



'''simple docstring'''

import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path

import pytest

import transformers
from transformers import (
    BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
    GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
    AutoTokenizer,
    BertConfig,
    BertTokenizer,
    BertTokenizerFast,
    CTRLTokenizer,
    GPTaTokenizer,
    GPTaTokenizerFast,
    PreTrainedTokenizerFast,
    RobertaTokenizer,
    RobertaTokenizerFast,
    is_tokenizers_available,
)
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.auto.tokenization_auto import (
    TOKENIZER_MAPPING,
    get_tokenizer_config,
    tokenizer_class_from_name,
)
from transformers.models.roberta.configuration_roberta import RobertaConfig
from transformers.testing_utils import (
    DUMMY_DIFF_TOKENIZER_IDENTIFIER,
    DUMMY_UNKNOWN_IDENTIFIER,
    SMALL_MODEL_IDENTIFIER,
    RequestCounter,
    require_tokenizers,
    slow,
)


sys.path.append(str(Path(__file__).parent.parent.parent.parent / 'utils'))

from test_module.custom_configuration import CustomConfig  # noqa E402
from test_module.custom_tokenization import CustomTokenizer  # noqa E402


if is_tokenizers_available():
				from test_module.custom_tokenization_fast import CustomTokenizerFast

class __snake_case(				unittest.TestCase ):


						'''simple docstring'''



						def     __snake_case   ( self				)     ->     Optional[int]:
							lowerCAmelCase   =     0


						@slow
						def     __snake_case   ( self				)     ->     List[str]:
							for model_name in (x for x in BERT_PRETRAINED_CONFIG_ARCHIVE_MAP.keys() if "japanese" not in x):
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
								self.assertIsNotNone(A_				)
								self.assertIsInstance(A_     ,	(BertTokenizer, BertTokenizerFast)				)
								self.assertGreater(len(A_				)     ,	0				)

							for model_name in GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP.keys():
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
								self.assertIsNotNone(A_				)
								self.assertIsInstance(A_     ,	(GPTaTokenizer, GPTaTokenizerFast)				)
								self.assertGreater(len(A_				)     ,	0				)


						def     __snake_case   ( self				)     ->     int:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
							self.assertIsInstance(A_     ,	(BertTokenizer, BertTokenizerFast)				)
							self.assertEqual(tokenizer.vocab_size     ,	12				)


						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
							self.assertIsInstance(A_     ,	(RobertaTokenizer, RobertaTokenizerFast)				)
							self.assertEqual(tokenizer.vocab_size     ,	20				)


						def     __snake_case   ( self				)     ->     Tuple:
							lowerCAmelCase   =     AutoConfig.from_pretrained(A_				)
							self.assertIsInstance(A_     ,	A_				)
							# Check that tokenizer_type ≠ model_type
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	config=A_				)
							self.assertIsInstance(A_     ,	(BertTokenizer, BertTokenizerFast)				)
							self.assertEqual(tokenizer.vocab_size     ,	12				)


						def     __snake_case   ( self				)     ->     List[Any]:
							with tempfile.TemporaryDirectory() as tmp_dir:
								shutil.copy("""./tests/fixtures/vocab.txt"""     ,	os.path.join(A_     ,	"""vocab.txt"""				)				)

								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	tokenizer_type="""bert"""     ,	use_fast=A_				)
								self.assertIsInstance(A_     ,	A_				)

							with tempfile.TemporaryDirectory() as tmp_dir:
								shutil.copy("""./tests/fixtures/vocab.json"""     ,	os.path.join(A_     ,	"""vocab.json"""				)				)
								shutil.copy("""./tests/fixtures/merges.txt"""     ,	os.path.join(A_     ,	"""merges.txt"""				)				)

								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	tokenizer_type="""gpt2"""     ,	use_fast=A_				)
								self.assertIsInstance(A_     ,	A_				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     List[Any]:
							with tempfile.TemporaryDirectory() as tmp_dir:
								shutil.copy("""./tests/fixtures/vocab.txt"""     ,	os.path.join(A_     ,	"""vocab.txt"""				)				)

								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	tokenizer_type="""bert"""				)
								self.assertIsInstance(A_     ,	A_				)

							with tempfile.TemporaryDirectory() as tmp_dir:
								shutil.copy("""./tests/fixtures/vocab.json"""     ,	os.path.join(A_     ,	"""vocab.json"""				)				)
								shutil.copy("""./tests/fixtures/merges.txt"""     ,	os.path.join(A_     ,	"""merges.txt"""				)				)

								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	tokenizer_type="""gpt2"""				)
								self.assertIsInstance(A_     ,	A_				)


						def     __snake_case   ( self				)     ->     Any:
							with pytest.raises(A_				):
								AutoTokenizer.from_pretrained("""./"""     ,	tokenizer_type="""xxx"""				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     int:
							for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
								lowerCAmelCase   =     tokenizer_class.from_pretrained("""wietsedv/bert-base-dutch-cased"""				)
								self.assertIsInstance(A_     ,	(BertTokenizer, BertTokenizerFast)				)

								if isinstance(A_     ,	A_				):
									self.assertEqual(tokenizer.basic_tokenizer.do_lower_case     ,	A_				)
								else:
									self.assertEqual(tokenizer.do_lower_case     ,	A_				)

								self.assertEqual(tokenizer.model_max_length     ,	512				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     List[Any]:
							for tokenizer_class in [BertTokenizer, BertTokenizerFast, AutoTokenizer]:
								with self.assertRaisesRegex(
								    A_     ,	"""julien-c/herlolip-not-exists is not a local folder and is not a valid model identifier"""     ,	):
									lowerCAmelCase   =     tokenizer_class.from_pretrained("""julien-c/herlolip-not-exists"""				)


						def     __snake_case   ( self				)     ->     Dict:
							# tests: https://github.com/huggingface/transformers/pull/13251
							# 1. models with `-`, e.g. xlm-roberta -> xlm_roberta
							# 2. models that don't remap 1-1 from model-name to model file, e.g., openai-gpt -> openai
							lowerCAmelCase   =     TOKENIZER_MAPPING.values()
							lowerCAmelCase   =     []

							for slow_tok, fast_tok in tokenizers:
								if slow_tok is not None:
									tokenizer_names.append(slow_tok.__name__				)

								if fast_tok is not None:
									tokenizer_names.append(fast_tok.__name__				)

							for tokenizer_name in tokenizer_names:
								# must find the right class
								tokenizer_class_from_name(A_				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     Optional[int]:
							self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""     ,	use_fast=A_				)     ,	A_				)
							self.assertIsInstance(AutoTokenizer.from_pretrained("""bert-base-cased"""				)     ,	A_				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""distilbert-base-uncased"""     ,	do_lower_case=A_				)
							lowerCAmelCase   =     """Hello, world. How are you?"""
							lowerCAmelCase   =     tokenizer.tokenize(A_				)
							self.assertEqual("""[UNK]"""     ,	tokens[0]				)

							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""microsoft/mpnet-base"""     ,	do_lower_case=A_				)
							lowerCAmelCase   =     tokenizer.tokenize(A_				)
							self.assertEqual("""[UNK]"""     ,	tokens[0]				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     Optional[Any]:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""robot-test/dummy-tokenizer-fast-with-model-config"""				)
							self.assertEqual(type(A_				)     ,	A_				)
							self.assertEqual(tokenizer.model_max_length     ,	512				)
							self.assertEqual(tokenizer.vocab_size     ,	3_0000				)
							self.assertEqual(tokenizer.unk_token     ,	"""[UNK]"""				)
							self.assertEqual(tokenizer.padding_side     ,	"""right"""				)
							self.assertEqual(tokenizer.truncation_side     ,	"""right"""				)


						def     __snake_case   ( self				)     ->     Any:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
							self.assertIsInstance(A_     ,	(BertTokenizer, BertTokenizerFast)				)
							with tempfile.TemporaryDirectory() as tmp_dir:
								tokenizer.save_pretrained(A_				)
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)

							self.assertIsInstance(A_     ,	tokenizer.__class__				)
							self.assertEqual(tokenizera.vocab_size     ,	12				)


						def     __snake_case   ( self				)     ->     List[Any]:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""ctrl"""				)
							# There is no fast CTRL so this always gives us a slow tokenizer.
							self.assertIsInstance(A_     ,	A_				)


						def     __snake_case   ( self				)     ->     Any:
							# Check we can load the tokenizer config of an online model.
							lowerCAmelCase   =     get_tokenizer_config("""bert-base-cased"""				)
							lowerCAmelCase   =     config.pop("""_commit_hash"""     ,	A_				)
							# If we ever update bert-base-cased tokenizer config, this dict here will need to be updated.
							self.assertEqual(A_     ,	{"""do_lower_case""": False}				)

							# This model does not have a tokenizer_config so we get back an empty dict.
							lowerCAmelCase   =     get_tokenizer_config(A_				)
							self.assertDictEqual(A_     ,	{}				)

							# A tokenizer saved with `save_pretrained` always creates a tokenizer config.
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
							with tempfile.TemporaryDirectory() as tmp_dir:
								tokenizer.save_pretrained(A_				)
								lowerCAmelCase   =     get_tokenizer_config(A_				)

							# Check the class of the tokenizer was properly saved (note that it always saves the slow class).
							self.assertEqual(config["""tokenizer_class"""]     ,	"""BertTokenizer"""				)


						def     __snake_case   ( self				)     ->     int:
							try:
								AutoConfig.register("""custom"""     ,	A_				)

								AutoTokenizer.register(A_     ,	slow_tokenizer_class=A_				)
								# Trying to register something existing in the Transformers library will raise an error
								with self.assertRaises(A_				):
									AutoTokenizer.register(A_     ,	slow_tokenizer_class=A_				)

								lowerCAmelCase   =     CustomTokenizer.from_pretrained(A_				)
								with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(A_				)

									lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
									self.assertIsInstance(A_     ,	A_				)

							finally:
								if "custom" in CONFIG_MAPPING._extra_content:
									del CONFIG_MAPPING._extra_content["custom"]
								if CustomConfig in TOKENIZER_MAPPING._extra_content:
									del TOKENIZER_MAPPING._extra_content[CustomConfig]


						@require_tokenizers
						def     __snake_case   ( self				)     ->     Optional[Any]:
							try:
								AutoConfig.register("""custom"""     ,	A_				)

								# Can register in two steps
								AutoTokenizer.register(A_     ,	slow_tokenizer_class=A_				)
								self.assertEqual(TOKENIZER_MAPPING[CustomConfig]     ,	(CustomTokenizer, None)				)
								AutoTokenizer.register(A_     ,	fast_tokenizer_class=A_				)
								self.assertEqual(TOKENIZER_MAPPING[CustomConfig]     ,	(CustomTokenizer, CustomTokenizerFast)				)

								del TOKENIZER_MAPPING._extra_content[CustomConfig]
								# Can register in one step
								AutoTokenizer.register(
								    A_     ,	slow_tokenizer_class=A_     ,	fast_tokenizer_class=A_				)
								self.assertEqual(TOKENIZER_MAPPING[CustomConfig]     ,	(CustomTokenizer, CustomTokenizerFast)				)

								# Trying to register something existing in the Transformers library will raise an error
								with self.assertRaises(A_				):
									AutoTokenizer.register(A_     ,	fast_tokenizer_class=A_				)

								# We pass through a bert tokenizer fast cause there is no converter slow to fast for our new toknizer
								# and that model does not have a tokenizer.json
								with tempfile.TemporaryDirectory() as tmp_dir:
									lowerCAmelCase   =     BertTokenizerFast.from_pretrained(A_				)
									bert_tokenizer.save_pretrained(A_				)
									lowerCAmelCase   =     CustomTokenizerFast.from_pretrained(A_				)

								with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(A_				)

									lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_				)
									self.assertIsInstance(A_     ,	A_				)

									lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	use_fast=A_				)
									self.assertIsInstance(A_     ,	A_				)

							finally:
								if "custom" in CONFIG_MAPPING._extra_content:
									del CONFIG_MAPPING._extra_content["custom"]
								if CustomConfig in TOKENIZER_MAPPING._extra_content:
									del TOKENIZER_MAPPING._extra_content[CustomConfig]


						def     __snake_case   ( self				)     ->     Dict:
							# If remote code is not set, we will time out when asking whether to load the model.
							with self.assertRaises(A_				):
								lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""				)
							# If remote code is disabled, we can't load this config.
							with self.assertRaises(A_				):
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_				)

							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_				)
							self.assertTrue(tokenizer.special_attribute_present				)
							# Test tokenizer can be reloaded.
							with tempfile.TemporaryDirectory() as tmp_dir:
								tokenizer.save_pretrained(A_				)
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	trust_remote_code=A_				)
							self.assertTrue(reloaded_tokenizer.special_attribute_present				)

							if is_tokenizers_available():
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)
								self.assertEqual(reloaded_tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)

								# Test we can also load the slow version
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_     ,	use_fast=A_				)
								self.assertTrue(tokenizer.special_attribute_present				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								# Test tokenizer can be reloaded.
								with tempfile.TemporaryDirectory() as tmp_dir:
									tokenizer.save_pretrained(A_				)
									lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	trust_remote_code=A_     ,	use_fast=A_				)
								self.assertEqual(reloaded_tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								self.assertTrue(reloaded_tokenizer.special_attribute_present				)
							else:
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								self.assertEqual(reloaded_tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)


						@require_tokenizers
						def     __snake_case   ( self				)     ->     Optional[int]:

							class __snake_case(				_lowerCAmelCase ):


													'''simple docstring'''



													UpperCAmelCase							:   List[str]									=		False







							class __snake_case(				_lowerCAmelCase ):


													'''simple docstring'''



													UpperCAmelCase							:   Union[str, Any]									=		NewTokenizer
													UpperCAmelCase							:   str									=		False

							try:
								AutoConfig.register("""custom"""     ,	A_				)
								AutoTokenizer.register(A_     ,	slow_tokenizer_class=A_				)
								AutoTokenizer.register(A_     ,	fast_tokenizer_class=A_				)
								# If remote code is not set, the default is to use local
								lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)
								self.assertFalse(tokenizer.special_attribute_present				)
								lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/test_dynamic_tokenizer"""     ,	use_fast=A_				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								self.assertFalse(tokenizer.special_attribute_present				)

								# If remote code is disabled, we load the local one.
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)
								self.assertFalse(tokenizer.special_attribute_present				)
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_     ,	use_fast=A_				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								self.assertFalse(tokenizer.special_attribute_present				)

								# If remote is enabled, we load from the Hub
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)
								self.assertTrue(tokenizer.special_attribute_present				)
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer"""     ,	trust_remote_code=A_     ,	use_fast=A_				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
								self.assertTrue(tokenizer.special_attribute_present				)

							finally:
								if "custom" in CONFIG_MAPPING._extra_content:
									del CONFIG_MAPPING._extra_content["custom"]
								if CustomConfig in TOKENIZER_MAPPING._extra_content:
									del TOKENIZER_MAPPING._extra_content[CustomConfig]


						def     __snake_case   ( self				)     ->     Tuple:
							lowerCAmelCase   =     AutoTokenizer.from_pretrained(
							    """hf-internal-testing/test_dynamic_tokenizer_legacy"""     ,	trust_remote_code=A_				)
							self.assertTrue(tokenizer.special_attribute_present				)
							if is_tokenizers_available():
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizerFast"""				)

								# Test we can also load the slow version
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(
								    """hf-internal-testing/test_dynamic_tokenizer_legacy"""     ,	trust_remote_code=A_     ,	use_fast=A_				)
								self.assertTrue(tokenizer.special_attribute_present				)
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)
							else:
								self.assertEqual(tokenizer.__class__.__name__     ,	"""NewTokenizer"""				)


						def     __snake_case   ( self				)     ->     Tuple:
							with self.assertRaisesRegex(
							    A_     ,	"""bert-base is not a local folder and is not a valid model identifier"""				):
								lowerCAmelCase   =     AutoTokenizer.from_pretrained("""bert-base"""				)


						def     __snake_case   ( self				)     ->     Optional[Any]:
							with self.assertRaisesRegex(
							    A_     ,	r"""aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"""				):
								lowerCAmelCase   =     AutoTokenizer.from_pretrained(A_     ,	revision="""aaaaaa"""				)




						def     __snake_case   ( self				)     ->     Optional[Any]:
							# Make sure we have cached the tokenizer.
							lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/tiny-random-bert"""				)
							with RequestCounter() as counter:
								lowerCAmelCase   =     AutoTokenizer.from_pretrained("""hf-internal-testing/tiny-random-bert"""				)
								self.assertEqual(counter.get_request_count     ,	0				)
								self.assertEqual(counter.head_request_count     ,	1				)
								self.assertEqual(counter.other_request_count     ,	0				)




'''simple docstring'''

def 		_snake_case		( _SCREAMING_SNAKE_CASE					:						list							)      ->						list:







	"""simple docstring"""

	if len(_SCREAMING_SNAKE_CASE							) < 2:
		return collection

	def circle_sort_util(_SCREAMING_SNAKE_CASE					:						list							,		_SCREAMING_SNAKE_CASE					:						int							,		_SCREAMING_SNAKE_CASE					:						int							) -> bool:
		lowerCAmelCase   =     False

		if low == high:
			return swapped

		lowerCAmelCase   =     low
		lowerCAmelCase   =     high

		while left < right:
			if collection[left] > collection[right]:
				lowerCAmelCase,       lowerCAmelCase   =     (
				    collection[right],
				    collection[left],
				)
				lowerCAmelCase   =     True

			left += 1
			right -= 1

		if left == right and collection[left] > collection[right + 1]:
			lowerCAmelCase,       lowerCAmelCase   =     (
			    collection[right + 1],
			    collection[left],
			)

			lowerCAmelCase   =     True

		lowerCAmelCase   =     low + int((high - low) / 2							)
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							,		_SCREAMING_SNAKE_CASE							)
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		mid + 1							,		_SCREAMING_SNAKE_CASE							)

		return swapped or left_swap or right_swap

	lowerCAmelCase   =     True

	while is_not_sorted is True:
		lowerCAmelCase   =     circle_sort_util(_SCREAMING_SNAKE_CASE							,		0							,		len(_SCREAMING_SNAKE_CASE							) - 1							)

	return collection


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