREAMING_SNAKE_CASE						:       Union[str, Any]								=			{'bos_token': '<s>', 'eos_token': '</s>', 'unk_token': '<unk>', 'pad_token': '<pad>'}



						def 						snake_case_ (					self					:     Union[str, Any]						):
											super().setUp()
											_UpperCAmelCase      :     Tuple        =   BloomTokenizerFast.from_pretrained("bigscience/tokenizer"						)
											tokenizer.save_pretrained(self.tmpdirname						)



						def 						snake_case_ (					self					:     str					,     **A					:     List[str]						):
											kwargs.update(self.special_tokens_map						)
											return BloomTokenizerFast.from_pretrained(self.tmpdirname					,     **A						)



						def 						snake_case_ (					self					:     Optional[int]						):
											_UpperCAmelCase      :     List[Any]        =   self.get_rust_tokenizer()

											_UpperCAmelCase      :     Dict        =   ["The quick brown fox</s>", "jumps over the lazy dog</s>"]
											_UpperCAmelCase      :     List[str]        =   [[2_1_7_5, 2_3_7_1_4, 7_3_1_7_3, 1_4_4_2_5_2, 2], [7_7, 1_3_2_6_1_9, 3_4_7_8, 3_6_8, 1_0_9_5_8_6, 3_5_4_3_3, 2]]

											_UpperCAmelCase      :     List[Any]        =   tokenizer.batch_encode_plus(A						)["input_ids"]
											self.assertListEqual(A					,     A						)

											_UpperCAmelCase      :     Optional[int]        =   tokenizer.batch_decode(A						)
											self.assertListEqual(A					,     A						)



						def 						snake_case_ (					self					:     Dict					,     A					:     Optional[Any]=6						):
											for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'{tokenizer.__class__.__name__} ({pretrained_name})'						):
																					_UpperCAmelCase      :     Union[str, Any]        =   self.rust_tokenizer_class.from_pretrained(A					,     **A						)
																					# tokenizer_r.pad_token = None # Hotfixing padding = None
																					# Simple input
																					_UpperCAmelCase      :     str        =   "This is a simple input"
																					_UpperCAmelCase      :     str        =   ["This is a simple input 1", "This is a simple input 2"]
																					_UpperCAmelCase      :     int        =   ("This is a simple input", "This is a pair")
																					_UpperCAmelCase      :     List[str]        =   [
																					    ("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"						)

																					_UpperCAmelCase      :     List[Any]        =   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 						snake_case_ (					self					:     int						):
											_UpperCAmelCase      :     Dict        =   self.get_rust_tokenizer()
											_UpperCAmelCase      :     Tuple        =   load_dataset("xnli"					,     "all_languages"					,     split="test"					,     streaming=A						)

											_UpperCAmelCase      :     List[Any]        =   next(iter(A						)						)["premise"]  # pick up one data
											_UpperCAmelCase      :     Optional[int]        =   list(sample_data.values()						)

											_UpperCAmelCase      :     Optional[int]        =   list(map(tokenizer.encode					,     A						)						)
											_UpperCAmelCase      :     Union[str, Any]        =   [tokenizer.decode(A					,     clean_up_tokenization_spaces=A						) for x in output_tokens]
											self.assertListEqual(A					,     A						)



						def 						snake_case_ (					self					:     Tuple						):
											# The test has to be overriden because BLOOM uses ALiBi positional embeddings that does not have
											# any sequence length constraints. This test of the parent class will fail since it relies on the
											# maximum sequence length of the positoonal embeddings.
											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 __future__ import annotations

from typing import Any

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						list[Any]    )  ->       None:





     '''simple docstring'''

     create_state_space_tree(SCREAMING_SNAKE_CASE__						,  []						,  0    )

def 						__snake_case						(				SCREAMING_SNAKE_CASE__     :						list[Any]						,  SCREAMING_SNAKE_CASE__     :						list[Any]						,  SCREAMING_SNAKE_CASE__     :						int    )  ->       None:





     '''simple docstring'''

     if index == len(SCREAMING_SNAKE_CASE__    ):
          print(SCREAMING_SNAKE_CASE__    )
          return

     create_state_space_tree(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__						,  index + 1    )
     current_subsequence.append(sequence[index]    )
     create_state_space_tree(SCREAMING_SNAKE_CASE__						,  SCREAMING_SNAKE_CASE__						,  index + 1    )
     current_subsequence.pop()


if __name__ == "__main__":
 _lowerCAmelCase    : list[Any]							=							[3, 1, 2, 4]
 generate_all_subsequences(seq)

 seq.clear()
 seq.extend(["A", "B", "C"])
 generate_all_subsequences(seq)
