

'''simple docstring'''

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


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







@require_sentencepiece
@require_tokenizers
class lowerCamelCase      (						__lowerCAmelCase							,							unittest.TestCase							):
				snake_case_           =   ErnieMTokenizer
				snake_case_           =   False
				snake_case_           =   True
				snake_case_           =   False
				snake_case_           =   False

				def 				_lowerCamelCase						(					self   )						->       Any:
					super().setUp()

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

				def 				_lowerCamelCase						(					self,	lowercase_   )						->       str:
					snake_case							 =				'this is a test'
					snake_case							 =				'this is a test'
					return input_text, output_text

				def 				_lowerCamelCase						(					self   )						->       Tuple:
					snake_case							 =				'<pad>'
					snake_case							 =				0

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

				def 				_lowerCamelCase						(					self   )						->       Tuple:
					snake_case							 =				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(lowercase_   ),	30000   )

				def 				_lowerCamelCase						(					self   )						->       Dict:
					self.assertEqual(self.get_tokenizer().vocab_size,	30000   )

				def 				_lowerCamelCase						(					self   )						->       List[Any]:
					if not self.test_rust_tokenizer:
						return

					snake_case							 =				self.get_tokenizer()
					snake_case							 =				self.get_rust_tokenizer()

					snake_case							 =				'I was born in 92000, and this is falsé.'

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

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

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

				def 				_lowerCamelCase						(					self   )						->       str:
					snake_case							 =				ErnieMTokenizer(lowercase_,	do_lower_case=lowercase_,	unk_token='<unk>',	pad_token='<pad>'   )

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

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

					snake_case							 =				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(
					    lowercase_,	['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.']   )
					snake_case							 =				tokenizer.convert_tokens_to_ids(lowercase_   )
					self.assertListEqual(lowercase_,	[31, 23, 386, 19, 518, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]   )

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

				def 				_lowerCamelCase						(					self   )						->       int:
					snake_case							 =				ErnieMTokenizer(lowercase_,	unk_token='<unk>',	pad_token='<pad>'   )

					snake_case							 =				tokenizer.encode('sequence builders'   )
					snake_case							 =				tokenizer.encode('multi-sequence build'   )

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

					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 				_lowerCamelCase						(					self   )						->       Union[str, Any]:
					# fmt: off
					snake_case							 =				{'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=lowercase_,	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'''

lowerCAmelCase_						   =			{0: [1, 2], 1: [0, 3], 2: [0], 3: [1], 4: [5, 6], 5: [4, 6], 6: [4, 5]}

lowerCAmelCase_						   =			{0: [1, 2, 3], 1: [0, 3], 2: [0], 3: [0, 1], 4: [], 5: []}

def     __magic_name__       ( A					,   A					,   A							)			->		list:
	snake_case							 =				True
	snake_case							 =				[]

	for neighbour in graph[vert]:
		if not visited[neighbour]:
			connected_verts += dfs(A					,   A					,   A							)

	return [vert, *connected_verts]

def     __magic_name__       ( A							)			->		list:
	snake_case							 =				len(A							)
	snake_case							 =				graph_size * [False]
	snake_case							 =				[]

	for i in range(A							):
		if not visited[i]:
			snake_case							 =				dfs(A					,   A					,   A							)
			components_list.append(A							)

	return components_list


if __name__ == "__main__":
						import doctest

						doctest.testmod()





