






from collections import OrderedDict
from typing import Mapping

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


lowerCamelCase      :       Tuple    =						logging.get_logger(__name__)

lowerCamelCase      :       Union[str, Any]    =						{
    "andreasmadsen/efficient_mlm_m0.40": (
        "https://huggingface.co/andreasmadsen/efficient_mlm_m0.40/resolve/main/config.json"
    ),
}



class 				_UpperCamelCase      (a_      ):
      snake_case_	=				"roberta-prelayernorm"


      def __init__(						self       ,    __UpperCamelCase=5_0_2_6_5       ,    __UpperCamelCase=7_6_8       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=1_2       ,    __UpperCamelCase=3_0_7_2       ,    __UpperCamelCase="gelu"       ,    __UpperCamelCase=0.1       ,    __UpperCamelCase=0.1       ,    __UpperCamelCase=5_1_2       ,    __UpperCamelCase=2       ,    __UpperCamelCase=0.0_2       ,    __UpperCamelCase=1e-12       ,    __UpperCamelCase=1       ,    __UpperCamelCase=0       ,    __UpperCamelCase=2       ,    __UpperCamelCase="absolute"       ,    __UpperCamelCase=True       ,    __UpperCamelCase=None       ,    **__UpperCamelCase       ,    )->						Optional[int]:
           super().__init__(pad_token_id=__UpperCamelCase       ,    bos_token_id=__UpperCamelCase       ,    eos_token_id=__UpperCamelCase       ,    **__UpperCamelCase						)

           __lowerCAmelCase             =       vocab_size
           __lowerCAmelCase             =       hidden_size
           __lowerCAmelCase             =       num_hidden_layers
           __lowerCAmelCase             =       num_attention_heads
           __lowerCAmelCase             =       hidden_act
           __lowerCAmelCase             =       intermediate_size
           __lowerCAmelCase             =       hidden_dropout_prob
           __lowerCAmelCase             =       attention_probs_dropout_prob
           __lowerCAmelCase             =       max_position_embeddings
           __lowerCAmelCase             =       type_vocab_size
           __lowerCAmelCase             =       initializer_range
           __lowerCAmelCase             =       layer_norm_eps
           __lowerCAmelCase             =       position_embedding_type
           __lowerCAmelCase             =       use_cache
           __lowerCAmelCase             =       classifier_dropout



class 				_UpperCamelCase      (a_      ):


      @property
      def 			__UpperCAmelCase		(						self						)->						Mapping[str, Mapping[int, str]]:

           if self.task == "multiple-choice":
                __lowerCAmelCase             =       {0: "batch", 1: "choice", 2: "sequence"}
           else:
                __lowerCAmelCase             =       {0: "batch", 1: "sequence"}
           return OrderedDict(
               [
                   ("input_ids", dynamic_axis),
                   ("attention_mask", dynamic_axis),
               ]						)











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    UpperCAmelCase__(				lowerCamelCase  ,				unittest.TestCase						):

   '''simple docstring'''




   A     :	Optional[int]												=     CpmAntTokenizer
   A     :	Optional[int]												=     False


   def       UpperCAmelCase		(    self	:      List[str])						->					str:




         """simple docstring"""

         super().setUp()

         lowercase__  =	[
             '<d>',
             '</d>',
             '<s>',
             '</s>',
             '</_>',
             '<unk>',
             '<pad>',
             '</n>',
             '我',
             '是',
             'C',
             'P',
             'M',
             'A',
             'n',
             't',
         ]
         lowercase__  =	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       UpperCAmelCase		(    self	:      str)						->					Optional[Any]:




         """simple docstring"""

         lowercase__  =	CpmAntTokenizer.from_pretrained('openbmb/cpm-ant-10b')
         lowercase__  =	'今天天气真好！'
         lowercase__  =	['今天', '天气', '真', '好', '！']
         lowercase__  =	tokenizer.tokenize(lowerCAmelCase)
         self.assertListEqual(lowerCAmelCase      ,					lowerCAmelCase)
         lowercase__  =	'今天天气真好！'
         lowercase__  =	[tokenizer.bos_token] + tokens

         lowercase__  =	[6, 98_02, 1_49_62, 20_82, 8_31, 2_44]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(lowerCAmelCase)      ,					lowerCAmelCase)

         lowercase__  =	tokenizer.decode(lowerCAmelCase)
         self.assertEqual(lowerCAmelCase      ,					lowerCAmelCase)
