"""simple docstring"""




from collections import OrderedDict
from typing import Mapping

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


_a   :	Dict 					=     logging.get_logger(__name__)

_a   :	List[str] 					=     {
    'camembert-base': 'https://huggingface.co/camembert-base/resolve/main/config.json',
    'umberto-commoncrawl-cased-v1': (
        'https://huggingface.co/Musixmatch/umberto-commoncrawl-cased-v1/resolve/main/config.json'
    ),
    'umberto-wikipedia-uncased-v1': (
        'https://huggingface.co/Musixmatch/umberto-wikipedia-uncased-v1/resolve/main/config.json'
    ),
}
class 		__A							(				__SCREAMING_SNAKE_CASE	):
     _UpperCamelCase							:    str	      =	"camembert"






     def __init__(	self       ,  a__=30522       ,  a__=768       ,  a__=12       ,  a__=12       ,  a__=3072       ,  a__="gelu"       ,  a__=0.1       ,  a__=0.1       ,  a__=512       ,  a__=2       ,  a__=0.0_2       ,  a__=1e-12       ,  a__=1       ,  a__=0       ,  a__=2       ,  a__="absolute"       ,  a__=True       ,  a__=None       ,  **a__       ,  ):
       super().__init__(pad_token_id=__snake_case       ,  bos_token_id=__snake_case       ,  eos_token_id=__snake_case       ,  **__snake_case						)

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







class 		__A							(				__SCREAMING_SNAKE_CASE	):






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







"""simple docstring"""




import os
import unittest

from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow

from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class 		__A							(				SCREAMING_SNAKE_CASE_					,			unittest.TestCase	):
     _UpperCamelCase							:    str	      =	CpmAntTokenizer
     _UpperCamelCase							:    List[Any]	      =	False






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

       _lowerCAmelCase		: Dict						    =  [
           """<d>""",
           """</d>""",
           """<s>""",
           """</s>""",
           """</_>""",
           """<unk>""",
           """<pad>""",
           """</n>""",
           """我""",
           """是""",
           """C""",
           """P""",
           """M""",
           """A""",
           """n""",
           """t""",
       ]
       _lowerCAmelCase		: int						    =  os.path.join(self.tmpdirname       ,  VOCAB_FILES_NAMES["""vocab_file"""]						)
       with open(self.vocab_file       ,  """w"""       ,  encoding="""utf-8"""						) as vocab_writer:
         vocab_writer.write("""""".join([x + """\n""" for x in vocab_tokens]						)						)






     @tooslow
     def 					__A						(	self						):
       _lowerCAmelCase		: Tuple						    =  CpmAntTokenizer.from_pretrained("""openbmb/cpm-ant-10b"""						)
       _lowerCAmelCase		: Optional[Any]						    =  """今天天气真好！"""
       _lowerCAmelCase		: Any						    =  ["""今天""", """天气""", """真""", """好""", """！"""]
       _lowerCAmelCase		: str						    =  tokenizer.tokenize(a__						)
       self.assertListEqual(a__       ,  a__						)
       _lowerCAmelCase		: Tuple						    =  """今天天气真好！"""
       _lowerCAmelCase		: Optional[Any]						    =  [tokenizer.bos_token] + tokens

       _lowerCAmelCase		: Optional[int]						    =  [6, 9802, 14962, 2082, 831, 244]
       self.assertListEqual(tokenizer.convert_tokens_to_ids(a__						)       ,  a__						)

       _lowerCAmelCase		: Tuple						    =  tokenizer.decode(a__						)
       self.assertEqual(a__       ,  a__						)




