





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


UpperCamelCase__          =get_tests_dir('fixtures/spiece.model')





@require_sentencepiece
@require_tokenizers
class 	lowerCAmelCase__(       __lowercase     ,   unittest.TestCase			):






       '''simple docstring'''


       __snake_case       	=			ErnieMTokenizer
       __snake_case       	=			False
       __snake_case       	=			True
       __snake_case       	=			False
       __snake_case       	=			False




       def 			UpperCamelCase_	(					self							)	->   Optional[int]:
            super().setUp()

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




       def 			UpperCamelCase_	(					self			,  __lowerCamelCase							)	->   Tuple:
            _SCREAMING_SNAKE_CASE				:		List[str]  			=							"this is a test"
            _SCREAMING_SNAKE_CASE				:		List[str]  			=							"this is a test"
            return input_text, output_text




       def 			UpperCamelCase_	(					self							)	->   int:
            _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							"<pad>"
            _SCREAMING_SNAKE_CASE				:		Any  			=							0

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




       def 			UpperCamelCase_	(					self							)	->   Any:
            _SCREAMING_SNAKE_CASE				:		Any  			=							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(__lowerCamelCase							)			,  3_0_0_0_0							)




       def 			UpperCamelCase_	(					self							)	->   Union[str, Any]:
            self.assertEqual(self.get_tokenizer().vocab_size			,  3_0_0_0_0							)




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

            _SCREAMING_SNAKE_CASE				:		Tuple  			=							self.get_tokenizer()
            _SCREAMING_SNAKE_CASE				:		str  			=							self.get_rust_tokenizer()

            _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							"I was born in 92000, and this is falsé."

            _SCREAMING_SNAKE_CASE				:		Tuple  			=							tokenizer.tokenize(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							rust_tokenizer.tokenize(__lowerCamelCase							)
            self.assertListEqual(__lowerCamelCase			,  __lowerCamelCase							)

            _SCREAMING_SNAKE_CASE				:		str  			=							tokenizer.encode(__lowerCamelCase			,  add_special_tokens=__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		Optional[Any]  			=							rust_tokenizer.encode(__lowerCamelCase			,  add_special_tokens=__lowerCamelCase							)
            self.assertListEqual(__lowerCamelCase			,  __lowerCamelCase							)

            _SCREAMING_SNAKE_CASE				:		Any  			=							self.get_rust_tokenizer()
            _SCREAMING_SNAKE_CASE				:		int  			=							tokenizer.encode(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							rust_tokenizer.encode(__lowerCamelCase							)
            self.assertListEqual(__lowerCamelCase			,  __lowerCamelCase							)




       def 			UpperCamelCase_	(					self							)	->   Optional[int]:
            _SCREAMING_SNAKE_CASE				:		int  			=							ErnieMTokenizer(__lowerCamelCase			,  do_lower_case=__lowerCamelCase			,  unk_token="<unk>"			,  pad_token="<pad>"							)

            _SCREAMING_SNAKE_CASE				:		Union[str, Any]  			=							tokenizer.tokenize("This is a test"							)
            self.assertListEqual(__lowerCamelCase			,  ["▁this", "▁is", "▁a", "▁test"]							)

            self.assertListEqual(tokenizer.convert_tokens_to_ids(__lowerCamelCase							)			,  [4_8, 2_5, 2_1, 1_2_8_9]							)

            _SCREAMING_SNAKE_CASE				:		str  			=							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(
                __lowerCamelCase			,  ["▁i", "▁was", "▁born", "▁in", "9", "2000", ",", "▁and", "▁this", "▁is", "▁fal", "s", "é", "."]							)
            _SCREAMING_SNAKE_CASE				:		Optional[int]  			=							tokenizer.convert_tokens_to_ids(__lowerCamelCase							)
            self.assertListEqual(__lowerCamelCase			,  [3_1, 2_3, 3_8_6, 1_9, 5_1_8, 3_0_5_0, 1_5, 1_7, 4_8, 2_5, 8_2_5_6, 1_8, 1, 9]							)

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




       def 			UpperCamelCase_	(					self							)	->   Any:
            _SCREAMING_SNAKE_CASE				:		int  			=							ErnieMTokenizer(__lowerCamelCase			,  unk_token="<unk>"			,  pad_token="<pad>"							)

            _SCREAMING_SNAKE_CASE				:		List[str]  			=							tokenizer.encode("sequence builders"							)
            _SCREAMING_SNAKE_CASE				:		int  			=							tokenizer.encode("multi-sequence build"							)

            _SCREAMING_SNAKE_CASE				:		List[Any]  			=							tokenizer.build_inputs_with_special_tokens(__lowerCamelCase							)
            _SCREAMING_SNAKE_CASE				:		str  			=							tokenizer.build_inputs_with_special_tokens(__lowerCamelCase			,  __lowerCamelCase							)

            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 			UpperCamelCase_	(					self							)	->   Union[str, Any]:
            # fmt: off
            _SCREAMING_SNAKE_CASE				:		List[str]  			=							{"input_ids": [[0, 1_1_0_6_2, 8_2_7_7_2, 7, 1_5, 8_2_7_7_2, 5_3_8, 5_1_5_2_9, 2_3_7, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 2_1_5_1_7_5, 1_3_1_4, 1_3_6, 1_7_1_9_8, 1_2_9_0, 2_0_6, 9, 5_6_3_5_9, 4_2, 1_2_2_0_0_9, 9, 1_6_4_6_6, 1_6, 8_7_3_4_4, 4_5_3_7, 9, 4_7_1_7, 7_8_3_8_1, 6, 1_5_9_9_5_8, 7, 1_5, 2_4_4_8_0, 6_1_8, 4, 5_2_7, 2_2_6_9_3, 9, 3_0_4, 4, 2_7_7_7, 2_4_4_8_0, 9_8_7_4, 4, 4_3_5_2_3, 5_9_4, 4, 8_0_3, 1_8_3_9_2, 3_3_1_8_9, 1_8, 4, 4_3_5_2_3, 2_4_4_4_7, 5, 5, 5, 1_6, 1_0_0, 2_4_9_5_5, 8_3_6_5_8, 9_6_2_6, 1_4_4_0_5_7, 1_5, 8_3_9, 2_2_3_3_5, 1_6, 1_3_6, 2_4_9_5_5, 8_3_6_5_8, 8_3_4_7_9, 1_5, 3_9_1_0_2, 7_2_4, 1_6, 6_7_8, 6_4_5, 6_4_6_0, 1_3_2_8, 4_5_8_9, 4_2, 1_2_2_0_0_9, 1_1_5_7_7_4, 2_3, 3_5_5_9, 1_3_2_8, 4_6_8_7_6, 7, 1_3_6, 5_3_8_9_4, 1_9_4_0, 4_2_2_2_7, 4_1_1_5_9, 1_7_7_2_1, 8_2_3, 4_2_5, 4, 2_7_5_1_2, 9_8_7_2_2, 2_0_6, 1_3_6, 5_5_3_1, 4_9_7_0, 9_1_9, 1_7_3_3_6, 5, 2], [0, 2_0_0_8_0, 6_1_8, 8_3, 8_2_7_7_5, 4_7, 4_7_9, 9, 1_5_1_7, 7_3, 5_3_8_9_4, 3_3_3, 8_0_5_8_1, 1_1_0_1_1_7, 1_8_8_1_1, 5_2_5_6, 1_2_9_5, 5_1, 1_5_2_5_2_6, 2_9_7, 7_9_8_6, 3_9_0, 1_2_4_4_1_6, 5_3_8, 3_5_4_3_1, 2_1_4, 9_8, 1_5_0_4_4, 2_5_7_3_7, 1_3_6, 7_1_0_8, 4_3_7_0_1, 2_3, 7_5_6, 1_3_5_3_5_5, 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, 5_8_1, 6_3_7_7_3, 1_1_9_4_5_5, 6, 1_4_7_7_9_7, 8_8_2_0_3, 7, 6_4_5, 7_0, 2_1, 3_2_8_5, 1_0_2_6_9, 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=__lowerCamelCase			,  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.",
                ]			,  )


"""simple docstring"""




def    __SCREAMING_SNAKE_CASE						(						lowercase__			,							lowercase__			,							lowercase__      ):
					"""simple docstring"""
					A			=					index
					A			=					2 * index + 1
					A			=					2 * index + 2
					if left_index < heap_size and unsorted[left_index] > unsorted[largest]:
										A			=					left_index

					if right_index < heap_size and unsorted[right_index] > unsorted[largest]:
										A			=					right_index

					if largest != index:
										A			,    A			=					unsorted[index], unsorted[largest]
										heapify(lowercase__			,							lowercase__			,							lowercase__      )
def    __SCREAMING_SNAKE_CASE						(						lowercase__      ):
					"""simple docstring"""
					A			=					len(lowercase__      )
					for i in range(n // 2 - 1			,							-1			,							-1      ):
										heapify(lowercase__			,							lowercase__			,							lowercase__      )
					for i in range(n - 1			,							0			,							-1      ):
										A			,    A			=					unsorted[i], unsorted[0]
										heapify(lowercase__			,							0			,							lowercase__      )
					return unsorted


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





