


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mpnet import MPNetTokenizer


_A		:					str          =							logging.get_logger(__name__)

_A		:					Any          =							{'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

_A		:					Union[str, Any]          =							{
    '''vocab_file''': {
        '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/vocab.txt''',
    },
    '''tokenizer_file''': {
        '''microsoft/mpnet-base''': '''https://huggingface.co/microsoft/mpnet-base/resolve/main/tokenizer.json''',
    },
}

_A		:					Union[str, Any]          =							{
    '''microsoft/mpnet-base''': 512,
}

_A		:					Union[str, Any]          =							{
    '''microsoft/mpnet-base''': {'''do_lower_case''': True},
}



class 							a       (      _UpperCAmelCase ):
     UpperCAmelCase__			:	str       =						VOCAB_FILES_NAMES
     UpperCAmelCase__			:	Optional[Any]       =						PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__			:	Tuple       =						PRETRAINED_INIT_CONFIGURATION
     UpperCAmelCase__			:	Union[str, Any]       =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__			:	str       =						MPNetTokenizer
     UpperCAmelCase__			:	Optional[Any]       =						["input_ids", "attention_mask"]





     def __init__(     self       :					int     ,						SCREAMING_SNAKE_CASE_       :					Tuple=None     ,						SCREAMING_SNAKE_CASE_       :					int=None     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]=True     ,						SCREAMING_SNAKE_CASE_       :					List[Any]="<s>"     ,						SCREAMING_SNAKE_CASE_       :					List[str]="</s>"     ,						SCREAMING_SNAKE_CASE_       :					Tuple="</s>"     ,						SCREAMING_SNAKE_CASE_       :					str="<s>"     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any]="[UNK]"     ,						SCREAMING_SNAKE_CASE_       :					str="<pad>"     ,						SCREAMING_SNAKE_CASE_       :					Tuple="<mask>"     ,						SCREAMING_SNAKE_CASE_       :					int=True     ,						SCREAMING_SNAKE_CASE_       :					List[Any]=None     ,						**SCREAMING_SNAKE_CASE_       :					Optional[int]     ,						):
        super().__init__(
            lowercase__     ,						tokenizer_file=lowercase__     ,						do_lower_case=lowercase__     ,						bos_token=lowercase__     ,						eos_token=lowercase__     ,						sep_token=lowercase__     ,						cls_token=lowercase__     ,						unk_token=lowercase__     ,						pad_token=lowercase__     ,						mask_token=lowercase__     ,						tokenize_chinese_chars=lowercase__     ,						strip_accents=lowercase__     ,						**lowercase__     ,						)

        __lowerCamelCase:					str	 =						json.loads(self.backend_tokenizer.normalizer.__getstate__()				)
        if (
            pre_tok_state.get("""lowercase"""     ,						lowercase__				) != do_lower_case
            or pre_tok_state.get("""strip_accents"""     ,						lowercase__				) != strip_accents
        ):
           __lowerCamelCase:					Dict	 =						getattr(lowercase__     ,						pre_tok_state.pop("""type"""				)				)
           __lowerCamelCase:					Any	 =						do_lower_case
           __lowerCamelCase:					Tuple	 =						strip_accents
           __lowerCamelCase:					str	 =						pre_tok_class(**lowercase__				)

        __lowerCamelCase:					Union[str, Any]	 =						do_lower_case





     @property
     def 			SCREAMING_SNAKE_CASE__							(     self       :					str				):







        if self._mask_token is None:
           if self.verbose:
              logger.error("""Using mask_token, but it is not set yet."""				)
           return None
        return str(self._mask_token				)





     @mask_token.setter
     def 			SCREAMING_SNAKE_CASE__							(     self       :					Optional[int]     ,						SCREAMING_SNAKE_CASE_       :					List[str]				):
        __lowerCamelCase:					Optional[int]	 =						AddedToken(lowercase__     ,						lstrip=lowercase__     ,						rstrip=lowercase__				) if isinstance(lowercase__     ,						lowercase__				) else value
        __lowerCamelCase:					Optional[int]	 =						value





     def 			SCREAMING_SNAKE_CASE__							(     self       :					List[Any]     ,						SCREAMING_SNAKE_CASE_       :					Tuple     ,						SCREAMING_SNAKE_CASE_       :					Dict=None				):
        __lowerCamelCase:					List[Any]	 =						[self.bos_token_id] + token_ids_a + [self.eos_token_id]
        if token_ids_a is None:
           return output

        return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





     def 			SCREAMING_SNAKE_CASE__							(     self       :					Optional[int]     ,						SCREAMING_SNAKE_CASE_       :					Dict     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any] = None				):
        __lowerCamelCase:					Any	 =						[self.sep_token_id]
        __lowerCamelCase:					Optional[Any]	 =						[self.cls_token_id]

        if token_ids_a is None:
           return len(cls + token_ids_a + sep				) * [0]
        return len(cls + token_ids_a + sep + sep + token_ids_a + sep				) * [0]







     def 			SCREAMING_SNAKE_CASE__							(     self       :					Any     ,						SCREAMING_SNAKE_CASE_       :					Union[str, Any]     ,						SCREAMING_SNAKE_CASE_       :					Optional[Any] = None				):
        __lowerCamelCase:					Optional[Any]	 =						self._tokenizer.model.save(lowercase__     ,						name=lowercase__				)
        return tuple(lowercase__				)




"""simple docstring"""




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


snake_case					  =						logging.get_logger(__name__)

snake_case					  =						{
    # pcqm4mv1 now deprecated
    'graphormer-base': 'https://huggingface.co/clefourrier/graphormer-base-pcqm4mv2/resolve/main/config.json',
    # See all Graphormer models at https://huggingface.co/models?filter=graphormer
}




class 	UpperCamelCase      (			__magic_name__ ):

				"""simple docstring"""



				UpperCAmelCase_							: Dict		    =							"graphormer"
				UpperCAmelCase_							: Optional[int]		    =							["past_key_values"]


				def __init__(							self						,      lowercase__ = 1						,      lowercase__ = 512 * 9						,      lowercase__ = 512 * 3						,      lowercase__ = 512						,      lowercase__ = 512						,      lowercase__ = 512						,      lowercase__ = 128						,      lowercase__ = 5						,      lowercase__ = 1024						,      lowercase__ = "multi_hop"						,      lowercase__ = 512						,      lowercase__ = False						,      lowercase__ = 12						,      lowercase__ = 768						,      lowercase__ = 768						,      lowercase__ = 32						,      lowercase__ = 0.1						,      lowercase__ = 0.1						,      lowercase__ = 0.0						,      lowercase__ = False						,      lowercase__ = False						,      lowercase__ = False						,      lowercase__ = "gelu"						,      lowercase__ = None						,      lowercase__ = False						,      lowercase__ = 0						,      lowercase__ = False						,      lowercase__ = 0.0						,      lowercase__ = 8						,      lowercase__ = None						,      lowercase__ = None						,      lowercase__ = True						,      lowercase__ = True						,      lowercase__=0						,      lowercase__=1						,      lowercase__=2						,      **lowercase__						,      )       ->       str:
									"""simple docstring"""







									SCREAMING_SNAKE_CASE           =      num_classes
									SCREAMING_SNAKE_CASE           =      num_atoms
									SCREAMING_SNAKE_CASE           =      num_in_degree
									SCREAMING_SNAKE_CASE           =      num_out_degree
									SCREAMING_SNAKE_CASE           =      num_edges
									SCREAMING_SNAKE_CASE           =      num_spatial
									SCREAMING_SNAKE_CASE           =      num_edge_dis
									SCREAMING_SNAKE_CASE           =      edge_type
									SCREAMING_SNAKE_CASE           =      multi_hop_max_dist
									SCREAMING_SNAKE_CASE           =      spatial_pos_max
									SCREAMING_SNAKE_CASE           =      max_nodes
									SCREAMING_SNAKE_CASE           =      num_hidden_layers
									SCREAMING_SNAKE_CASE           =      embedding_dim
									SCREAMING_SNAKE_CASE           =      embedding_dim
									SCREAMING_SNAKE_CASE           =      ffn_embedding_dim
									SCREAMING_SNAKE_CASE           =      num_attention_heads
									SCREAMING_SNAKE_CASE           =      dropout
									SCREAMING_SNAKE_CASE           =      attention_dropout
									SCREAMING_SNAKE_CASE           =      layerdrop
									SCREAMING_SNAKE_CASE           =      encoder_normalize_before
									SCREAMING_SNAKE_CASE           =      pre_layernorm
									SCREAMING_SNAKE_CASE           =      apply_graphormer_init
									SCREAMING_SNAKE_CASE           =      activation_fn
									SCREAMING_SNAKE_CASE           =      embed_scale
									SCREAMING_SNAKE_CASE           =      freeze_embeddings
									SCREAMING_SNAKE_CASE           =      num_trans_layers_to_freeze
									SCREAMING_SNAKE_CASE           =      share_input_output_embed
									SCREAMING_SNAKE_CASE           =      traceable
									SCREAMING_SNAKE_CASE           =      q_noise
									SCREAMING_SNAKE_CASE           =      qn_block_size

									# These parameters are here for future extensions
									# atm, the model only supports self attention
									SCREAMING_SNAKE_CASE           =      kdim
									SCREAMING_SNAKE_CASE           =      vdim
									SCREAMING_SNAKE_CASE           =      self_attention
									SCREAMING_SNAKE_CASE           =      bias

									super().__init__(
									    pad_token_id=lowercase__						,      bos_token_id=lowercase__						,      eos_token_id=lowercase__						,      **lowercase__						,      )
