






"""simple docstring"""

import unittest

from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowercase    			=       get_tests_dir('''fixtures/test_sentencepiece.model''')

@require_sentencepiece
@require_tokenizers
class 						A_							(      snake_case_					,							unittest.TestCase  ):
				UpperCAmelCase__        =				ReformerTokenizer
				UpperCAmelCase__        =				ReformerTokenizerFast
				UpperCAmelCase__        =				True
				UpperCAmelCase__        =				False
				UpperCAmelCase__        =				True







				def     _snake_case					(							self							:						Optional[Any]	)				->					Any:
										super().setUp()

										__magic_name__            =     ReformerTokenizer(__lowerCamelCase						,    keep_accents=__lowerCamelCase	)
										tokenizer.save_pretrained(self.tmpdirname	)







				def     _snake_case					(							self							:						List[str]	)				->					Tuple:
										__magic_name__            =     "<s>"
										__magic_name__            =     1

										self.assertEqual(self.get_tokenizer()._convert_token_to_id(__lowerCamelCase	)						,    __lowerCamelCase	)
										self.assertEqual(self.get_tokenizer()._convert_id_to_token(__lowerCamelCase	)						,    __lowerCamelCase	)







				def     _snake_case					(							self							:						Optional[int]	)				->					str:
										__magic_name__            =     list(self.get_tokenizer().get_vocab().keys()	)

										self.assertEqual(vocab_keys[0]						,    "<unk>"	)
										self.assertEqual(vocab_keys[1]						,    "<s>"	)
										self.assertEqual(vocab_keys[-1]						,    "j"	)
										self.assertEqual(len(__lowerCamelCase	)						,    1_0_0_0	)







				def     _snake_case					(							self							:						str	)				->					List[str]:
										self.assertEqual(self.get_tokenizer().vocab_size						,    1_0_0_0	)







				def     _snake_case					(							self							:						Tuple	)				->					int:
										if not self.test_rust_tokenizer:
																return

										__magic_name__            =     self.get_tokenizer()
										__magic_name__            =     self.get_rust_tokenizer()

										__magic_name__            =     "I was born in 92000, and this is falsé."

										__magic_name__            =     tokenizer.tokenize(__lowerCamelCase	)
										__magic_name__            =     rust_tokenizer.tokenize(__lowerCamelCase	)
										self.assertListEqual(__lowerCamelCase						,    __lowerCamelCase	)

										__magic_name__            =     tokenizer.encode(__lowerCamelCase						,    add_special_tokens=__lowerCamelCase	)
										__magic_name__            =     rust_tokenizer.encode(__lowerCamelCase						,    add_special_tokens=__lowerCamelCase	)
										self.assertListEqual(__lowerCamelCase						,    __lowerCamelCase	)

										__magic_name__            =     self.get_rust_tokenizer()
										__magic_name__            =     tokenizer.encode(__lowerCamelCase	)
										__magic_name__            =     rust_tokenizer.encode(__lowerCamelCase	)
										self.assertListEqual(__lowerCamelCase						,    __lowerCamelCase	)







				def     _snake_case					(							self							:						Tuple						,    __lowerCamelCase							:						Optional[int]=1_5	)				->					int:
										for tokenizer, pretrained_name, kwargs in self.tokenizers_list:
																with self.subTest(f'''{tokenizer.__class__.__name__} ({pretrained_name})'''	):
																						__magic_name__            =     self.rust_tokenizer_class.from_pretrained(__lowerCamelCase						,    **__lowerCamelCase	)

																						# Simple input
																						__magic_name__            =     "This is a simple input"
																						__magic_name__            =     ["This is a simple input 1", "This is a simple input 2"]
																						__magic_name__            =     ("This is a simple input", "This is a pair")
																						__magic_name__            =     [
																						    ("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
																						self.assertRaises(__lowerCamelCase						,    tokenizer_r.encode						,    __lowerCamelCase						,    max_length=__lowerCamelCase						,    padding="max_length"	)

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

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

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

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

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







				def     _snake_case					(							self							:						List[Any]	)				->					Any:
										pass







				def     _snake_case					(							self							:						Tuple	)				->					List[str]:
										__magic_name__            =     ReformerTokenizer(__lowerCamelCase						,    keep_accents=__lowerCamelCase	)

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

										self.assertListEqual(
										    tokenizer.convert_tokens_to_ids(__lowerCamelCase	)						,    [2_8_5, 4_6, 1_0, 1_7_0, 3_8_2]						,    )

										__magic_name__            =     tokenizer.tokenize("I was born in 92000, and this is falsé."	)
										self.assertListEqual(
										    __lowerCamelCase						,    [
										        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",
										        ".",
										    ]						,    )
										__magic_name__            =     tokenizer.convert_tokens_to_ids(__lowerCamelCase	)
										self.assertListEqual(
										    __lowerCamelCase						,    [8, 2_1, 8_4, 5_5, 2_4, 1_9, 7, 0, 6_0_2, 3_4_7, 3_4_7, 3_4_7, 3, 1_2, 6_6, 4_6, 7_2, 8_0, 6, 0, 4]						,    )

										__magic_name__            =     tokenizer.convert_ids_to_tokens(__lowerCamelCase	)
										self.assertListEqual(
										    __lowerCamelCase						,    [
										        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>",
										        ".",
										    ]						,    )







				@cached_property
				def     _snake_case					(							self							:						List[Any]	)				->					Optional[int]:
										return ReformerTokenizer.from_pretrained("google/reformer-crime-and-punishment"	)







				@slow
				def     _snake_case					(							self							:						List[str]	)				->					Optional[int]:
										__magic_name__            =     "Hello World!"
										__magic_name__            =     [1_2_6, 3_2, 2_6_2, 1_5_2, 3_8, 7_2, 2_8_7]

										self.assertListEqual(__lowerCamelCase						,    self.big_tokenizer.encode(__lowerCamelCase	)	)







				@slow
				def     _snake_case					(							self							:						List[Any]	)				->					Any:
										__magic_name__            =     (
										    "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
										    " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
										)
										__magic_name__            =     [
										    1_0_8,
										    2_6_5,
										    2_4,
										    1_1_1,
										    4,
										    2_5_8,
										    1_5_6,
										    3_5,
										    2_8,
										    2_7_5,
										    3,
										    2_5_9,
										    2_9_7,
										    2_6_0,
										    8_4,
										    4,
										    3_5,
										    1_1_0,
										    4_4,
										    8,
										    2_5_9,
										    9_1,
										    2_6_8,
										    2_1,
										    1_1,
										    2_0_9,
										    2_7_4,
										    1_0_9,
										    2_6_6,
										    2_7_7,
										    1_1_7,
										    8_6,
										    9_3,
										    3_1_5,
										    2_5_8,
										    2_7_8,
										    2_5_8,
										    2_7_7,
										    2_5_8,
										    0,
										    2_5_8,
										    2_8_8,
										    2_5_8,
										    3_1_9,
										    2_5_8,
										    0,
										    2_5_8,
										    0,
										    2_5_8,
										    0,
										    2_5_8,
										    0,
										    2_5_8,
										    2_8_7,
										    2_5_8,
										    3_1_5,
										    2_5_8,
										    2_8_9,
										    2_5_8,
										    2_7_8,
										    9_9,
										    2_6_9,
										    2_6_6,
										    2_6_2,
										    8,
										    2_5_9,
										    2_4_1,
										    4,
										    2_1_7,
										    2_3_0,
										    2_6_8,
										    2_6_6,
										    5_5,
										    1_6_8,
										    1_0_6,
										    7_5,
										    1_9_3,
										    2_6_6,
										    2_2_3,
										    2_7,
										    4_9,
										    2_6,
										    2_8_2,
										    2_5,
										    2_6_4,
										    2_9_9,
										    1_9,
										    2_6,
										    0,
										    2_5_8,
										    2_7_7,
										    1_1_7,
										    8_6,
										    9_3,
										    1_7_6,
										    1_8_3,
										    2_7_0,
										    1_1,
										    2_6_2,
										    4_2,
										    6_1,
										    2_6_5,
										]

										self.assertListEqual(__lowerCamelCase						,    self.big_tokenizer.encode(__lowerCamelCase	)	)







				@require_torch
				@slow
				def     _snake_case					(							self							:						int	)				->					List[str]:
										import torch

										from transformers import ReformerConfig, ReformerModel

										# Build sequence
										__magic_name__            =     list(self.big_tokenizer.get_vocab().keys()	)[:1_0]
										__magic_name__            =     " ".join(__lowerCamelCase	)
										__magic_name__            =     self.big_tokenizer.encode_plus(__lowerCamelCase						,    return_tensors="pt"	)
										__magic_name__            =     self.big_tokenizer.batch_encode_plus([sequence, sequence]						,    return_tensors="pt"	)

										__magic_name__            =     ReformerConfig()
										# The input gets padded during training so adjust the axial position encodings from the pretrained model value of (512, 1024)
										__magic_name__            =     encoded_sequence["input_ids"].shape
										__magic_name__            =     ReformerModel(__lowerCamelCase	)

										# Reformer has config.vocab_size == tokenizer.vocab_size == len(tokenizer) - 1 = 320; len(tokenizer) is 321 (including a pad token with id 320)
										assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

										with torch.no_grad():
																model(**__lowerCamelCase	)
																model(**__lowerCamelCase	)







				@slow
				def     _snake_case					(							self							:						Optional[Any]	)				->					Optional[Any]:
										# fmt: off
										__magic_name__            =     {"input_ids": [[1_0_8, 2_6_5, 2_4, 1_1_1, 4, 2_5_8, 1_5_6, 7, 5_1, 2_7_9, 5_8, 7, 7_6, 2_5, 6_9, 2_7_8], [1_4_0, 2_4_3, 2_6_4, 1_3_4, 1_7, 2_6_7, 7_7, 2_6_3, 2_2, 2_6_2, 2_9_7, 2_5_8, 3_0_4, 1_7_7, 2_7_9, 2_6_6, 1_4, 8_9, 1_3, 3_5, 2_6_1, 2_9_9, 2_7_2, 1_3_7, 2_7_5, 2_7_8]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
										# fmt: on

										# This tokenizer does not know some characters like ")".
										# That is the reason why we use very simple texts here.
										# Also see https://github.com/huggingface/transformers/pull/11737#issuecomment-850769064
										__magic_name__            =     [
										    "This is a very simple sentence.",
										    "The quick brown fox jumps over the lazy dog.",
										]

										self.tokenizer_integration_test_util(
										    expected_encoding=__lowerCamelCase						,    model_name="google/reformer-crime-and-punishment"						,    revision="0e6c3decb8211d49bf881013425dc8b0448b3f5a"						,    padding=__lowerCamelCase						,    sequences=__lowerCamelCase						,    )











"""simple docstring"""

def _lowerCAmelCase	(  __lowerCamelCase:list   ):

						'''simple docstring'''






						__magic_name__            =     len(__lowerCamelCase   )
						for i in range(1 ,						__lowerCamelCase   ):
												__magic_name__            =     collection[i]
												__magic_name__            =     0
												__magic_name__            =     i - 1

												while low <= high:
																		__magic_name__            =     (low + high) // 2
																		if val < collection[mid]:
																								__magic_name__            =     mid - 1
																		else:
																								__magic_name__            =     mid + 1
												for j in range(__lowerCamelCase ,						__lowerCamelCase ,						-1   ):
																		__magic_name__            =     collection[j - 1]
												__magic_name__            =     val
						return collection


if __name__ == "__main__":
			lowercase    			=       input('''Enter numbers separated by a comma:\n''').strip()
			lowercase    			=       [int(item) for item in user_input.split(''',''')]
			print(binary_insertion_sort(unsorted))



