


from collections import OrderedDict
from typing import Mapping

from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging


snake_case    :   Dict	    =					logging.get_logger(__name__)

snake_case    :   List[str]	    =					{
    '''google/bigbird-roberta-base''': '''https://huggingface.co/google/bigbird-roberta-base/resolve/main/config.json''',
    '''google/bigbird-roberta-large''': '''https://huggingface.co/google/bigbird-roberta-large/resolve/main/config.json''',
    '''google/bigbird-base-trivia-itc''': '''https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/config.json''',
    # See all BigBird models at https://huggingface.co/models?filter=big_bird
}







class 		_snake_case  (				_snake_case							):
 SCREAMING_SNAKE_CASE__				=	'big_bird'




 def __init__(		self ,  _lowerCamelCase=5_0358 ,  _lowerCamelCase=768 ,  _lowerCamelCase=12 ,  _lowerCamelCase=12 ,  _lowerCamelCase=3072 ,  _lowerCamelCase="gelu_new" ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=0.1 ,  _lowerCamelCase=4096 ,  _lowerCamelCase=2 ,  _lowerCamelCase=0.02 ,  _lowerCamelCase=1e-12 ,  _lowerCamelCase=True ,  _lowerCamelCase=0 ,  _lowerCamelCase=1 ,  _lowerCamelCase=2 ,  _lowerCamelCase=66 ,  _lowerCamelCase="block_sparse" ,  _lowerCamelCase=True ,  _lowerCamelCase=False ,  _lowerCamelCase=64 ,  _lowerCamelCase=3 ,  _lowerCamelCase=None ,  **_lowerCamelCase ,  ):
       super().__init__(
           pad_token_id=_lowerCamelCase ,  bos_token_id=_lowerCamelCase ,  eos_token_id=_lowerCamelCase ,  sep_token_id=_lowerCamelCase ,  **_lowerCamelCase ,  )

       a						:str										=	vocab_size
       a						:List[str]										=	max_position_embeddings
       a						:List[str]										=	hidden_size
       a						:str										=	num_hidden_layers
       a						:List[str]										=	num_attention_heads
       a						:List[Any]										=	intermediate_size
       a						:Any										=	hidden_act
       a						:Any										=	hidden_dropout_prob
       a						:str										=	attention_probs_dropout_prob
       a						:Union[str, Any]										=	initializer_range
       a						:str										=	type_vocab_size
       a						:Optional[Any]										=	layer_norm_eps
       a						:Optional[int]										=	use_cache

       a						:int										=	rescale_embeddings
       a						:str										=	attention_type
       a						:List[Any]										=	use_bias
       a						:int										=	block_size
       a						:str										=	num_random_blocks
       a						:Dict										=	classifier_dropout







class 		_snake_case  (				_snake_case							):




 @property
 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       if self.task == "multiple-choice":
             a						:List[str]										=	{0: '''batch''', 1: '''choice''', 2: '''sequence'''}
       else:
             a						:Any										=	{0: '''batch''', 1: '''sequence'''}
       return OrderedDict(
           [
               ('''input_ids''', dynamic_axis),
               ('''attention_mask''', dynamic_axis),
           ]   )









import os
import unittest

from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir

from ...test_tokenization_common import TokenizerTesterMixin


snake_case    :   List[Any]	    =					get_tests_dir('''fixtures/test_sentencepiece_bpe.model''')







class 		_snake_case  (				_snake_case						,   unittest.TestCase							):
 SCREAMING_SNAKE_CASE__				=	BartphoTokenizer
 SCREAMING_SNAKE_CASE__				=	False
 SCREAMING_SNAKE_CASE__				=	True




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       super().setUp()

       a						:Dict										=	['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']
       a						:Optional[Any]										=	dict(zip(_lowerCamelCase ,  range(len(_lowerCamelCase   )   )   )   )
       a						:Tuple										=	{'''unk_token''': '''<unk>'''}

       a						:Union[str, Any]										=	os.path.join(self.tmpdirname ,  VOCAB_FILES_NAMES['''monolingual_vocab_file''']   )
       with open(self.monolingual_vocab_file ,  '''w''' ,  encoding='''utf-8'''   ) as fp:
             for token in vocab_tokens:
                   fp.write(F'''{token} {vocab_tokens[token]}\n'''   )

       a						:Any										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       tokenizer.save_pretrained(self.tmpdirname   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  **_lowerCamelCase   ):
       kwargs.update(self.special_tokens_map   )
       return BartphoTokenizer.from_pretrained(self.tmpdirname ,  **_lowerCamelCase   )




 def 	SCREAMING_SNAKE_CASE__    (		self ,  _lowerCamelCase   ):
       a						:int										=	'''This is a là test'''
       a						:str										=	'''This is a<unk><unk> test'''
       return input_text, output_text




 def 	SCREAMING_SNAKE_CASE__    (		self   ):
       a						:List[str]										=	BartphoTokenizer(_lowerCamelCase ,  self.monolingual_vocab_file ,  **self.special_tokens_map   )
       a						:Optional[Any]										=	'''This is a là test'''
       a						:Tuple										=	'''▁This ▁is ▁a ▁l à ▁t est'''.split()
       a						:int										=	tokenizer.tokenize(_lowerCamelCase   )
       self.assertListEqual(_lowerCamelCase ,  _lowerCamelCase   )

       a						:Union[str, Any]										=	tokens + [tokenizer.unk_token]
       a						:str										=	[4, 5, 6, 3, 3, 7, 8, 3]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(_lowerCamelCase   ) ,  _lowerCamelCase   )





