
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__       :   Tuple   						=					get_tests_dir("""fixtures/spiece.model""")





@require_sentencepiece
@require_tokenizers
class 						lowercase       (  __UpperCamelCase	,		unittest.TestCase					):
					__a					=    ErnieMTokenizer
					__a					=    False
					__a					=    True
					__a					=    False
					__a					=    False
					def lowercase_			(		self    ):
								"""simple docstring"""







								super().setUp()

								# We have a SentencePiece fixture for testing
								lowerCAmelCase__ :    List[Any]				      =			ErnieMTokenizer(SCREAMING_SNAKE_CASE__ ,	unk_token='''<unk>''' ,	pad_token='''<pad>'''    )
								tokenizer.save_pretrained(self.tmpdirname    )
					def lowercase_			(		self ,	SCREAMING_SNAKE_CASE__    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[Any]				      =			'''this is a test'''
								lowerCAmelCase__ :    Union[str, Any]				      =			'''this is a test'''
								return input_text, output_text
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    int				      =			'''<pad>'''
								lowerCAmelCase__ :    Optional[int]				      =			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 lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Tuple				      =			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__    ) ,	30000    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								self.assertEqual(self.get_tokenizer().vocab_size ,	30000    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								if not self.test_rust_tokenizer:
											return

								lowerCAmelCase__ :    str				      =			self.get_tokenizer()
								lowerCAmelCase__ :    Optional[Any]				      =			self.get_rust_tokenizer()

								lowerCAmelCase__ :    int				      =			'''I was born in 92000, and this is falsé.'''

								lowerCAmelCase__ :    List[str]				      =			tokenizer.tokenize(SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    List[Any]				      =			rust_tokenizer.tokenize(SCREAMING_SNAKE_CASE__    )
								self.assertListEqual(SCREAMING_SNAKE_CASE__ ,	SCREAMING_SNAKE_CASE__    )

								lowerCAmelCase__ :    List[Any]				      =			tokenizer.encode(SCREAMING_SNAKE_CASE__ ,	add_special_tokens=SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    List[Any]				      =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__ ,	add_special_tokens=SCREAMING_SNAKE_CASE__    )
								self.assertListEqual(SCREAMING_SNAKE_CASE__ ,	SCREAMING_SNAKE_CASE__    )

								lowerCAmelCase__ :    str				      =			self.get_rust_tokenizer()
								lowerCAmelCase__ :    int				      =			tokenizer.encode(SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    Union[str, Any]				      =			rust_tokenizer.encode(SCREAMING_SNAKE_CASE__    )
								self.assertListEqual(SCREAMING_SNAKE_CASE__ ,	SCREAMING_SNAKE_CASE__    )
					def lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Optional[Any]				      =			ErnieMTokenizer(SCREAMING_SNAKE_CASE__ ,	do_lower_case=SCREAMING_SNAKE_CASE__ ,	unk_token='''<unk>''' ,	pad_token='''<pad>'''    )

								lowerCAmelCase__ :    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, 1289]    )

								lowerCAmelCase__ :    int				      =			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''', '''.''']    )
								lowerCAmelCase__ :    Union[str, Any]				      =			tokenizer.convert_tokens_to_ids(SCREAMING_SNAKE_CASE__    )
								self.assertListEqual(SCREAMING_SNAKE_CASE__ ,	[31, 23, 386, 19, 518, 3050, 15, 17, 48, 25, 8256, 18, 1, 9]    )

								lowerCAmelCase__ :    str				      =			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 lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    Dict				      =			ErnieMTokenizer(SCREAMING_SNAKE_CASE__ ,	unk_token='''<unk>''' ,	pad_token='''<pad>'''    )

								lowerCAmelCase__ :    str				      =			tokenizer.encode('''sequence builders'''    )
								lowerCAmelCase__ :    Union[str, Any]				      =			tokenizer.encode('''multi-sequence build'''    )

								lowerCAmelCase__ :    List[str]				      =			tokenizer.build_inputs_with_special_tokens(SCREAMING_SNAKE_CASE__    )
								lowerCAmelCase__ :    List[str]				      =			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 lowercase_			(		self    ):
								"""simple docstring"""







								lowerCAmelCase__ :    str				      =			{'''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=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.''',
								    ] ,	)





import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from unittest.mock import Mock, patch

import diffusers.utils.hub_utils





class 						lowercase       (  unittest.TestCase					):
					@patch('''diffusers.utils.hub_utils.get_full_repo_name'''    )
					def lowercase_			(		self ,	SCREAMING_SNAKE_CASE__    ):
								"""simple docstring"""







								lowerCAmelCase__ :    str				      =			'''full_repo_name'''
								with TemporaryDirectory() as tmpdir:
											# Dummy args values
											lowerCAmelCase__ :    Optional[int]				      =			Mock()
											lowerCAmelCase__ :    Optional[int]				      =			tmpdir
											lowerCAmelCase__ :    Optional[Any]				      =			0
											lowerCAmelCase__ :    Optional[int]				      =			'''hub_token'''
											lowerCAmelCase__ :    Tuple				      =			'''dataset_name'''
											lowerCAmelCase__ :    int				      =			0.01
											lowerCAmelCase__ :    Optional[int]				      =			100000
											lowerCAmelCase__ :    Any				      =			10000
											lowerCAmelCase__ :    Union[str, Any]				      =			0.01
											lowerCAmelCase__ :    int				      =			0.02
											lowerCAmelCase__ :    Union[str, Any]				      =			0.03
											lowerCAmelCase__ :    str				      =			0.0_005
											lowerCAmelCase__ :    Dict				      =			0.000_001
											lowerCAmelCase__ :    Tuple				      =			1
											lowerCAmelCase__ :    Optional[int]				      =			10
											lowerCAmelCase__ :    int				      =			0.001
											lowerCAmelCase__ :    Union[str, Any]				      =			0.1
											lowerCAmelCase__ :    Tuple				      =			0.2
											lowerCAmelCase__ :    Optional[int]				      =			True

											# Model card mush be rendered and saved
											diffusers.utils.hub_utils.create_model_card(SCREAMING_SNAKE_CASE__ ,	model_name='''model_name'''    )
											self.assertTrue((Path(SCREAMING_SNAKE_CASE__    ) / '''README.md''').is_file()    )



