






from collections import OrderedDict
from typing import Mapping

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


_a      	=  logging.get_logger(__name__)

_a      	=  {
    '''junnyu/roformer_chinese_small''': '''https://huggingface.co/junnyu/roformer_chinese_small/resolve/main/config.json''',
    '''junnyu/roformer_chinese_base''': '''https://huggingface.co/junnyu/roformer_chinese_base/resolve/main/config.json''',
    '''junnyu/roformer_chinese_char_small''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_small/resolve/main/config.json'''
    ),
    '''junnyu/roformer_chinese_char_base''': (
        '''https://huggingface.co/junnyu/roformer_chinese_char_base/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_discriminator''': (
        '''https://huggingface.co/junnyu/roformer_small_discriminator/resolve/main/config.json'''
    ),
    '''junnyu/roformer_small_generator''': (
        '''https://huggingface.co/junnyu/roformer_small_generator/resolve/main/config.json'''
    ),
    # See all RoFormer models at https://huggingface.co/models?filter=roformer
}





class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	UpperCamelCase__								=      "roformer"

	def __init__(							self       ,    UpperCAmelCase=5_0000       ,    UpperCAmelCase=None       ,    UpperCAmelCase=768       ,    UpperCAmelCase=12       ,    UpperCAmelCase=12       ,    UpperCAmelCase=3072       ,    UpperCAmelCase="gelu"       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=0.1       ,    UpperCAmelCase=1536       ,    UpperCAmelCase=2       ,    UpperCAmelCase=0.02       ,    UpperCAmelCase=1e-12       ,    UpperCAmelCase=0       ,    UpperCAmelCase=False       ,    UpperCAmelCase=True       ,    **UpperCAmelCase       ,    ):
							"""simple docstring"""







							super().__init__(pad_token_id=UpperCAmelCase       ,    **UpperCAmelCase    )

							_UpperCAmelCase									=			vocab_size
							_UpperCAmelCase									=			hidden_size if embedding_size is None else embedding_size
							_UpperCAmelCase									=			hidden_size
							_UpperCAmelCase									=			num_hidden_layers
							_UpperCAmelCase									=			num_attention_heads
							_UpperCAmelCase									=			hidden_act
							_UpperCAmelCase									=			intermediate_size
							_UpperCAmelCase									=			hidden_dropout_prob
							_UpperCAmelCase									=			attention_probs_dropout_prob
							_UpperCAmelCase									=			max_position_embeddings
							_UpperCAmelCase									=			type_vocab_size
							_UpperCAmelCase									=			initializer_range
							_UpperCAmelCase									=			layer_norm_eps
							_UpperCAmelCase									=			rotary_value
							_UpperCAmelCase									=			use_cache





class __lowerCamelCase (      snake_case__):





	"""simple docstring"""






	@property
	def        UpperCamelCase    (							self    ):
							"""simple docstring"""







							if self.task == "multiple-choice":
													_UpperCAmelCase									=			{0: 'batch', 1: 'choice', 2: 'sequence'}
							else:
													_UpperCAmelCase									=			{0: 'batch', 1: 'sequence'}
							_UpperCAmelCase									=			{0: 'batch', 1: 'sequence'}
							return OrderedDict(
							    [
							        ('input_ids', dynamic_axis),
							        ('attention_mask', dynamic_axis),
							        ('token_type_ids', 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 		SCREAMING_SNAKE_CASE__				(       _UpperCAmelCase						,      unittest.TestCase  ):
      A_						:				List[str]							=    CpmAntTokenizer
      A_						:				Optional[int]							=    False


      def    a (self       :      Optional[int]      ):





         """simple docstring"""



         super().setUp()

         __snake_case							       =   [
             '''<d>''',
             '''</d>''',
             '''<s>''',
             '''</s>''',
             '''</_>''',
             '''<unk>''',
             '''<pad>''',
             '''</n>''',
             '''我''',
             '''是''',
             '''C''',
             '''P''',
             '''M''',
             '''A''',
             '''n''',
             '''t''',
         ]
         __snake_case							       =   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       :      Dict      ):





         """simple docstring"""



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

         __snake_case							       =   [6, 9802, 1_4962, 2082, 831, 244]
         self.assertListEqual(tokenizer.convert_tokens_to_ids(a__      )				,			a__      )

         __snake_case							       =   tokenizer.decode(a__      )
         self.assertEqual(a__				,			a__      )

