




'''simple docstring'''





import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_splinter import SplinterTokenizer


_SCREAMING_SNAKE_CASE							:     List[str]   	=				logging.get_logger(__name__)

_SCREAMING_SNAKE_CASE							:     Any   	=				{"""vocab_file""": """vocab.txt"""}

_SCREAMING_SNAKE_CASE							:     Optional[int]   	=				{
    """vocab_file""": {
        """tau/splinter-base""": """https://huggingface.co/tau/splinter-base/resolve/main/vocab.txt""",
        """tau/splinter-base-qass""": """https://huggingface.co/tau/splinter-base-qass/resolve/main/vocab.txt""",
        """tau/splinter-large""": """https://huggingface.co/tau/splinter-large/resolve/main/vocab.txt""",
        """tau/splinter-large-qass""": """https://huggingface.co/tau/splinter-large-qass/resolve/main/vocab.txt""",
    }
}

_SCREAMING_SNAKE_CASE							:     str   	=				{
    """tau/splinter-base""": 512,
    """tau/splinter-base-qass""": 512,
    """tau/splinter-large""": 512,
    """tau/splinter-large-qass""": 512,
}

_SCREAMING_SNAKE_CASE							:     Optional[Any]   	=				{
    """tau/splinter-base""": {"""do_lower_case""": False},
    """tau/splinter-base-qass""": {"""do_lower_case""": False},
    """tau/splinter-large""": {"""do_lower_case""": False},
    """tau/splinter-large-qass""": {"""do_lower_case""": False},
}




class 				_snake_case	(			a_							):
			lowerCAmelCase_  :   Any		 =					VOCAB_FILES_NAMES
			lowerCAmelCase_  :   List[str]		 =					PRETRAINED_VOCAB_FILES_MAP
			lowerCAmelCase_  :   str		 =					PRETRAINED_INIT_CONFIGURATION
			lowerCAmelCase_  :   List[str]		 =					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			lowerCAmelCase_  :   Any		 =					SplinterTokenizer




			def __init__(      self       ,							a__=None       ,							a__=None       ,							a__=True       ,							a__="[UNK]"       ,							a__="[SEP]"       ,							a__="[PAD]"       ,							a__="[CLS]"       ,							a__="[MASK]"       ,							a__="[QUESTION]"       ,							a__=True       ,							a__=None       ,							**a__       ,							)       ->       int:

										'''simple docstring'''




										super().__init__(
										    _snake_case       ,							tokenizer_file=_snake_case       ,							do_lower_case=_snake_case       ,							unk_token=_snake_case       ,							sep_token=_snake_case       ,							pad_token=_snake_case       ,							cls_token=_snake_case       ,							mask_token=_snake_case       ,							tokenize_chinese_chars=_snake_case       ,							strip_accents=_snake_case       ,							additional_special_tokens=(question_token,)       ,							**_snake_case       ,							)

										snake_case_			      =   json.loads(self.backend_tokenizer.normalizer.__getstate__()							)
										if (
										    pre_tok_state.get("lowercase"       ,							_snake_case							) != do_lower_case
										    or pre_tok_state.get("strip_accents"       ,							_snake_case							) != strip_accents
										):
																	snake_case_			      =   getattr(_snake_case       ,							pre_tok_state.pop("type"							)							)
																	snake_case_			      =   do_lower_case
																	snake_case_			      =   strip_accents
																	snake_case_			      =   pre_tok_class(**_snake_case							)

										snake_case_			      =   do_lower_case




			@property
			def      lowerCAmelCase__       (      self							)       ->       str:

										'''simple docstring'''




										return self.convert_tokens_to_ids(self.question_token							)




			def      lowerCAmelCase__       (      self       ,							a__       ,							a__ = None							)       ->       List[int]:

										'''simple docstring'''




										if token_ids_a is None:
																	return [self.cls_token_id] + token_ids_a + [self.sep_token_id]

										snake_case_			      =   [self.cls_token_id]
										snake_case_			      =   [self.sep_token_id]
										snake_case_			      =   [self.question_token_id] + [self.convert_tokens_to_ids("."							)]
										if self.padding_side == "right":
																	# Input is question-then-context
																	return cls + token_ids_a + question_suffix + sep + token_ids_a + sep
										else:
																	# Input is context-then-question
																	return cls + token_ids_a + sep + token_ids_a + question_suffix + sep




			def      lowerCAmelCase__       (      self       ,							a__       ,							a__ = None							)       ->       List[int]:

										'''simple docstring'''




										snake_case_			      =   [self.sep_token_id]
										snake_case_			      =   [self.cls_token_id]
										snake_case_			      =   [self.question_token_id] + [self.convert_tokens_to_ids("."							)]
										if token_ids_a is None:
																	return len(cls + token_ids_a + sep							) * [0]

										if self.padding_side == "right":
																	# Input is question-then-context
																	return len(cls + token_ids_a + question_suffix + sep							) * [0] + len(token_ids_a + sep							) * [1]
										else:
																	# Input is context-then-question
																	return len(cls + token_ids_a + sep							) * [0] + len(token_ids_a + question_suffix + sep							) * [1]




			def      lowerCAmelCase__       (      self       ,							a__       ,							a__ = None							)       ->       Tuple[str]:

										'''simple docstring'''




										snake_case_			      =   self._tokenizer.model.save(_snake_case       ,							name=_snake_case							)
										return tuple(_snake_case							)










'''simple docstring'''





import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
		import torch

		from transformers import CamembertModel




@require_torch
@require_sentencepiece
@require_tokenizers
class 				_snake_case	(			unittest.TestCase							):




			@slow
			def      lowerCAmelCase__       (      self							)       ->       List[Any]:

										'''simple docstring'''




										snake_case_			      =   CamembertModel.from_pretrained("camembert-base"							)
										model.to(a__							)

										snake_case_			      =   torch.tensor(
										    [[5, 121, 11, 660, 16, 730, 25_543, 110, 83, 6]]       ,							device=a__       ,							dtype=torch.long       ,							)  # J'aime le camembert !
										with torch.no_grad():
																	snake_case_			      =   model(a__							)["last_hidden_state"]
										snake_case_			      =   torch.Size((1, 10, 768)							)
										self.assertEqual(output.shape       ,							a__							)
										# compare the actual values for a slice.
										snake_case_			      =   torch.tensor(
										    [[[-0.0_2_5_4, 0.0_2_3_5, 0.1_0_2_7], [0.0_6_0_6, -0.1_8_1_1, -0.0_4_1_8], [-0.1_5_6_1, -0.1_1_2_7, 0.2_6_8_7]]]       ,							device=a__       ,							dtype=torch.float       ,							)
										# camembert = torch.hub.load('pytorch/fairseq', 'camembert.v0')
										# camembert.eval()
										# expected_slice = roberta.model.forward(input_ids)[0][:, :3, :3].detach()

										self.assertTrue(torch.allclose(output[:, :3, :3]       ,							a__       ,							atol=1e-4							)							)




