



'''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__     (				_lowercase,			unittest.TestCase	):
	__magic_name__		:    Any	    =     CpmAntTokenizer
	__magic_name__		:    Optional[int]	    =     False


	def 				lowercase__  (self : Optional[int]      )     ->			Union[str, Any]:

					"""simple docstring"""

					super().setUp()

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

					"""simple docstring"""

					SCREAMING_SNAKE_CASE  :						Any      					= CpmAntTokenizer.from_pretrained('''openbmb/cpm-ant-10b'''      )
					SCREAMING_SNAKE_CASE  :						Tuple      					= '''今天天气真好！'''
					SCREAMING_SNAKE_CASE  :						Dict      					= ['''今天''', '''天气''', '''真''', '''好''', '''！''']
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= tokenizer.tokenize(__UpperCAmelCase      )
					self.assertListEqual(__UpperCAmelCase,					__UpperCAmelCase      )
					SCREAMING_SNAKE_CASE  :						str      					= '''今天天气真好！'''
					SCREAMING_SNAKE_CASE  :						List[Any]      					= [tokenizer.bos_token] + tokens

					SCREAMING_SNAKE_CASE  :						Any      					= [6, 9802, 14962, 2082, 831, 244]
					self.assertListEqual(tokenizer.convert_tokens_to_ids(__UpperCAmelCase      ),					__UpperCAmelCase      )

					SCREAMING_SNAKE_CASE  :						List[str]      					= tokenizer.decode(__UpperCAmelCase      )
					self.assertEqual(__UpperCAmelCase,					__UpperCAmelCase      )









'''simple docstring'''

from ...configuration_utils import PretrainedConfig
from ...utils import logging


snake_case_			=     logging.get_logger(__name__)

snake_case_			=     {
    """microsoft/markuplm-base""": """https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json""",
    """microsoft/markuplm-large""": """https://huggingface.co/microsoft/markuplm-large/resolve/main/config.json""",
}


class 	a__     (				_lowercase	):
	__magic_name__		:    List[Any]	    =     "markuplm"


	def __init__(self : List[Any],					__UpperCAmelCase : int=30522,					__UpperCAmelCase : Tuple=768,					__UpperCAmelCase : str=12,					__UpperCAmelCase : List[Any]=12,					__UpperCAmelCase : Tuple=3072,					__UpperCAmelCase : Union[str, Any]="gelu",					__UpperCAmelCase : Union[str, Any]=0.1,					__UpperCAmelCase : str=0.1,					__UpperCAmelCase : Union[str, Any]=512,					__UpperCAmelCase : Dict=2,					__UpperCAmelCase : int=0.02,					__UpperCAmelCase : Optional[Any]=1e-12,					__UpperCAmelCase : Union[str, Any]=0,					__UpperCAmelCase : Optional[Any]=0,					__UpperCAmelCase : Union[str, Any]=2,					__UpperCAmelCase : int=256,					__UpperCAmelCase : Tuple=1024,					__UpperCAmelCase : Optional[Any]=216,					__UpperCAmelCase : str=1001,					__UpperCAmelCase : Optional[Any]=32,					__UpperCAmelCase : Dict=50,					__UpperCAmelCase : Union[str, Any]="absolute",					__UpperCAmelCase : Tuple=True,					__UpperCAmelCase : List[str]=None,					**__UpperCAmelCase : Union[str, Any],					)     ->			Union[str, Any]:

					"""simple docstring"""

					super().__init__(
					    pad_token_id=__UpperCAmelCase,					bos_token_id=__UpperCAmelCase,					eos_token_id=__UpperCAmelCase,					**__UpperCAmelCase,					)
					SCREAMING_SNAKE_CASE  :						List[Any]      					= vocab_size
					SCREAMING_SNAKE_CASE  :						Dict      					= hidden_size
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= num_hidden_layers
					SCREAMING_SNAKE_CASE  :						Dict      					= num_attention_heads
					SCREAMING_SNAKE_CASE  :						Any      					= hidden_act
					SCREAMING_SNAKE_CASE  :						Tuple      					= intermediate_size
					SCREAMING_SNAKE_CASE  :						Tuple      					= hidden_dropout_prob
					SCREAMING_SNAKE_CASE  :						List[str]      					= attention_probs_dropout_prob
					SCREAMING_SNAKE_CASE  :						List[str]      					= max_position_embeddings
					SCREAMING_SNAKE_CASE  :						Dict      					= type_vocab_size
					SCREAMING_SNAKE_CASE  :						Tuple      					= initializer_range
					SCREAMING_SNAKE_CASE  :						Optional[Any]      					= layer_norm_eps
					SCREAMING_SNAKE_CASE  :						int      					= position_embedding_type
					SCREAMING_SNAKE_CASE  :						List[Any]      					= use_cache
					SCREAMING_SNAKE_CASE  :						int      					= classifier_dropout
					# additional properties
					SCREAMING_SNAKE_CASE  :						List[Any]      					= max_depth
					SCREAMING_SNAKE_CASE  :						Any      					= max_xpath_tag_unit_embeddings
					SCREAMING_SNAKE_CASE  :						int      					= max_xpath_subs_unit_embeddings
					SCREAMING_SNAKE_CASE  :						Dict      					= tag_pad_id
					SCREAMING_SNAKE_CASE  :						Optional[int]      					= subs_pad_id
					SCREAMING_SNAKE_CASE  :						int      					= xpath_unit_hidden_size




