






import unittest

from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available

from ...test_tokenization_common import TokenizerTesterMixin


lowerCamelCase       :       Any        =				get_tests_dir('''fixtures/test_sentencepiece.model''')
lowerCamelCase       :       Any        =				get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')

lowerCamelCase       :       Optional[int]        =				'''pt''' if is_torch_available() else '''tf'''

@require_sentencepiece
@require_tokenizers
class 						lowerCAmelCase   (       __a					,				unittest.TestCase	):

					'''simple docstring'''

					_A  :	Dict     =					CamembertTokenizer
					_A  :	Union[str, Any]     =					CamembertTokenizerFast
					_A  :	Union[str, Any]     =					True
					_A  :	Tuple     =					True



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


												"""simple docstring"""

												super().setUp()

												# We have a SentencePiece fixture for testing
												__lowercase					:							Union[str, Any]			=   CamembertTokenizer(__a							)
												tokenizer.save_pretrained(self.tmpdirname							)



					def 					lowerCAmelCase (     self :		Optional[int]							)	->     Optional[Any]:


												"""simple docstring"""

												__lowercase					:							Dict			=   """<pad>"""
												__lowercase					:							Dict			=   1

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



					def 					lowerCAmelCase (     self :		Optional[Any]							)	->     Tuple:


												"""simple docstring"""

												__lowercase					:							int			=   list(self.get_tokenizer().get_vocab().keys()							)

												self.assertEqual(vocab_keys[0]						,   """<s>NOTUSED"""							)
												self.assertEqual(vocab_keys[1]						,   """<pad>"""							)
												self.assertEqual(vocab_keys[-1]						,   """<mask>"""							)
												self.assertEqual(len(__a							)						,   1004							)



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


												"""simple docstring"""

												self.assertEqual(self.get_tokenizer().vocab_size						,   1005							)



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


												"""simple docstring"""

												__lowercase					:							Tuple			=   CamembertTokenizer(__a							)
												tokenizer.save_pretrained(self.tmpdirname							)
												__lowercase					:							Tuple			=   CamembertTokenizerFast.from_pretrained(self.tmpdirname							)

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

												__lowercase					:							Optional[Any]			=   tokenizer.encode(__a							)
												__lowercase					:							List[Any]			=   rust_tokenizer.encode(__a							)
												self.assertListEqual(__a						,   __a							)

												__lowercase					:							Tuple			=   tokenizer.encode(__a						,   add_special_tokens=__a							)
												__lowercase					:							Union[str, Any]			=   rust_tokenizer.encode(__a						,   add_special_tokens=__a							)
												self.assertListEqual(__a						,   __a							)

												# <unk> tokens are not the same for `rust` than for `slow`.
												# Because spm gives back raw token instead of `unk` in EncodeAsPieces
												# tokens = tokenizer.tokenize(sequence)
												__lowercase					:							Dict			=   tokenizer.convert_ids_to_tokens(__a							)
												__lowercase					:							Any			=   rust_tokenizer.tokenize(__a							)
												self.assertListEqual(__a						,   __a							)



					def 					lowerCAmelCase (     self :		Any							)	->     Dict:


												"""simple docstring"""

												if not self.test_rust_tokenizer:
																			return

												__lowercase					:							List[str]			=   self.get_tokenizer()
												__lowercase					:							Any			=   self.get_rust_tokenizer()

												__lowercase					:							Any			=   """I was born in 92000, and this is falsé."""

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

												__lowercase					:							Dict			=   tokenizer.encode(__a						,   add_special_tokens=__a							)
												__lowercase					:							Dict			=   rust_tokenizer.encode(__a						,   add_special_tokens=__a							)
												self.assertListEqual(__a						,   __a							)

												__lowercase					:							Any			=   self.get_rust_tokenizer()
												__lowercase					:							str			=   tokenizer.encode(__a							)
												__lowercase					:							Union[str, Any]			=   rust_tokenizer.encode(__a							)
												self.assertListEqual(__a						,   __a							)



					@slow
					def 					lowerCAmelCase (     self :		Optional[int]							)	->     List[Any]:


												"""simple docstring"""

												__lowercase					:							str			=   {"""input_ids""": [[5, 54, 7196, 297, 30, 23, 776, 18, 11, 3215, 3705, 8252, 22, 3164, 1181, 2116, 29, 16, 813, 25, 791, 3314, 20, 3446, 38, 27575, 120, 6, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [5, 468, 17, 11, 9088, 20, 1517, 8, 22804, 18818, 10, 38, 629, 607, 607, 142, 19, 7196, 867, 56, 10326, 24, 2267, 20, 416, 5072, 15612, 233, 734, 7, 2399, 27, 16, 3015, 1649, 7, 24, 20, 4338, 2399, 27, 13, 3400, 14, 13, 6189, 8, 930, 9, 6]], """attention_mask""": [[1, 1, 1, 1, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]}  # noqa: E501
												# fmt: on

												# camembert is a french model. So we also use french texts.
												__lowercase					:							List[str]			=   [
												    """Le transformeur est un modèle d'apprentissage profond introduit en 2017, """
												    """utilisé principalement dans le domaine du traitement automatique des langues (TAL).""",
												    """À l'instar des réseaux de neurones récurrents (RNN), les transformeurs sont conçus """
												    """pour gérer des données séquentielles, telles que le langage naturel, pour des tâches """
												    """telles que la traduction et la synthèse de texte.""",
												]

												self.tokenizer_integration_test_util(
												    expected_encoding=__a						,   model_name="""camembert-base"""						,   revision="""3a0641d9a1aeb7e848a74299e7e4c4bca216b4cf"""						,   sequences=__a						,   )







from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase       :       Optional[Any]        =				logging.get_logger(__name__)

lowerCamelCase       :       List[str]        =				{
    '''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/config.json''',
    # See all CANINE models at https://huggingface.co/models?filter=canine
}

class 						lowerCAmelCase   (       __a	):

					'''simple docstring'''

					_A  :	List[Any]     =					'''canine'''



					def __init__(     self :		List[str]						,   __a :		Optional[int]=768						,   __a :		Any=12						,   __a :		Any=12						,   __a :		Dict=3072						,   __a :		Dict="gelu"						,   __a :		List[Any]=0.1						,   __a :		List[Any]=0.1						,   __a :		Tuple=16384						,   __a :		List[Any]=16						,   __a :		List[Any]=0.02						,   __a :		Optional[Any]=1E-12						,   __a :		Dict=0						,   __a :		List[Any]=0xe_0_0_0						,   __a :		Optional[int]=0xe_0_0_1						,   __a :		Any=4						,   __a :		Dict=4						,   __a :		Optional[int]=8						,   __a :		Any=16384						,   __a :		Optional[Any]=128						,   **__a :		List[str]						,   )	->     Union[str, Any]:


												"""simple docstring"""

												super().__init__(pad_token_id=__a						,   bos_token_id=__a						,   eos_token_id=__a						,   **__a							)

												__lowercase					:							int			=   max_position_embeddings
												__lowercase					:							List[str]			=   hidden_size
												__lowercase					:							List[Any]			=   num_hidden_layers
												__lowercase					:							Dict			=   num_attention_heads
												__lowercase					:							int			=   intermediate_size
												__lowercase					:							Dict			=   hidden_act
												__lowercase					:							Tuple			=   hidden_dropout_prob
												__lowercase					:							Union[str, Any]			=   attention_probs_dropout_prob
												__lowercase					:							Union[str, Any]			=   initializer_range
												__lowercase					:							Any			=   type_vocab_size
												__lowercase					:							int			=   layer_norm_eps

												# Character config:
												__lowercase					:							int			=   downsampling_rate
												__lowercase					:							str			=   upsampling_kernel_size
												__lowercase					:							Union[str, Any]			=   num_hash_functions
												__lowercase					:							Optional[Any]			=   num_hash_buckets
												__lowercase					:							Optional[int]			=   local_transformer_stride