


import unittest

from transformers import ErnieMTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


SCREAMING_SNAKE_CASE__       			=				get_tests_dir("""fixtures/spiece.model""")







@require_sentencepiece
@require_tokenizers
class     __lowerCamelCase     (  snake_case_							,   unittest.TestCase     ):


							"""simple docstring"""

							lowerCAmelCase__          =				ErnieMTokenizer
							lowerCAmelCase__          =				False
							lowerCAmelCase__          =				True
							lowerCAmelCase__          =				False
							lowerCAmelCase__          =				False




							def 				A__      (  self  )     ->       Optional[Any]:






								'''simple docstring'''






								super().setUp()

								# We have a SentencePiece fixture for testing
								lowercase_			 = ErnieMTokenizer(UpperCAmelCase						,       unk_token="<unk>"						,       pad_token="<pad>"  )
								tokenizer.save_pretrained(self.tmpdirname  )




							def 				A__      (  self						,       UpperCAmelCase  )     ->       int:






								'''simple docstring'''






								lowercase_			 = "this is a test"
								lowercase_			 = "this is a test"
								return input_text, output_text




							def 				A__      (  self  )     ->       Tuple:






								'''simple docstring'''






								lowercase_			 = "<pad>"
								lowercase_			 = 0

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




							def 				A__      (  self  )     ->       Any:






								'''simple docstring'''






								lowercase_			 = list(self.get_tokenizer().get_vocab().keys()  )

								self.assertEqual(vocab_keys[0]						,       "<pad>"  )
								self.assertEqual(vocab_keys[1]						,       "<unk>"  )
								self.assertEqual(vocab_keys[-1]						,       "▁eloquent"  )
								self.assertEqual(len(UpperCAmelCase  )						,       30000  )




							def 				A__      (  self  )     ->       str:






								'''simple docstring'''






								self.assertEqual(self.get_tokenizer().vocab_size						,       30000  )




							def 				A__      (  self  )     ->       Optional[Any]:






								'''simple docstring'''






								if not self.test_rust_tokenizer:
									return

								lowercase_			 = self.get_tokenizer()
								lowercase_			 = self.get_rust_tokenizer()

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

								lowercase_			 = tokenizer.tokenize(UpperCAmelCase  )
								lowercase_			 = rust_tokenizer.tokenize(UpperCAmelCase  )
								self.assertListEqual(UpperCAmelCase						,       UpperCAmelCase  )

								lowercase_			 = tokenizer.encode(UpperCAmelCase						,       add_special_tokens=UpperCAmelCase  )
								lowercase_			 = rust_tokenizer.encode(UpperCAmelCase						,       add_special_tokens=UpperCAmelCase  )
								self.assertListEqual(UpperCAmelCase						,       UpperCAmelCase  )

								lowercase_			 = self.get_rust_tokenizer()
								lowercase_			 = tokenizer.encode(UpperCAmelCase  )
								lowercase_			 = rust_tokenizer.encode(UpperCAmelCase  )
								self.assertListEqual(UpperCAmelCase						,       UpperCAmelCase  )




							def 				A__      (  self  )     ->       int:






								'''simple docstring'''






								lowercase_			 = ErnieMTokenizer(UpperCAmelCase						,       do_lower_case=UpperCAmelCase						,       unk_token="<unk>"						,       pad_token="<pad>"  )

								lowercase_			 = tokenizer.tokenize("This is a test"  )
								self.assertListEqual(UpperCAmelCase						,       ["▁this", "▁is", "▁a", "▁test"]  )

								self.assertListEqual(tokenizer.convert_tokens_to_ids(UpperCAmelCase  )						,       [48, 25, 21, 1289]  )

								lowercase_			 = tokenizer.tokenize("I was born in 92000, and this is falsé."  )
								# ErnieMTokenizer(paddlenlp implementation) outputs '9' instead of '_9' so to mimic that '_9' is changed to '9'
								self.assertListEqual(
								    UpperCAmelCase						,       ["▁i", "▁was", "▁born", "▁in", "9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]  )
								lowercase_			 = tokenizer.convert_tokens_to_ids(UpperCAmelCase  )
								self.assertListEqual(UpperCAmelCase						,       [31, 23, 386, 19, 518, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]  )

								lowercase_			 = tokenizer.convert_ids_to_tokens(UpperCAmelCase  )
								self.assertListEqual(
								    UpperCAmelCase						,       ["▁i", "▁was", "▁born", "▁in", "9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "<unk>", "."]						,       )




							def 				A__      (  self  )     ->       Union[str, Any]:






								'''simple docstring'''






								lowercase_			 = ErnieMTokenizer(UpperCAmelCase						,       unk_token="<unk>"						,       pad_token="<pad>"  )

								lowercase_			 = tokenizer.encode("sequence builders"  )
								lowercase_			 = tokenizer.encode("multi-sequence build"  )

								lowercase_			 = tokenizer.build_inputs_with_special_tokens(UpperCAmelCase  )
								lowercase_			 = tokenizer.build_inputs_with_special_tokens(UpperCAmelCase						,       UpperCAmelCase  )

								assert encoded_sentence == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id]
								assert encoded_pair == [tokenizer.cls_token_id] + text + [tokenizer.sep_token_id] + [
								    tokenizer.sep_token_id
								] + text_a + [tokenizer.sep_token_id]




							@slow
							def 				A__      (  self  )     ->       Optional[int]:






								'''simple docstring'''






								lowercase_			 = {"input_ids": [[0, 11062, 82772, 7, 15, 82772, 538, 51529, 237, 17198, 1290, 206, 9, 215175, 1314, 136, 17198, 1290, 206, 9, 56359, 42, 122009, 9, 16466, 16, 87344, 4537, 9, 4717, 78381, 6, 159958, 7, 15, 24480, 618, 4, 527, 22693, 9, 304, 4, 2777, 24480, 9874, 4, 43523, 594, 4, 803, 18392, 33189, 18, 4, 43523, 24447, 5, 5, 5, 16, 100, 24955, 83658, 9626, 144057, 15, 839, 22335, 16, 136, 24955, 83658, 83479, 15, 39102, 724, 16, 678, 645, 6460, 1328, 4589, 42, 122009, 115774, 23, 3559, 1328, 46876, 7, 136, 53894, 1940, 42227, 41159, 17721, 823, 425, 4, 27512, 98722, 206, 136, 5531, 4970, 919, 17336, 5, 2], [0, 20080, 618, 83, 82775, 47, 479, 9, 1517, 73, 53894, 333, 80581, 110117, 18811, 5256, 1295, 51, 152526, 297, 7986, 390, 124416, 538, 35431, 214, 98, 15044, 25737, 136, 7108, 43701, 23, 756, 135355, 7, 5, 2, 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, 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], [0, 581, 63773, 119455, 6, 147797, 88203, 7, 645, 70, 21, 3285, 10269, 5, 2, 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, 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, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}
								# fmt: on

								self.tokenizer_integration_test_util(
								    expected_encoding=UpperCAmelCase						,       model_name="susnato/ernie-m-base_pytorch"						,       sequences=[
								        "Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides "
								        "general-purpose architectures (BERT, GPT-2, RoBERTa, XLM, DistilBert, XLNet...) for Natural "
								        "Language Understanding (NLU) and Natural Language Generation (NLG) with over32+ pretrained "
								        "models in100+ languages and deep interoperability between Jax, PyTorch and TensorFlow.",
								        "BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly "
								        "conditioning on both left and right context in all layers.",
								        "The quick brown fox jumps over the lazy dog.",
								    ]						,       )





from __future__ import annotations

from random import randrange




def SCREAMING_SNAKE_CASE_  (				__lowerCamelCase:		list  ):







	'''simple docstring'''



	if len(__lowerCamelCase  ) < 2:
		return collection
	lowercase_			 = randrange(len(__lowerCamelCase  )  )  # Use random element as pivot
	lowercase_			 = collection[pivot_index]
	lowercase_			 = []  # All elements greater than pivot
	lowercase_			 = []  # All elements less than or equal to pivot

	for element in collection[:pivot_index]:
		(greater if element > pivot else lesser).append(__lowerCamelCase  )

	for element in collection[pivot_index + 1 :]:
		(greater if element > pivot else lesser).append(__lowerCamelCase  )

	return [*quick_sort(__lowerCamelCase  ), pivot, *quick_sort(__lowerCamelCase  )]


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

