



"""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


A_	:						List[str]				=			get_tests_dir('fixtures/spiece.model')
@require_sentencepiece
@require_tokenizers
class 						lowerCAmelCase__	(  _lowerCamelCase       ,       unittest.TestCase   ):


	'''simple docstring'''







	_SCREAMING_SNAKE_CASE  :		int     	=   ErnieMTokenizer
	_SCREAMING_SNAKE_CASE  :		int     	=   False
	_SCREAMING_SNAKE_CASE  :		Tuple     	=   True
	_SCREAMING_SNAKE_CASE  :		Any     	=   False
	_SCREAMING_SNAKE_CASE  :		Any     	=   False





	def  _lowerCAmelCase    (			self							:					List[Any]						)	->  str:





					"""simple docstring"""


					super().setUp()

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





	def  _lowerCAmelCase    (			self							:					List[str]    ,					_SCREAMING_SNAKE_CASE							:					Any						)	->  List[Any]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       List[Any] 							=    'this is a test'
					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    'this is a test'
					return input_text, output_text





	def  _lowerCAmelCase    (			self							:					Dict						)	->  Any:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Any 							=    '<pad>'
					SCREAMING_SNAKE_CASE	:       Union[str, Any] 							=    0

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





	def  _lowerCAmelCase    (			self							:					str						)	->  Any:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       List[str] 							=    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(_SCREAMING_SNAKE_CASE						)    ,					30_000						)





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





					"""simple docstring"""


					self.assertEqual(self.get_tokenizer().vocab_size    ,					30_000						)





	def  _lowerCAmelCase    (			self							:					List[str]						)	->  str:





					"""simple docstring"""


					if not self.test_rust_tokenizer:
									return

					SCREAMING_SNAKE_CASE	:       Tuple 							=    self.get_tokenizer()
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    self.get_rust_tokenizer()

					SCREAMING_SNAKE_CASE	:       List[str] 							=    'I was born in 92000, and this is falsé.'

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

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

					SCREAMING_SNAKE_CASE	:       Dict 							=    self.get_rust_tokenizer()
					SCREAMING_SNAKE_CASE	:       List[str] 							=    tokenizer.encode(_SCREAMING_SNAKE_CASE						)
					SCREAMING_SNAKE_CASE	:       Any 							=    rust_tokenizer.encode(_SCREAMING_SNAKE_CASE						)
					self.assertListEqual(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE						)





	def  _lowerCAmelCase    (			self							:					Optional[Any]						)	->  List[str]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       int 							=    ErnieMTokenizer(_SCREAMING_SNAKE_CASE    ,					do_lower_case=_SCREAMING_SNAKE_CASE    ,					unk_token='<unk>'    ,					pad_token='<pad>'						)

					SCREAMING_SNAKE_CASE	:       List[Any] 							=    tokenizer.tokenize('This is a test'						)
					self.assertListEqual(_SCREAMING_SNAKE_CASE    ,					['▁this', '▁is', '▁a', '▁test']						)

					self.assertListEqual(tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE						)    ,					[48, 25, 21, 1_289]						)

					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(
					    _SCREAMING_SNAKE_CASE    ,					['▁i', '▁was', '▁born', '▁in', '9', '2000', ',', '▁and', '▁this', '▁is', '▁fal', 's', 'é', '.']						)
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    tokenizer.convert_tokens_to_ids(_SCREAMING_SNAKE_CASE						)
					self.assertListEqual(_SCREAMING_SNAKE_CASE    ,					[31, 23, 386, 19, 518, 3_050, 15, 17, 48, 25, 8_256, 18, 1, 9]						)

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





	def  _lowerCAmelCase    (			self							:					str						)	->  Optional[Any]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       str 							=    ErnieMTokenizer(_SCREAMING_SNAKE_CASE    ,					unk_token='<unk>'    ,					pad_token='<pad>'						)

					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    tokenizer.encode('sequence builders'						)
					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    tokenizer.encode('multi-sequence build'						)

					SCREAMING_SNAKE_CASE	:       Optional[Any] 							=    tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE						)
					SCREAMING_SNAKE_CASE	:       Optional[int] 							=    tokenizer.build_inputs_with_special_tokens(_SCREAMING_SNAKE_CASE    ,					_SCREAMING_SNAKE_CASE						)

					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							:					Tuple						)	->  Any:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       Any 							=    {'input_ids': [[0, 11_062, 82_772, 7, 15, 82_772, 538, 51_529, 237, 17_198, 1_290, 206, 9, 215_175, 1_314, 136, 17_198, 1_290, 206, 9, 56_359, 42, 122_009, 9, 16_466, 16, 87_344, 4_537, 9, 4_717, 78_381, 6, 159_958, 7, 15, 24_480, 618, 4, 527, 22_693, 9, 304, 4, 2_777, 24_480, 9_874, 4, 43_523, 594, 4, 803, 18_392, 33_189, 18, 4, 43_523, 24_447, 5, 5, 5, 16, 100, 24_955, 83_658, 9_626, 144_057, 15, 839, 22_335, 16, 136, 24_955, 83_658, 83_479, 15, 39_102, 724, 16, 678, 645, 6_460, 1_328, 4_589, 42, 122_009, 115_774, 23, 3_559, 1_328, 46_876, 7, 136, 53_894, 1_940, 42_227, 41_159, 17_721, 823, 425, 4, 27_512, 98_722, 206, 136, 5_531, 4_970, 919, 17_336, 5, 2], [0, 20_080, 618, 83, 82_775, 47, 479, 9, 1_517, 73, 53_894, 333, 80_581, 110_117, 18_811, 5_256, 1_295, 51, 152_526, 297, 7_986, 390, 124_416, 538, 35_431, 214, 98, 15_044, 25_737, 136, 7_108, 43_701, 23, 756, 135_355, 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, 63_773, 119_455, 6, 147_797, 88_203, 7, 645, 70, 21, 3_285, 10_269, 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=_SCREAMING_SNAKE_CASE    ,					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"""

import platform
from argparse import ArgumentParser

import huggingface_hub
import pandas
import pyarrow

from datasets import __version__ as version
from datasets.commands import BaseDatasetsCLICommand
def    __snake_case       (  __A			:	Union[str, Any]    )    ->					Tuple:






				'''simple docstring'''
				return EnvironmentCommand()







class 						lowerCAmelCase__	(  _lowerCamelCase   ):


	'''simple docstring'''







	@staticmethod
	def  _lowerCAmelCase    (			_SCREAMING_SNAKE_CASE							:					ArgumentParser						)	->  str:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       int 							=    parser.add_parser('env'    ,					help='Print relevant system environment info.'						)
					download_parser.set_defaults(func=_SCREAMING_SNAKE_CASE						)





	def  _lowerCAmelCase    (			self							:					Optional[int]						)	->  Optional[int]:





					"""simple docstring"""


					SCREAMING_SNAKE_CASE	:       int 							=    {
					    '`datasets` version': version,
					    'Platform': platform.platform(),
					    'Python version': platform.python_version(),
					    'Huggingface_hub version': huggingface_hub.__version__,
					    'PyArrow version': pyarrow.__version__,
					    'Pandas version': pandas.__version__,
					}

					print('\nCopy-and-paste the text below in your GitHub issue.\n'						)
					print(self.format_dict(_SCREAMING_SNAKE_CASE						)						)

					return info







	@staticmethod
	def  _lowerCAmelCase    (			_SCREAMING_SNAKE_CASE							:					Optional[Any]						)	->  List[Any]:





					"""simple docstring"""


					return "\n".join([f"""- {prop}: {val}""" for prop, val in d.items()]						) + "\n"





