'''simple docstring'''




from collections import OrderedDict
from typing import Any, List, Mapping, Optional

from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging


_lowercase		:					Optional[int]													=		logging.get_logger(__name__)

_lowercase		:					List[str]													=		{
    "gpt2": "https://huggingface.co/gpt2/resolve/main/config.json",
    "gpt2-medium": "https://huggingface.co/gpt2-medium/resolve/main/config.json",
    "gpt2-large": "https://huggingface.co/gpt2-large/resolve/main/config.json",
    "gpt2-xl": "https://huggingface.co/gpt2-xl/resolve/main/config.json",
    "distilgpt2": "https://huggingface.co/distilgpt2/resolve/main/config.json",
}





class        __magic_name__		(       _UpperCAmelCase):
			UpperCamelCase__							=			'''gpt2'''
			UpperCamelCase__							=			['''past_key_values''']
			UpperCamelCase__							=			{
			    '''hidden_size''': '''n_embd''',
			    '''max_position_embeddings''': '''n_positions''',
			    '''num_attention_heads''': '''n_head''',
			    '''num_hidden_layers''': '''n_layer''',
			}







			def __init__(      self							:    str							,     lowercase_							:    Optional[int]=50257							,     lowercase_							:    Dict=1024							,     lowercase_							:    str=768							,     lowercase_							:    Optional[int]=12							,     lowercase_							:    Union[str, Any]=12							,     lowercase_							:    Any=None							,     lowercase_							:    Tuple="gelu_new"							,     lowercase_							:    int=0.1							,     lowercase_							:    Tuple=0.1							,     lowercase_							:    Dict=0.1							,     lowercase_							:    Optional[Any]=1E-5							,     lowercase_							:    Any=0.02							,     lowercase_							:    Union[str, Any]="cls_index"							,     lowercase_							:    Dict=True							,     lowercase_							:    Tuple=None							,     lowercase_							:    List[str]=True							,     lowercase_							:    Tuple=0.1							,     lowercase_							:    Tuple=True							,     lowercase_							:    Tuple=True							,     lowercase_							:    int=50256							,     lowercase_							:    Optional[Any]=50256							,     lowercase_							:    str=False							,     lowercase_							:    List[str]=False							,     **lowercase_							:    int							,     ):
										lowercase_   :     List[Any]									=			vocab_size
										lowercase_   :     List[str]									=			n_positions
										lowercase_   :     Dict									=			n_embd
										lowercase_   :     List[Any]									=			n_layer
										lowercase_   :     Any									=			n_head
										lowercase_   :     Tuple									=			n_inner
										lowercase_   :     List[Any]									=			activation_function
										lowercase_   :     Optional[int]									=			resid_pdrop
										lowercase_   :     str									=			embd_pdrop
										lowercase_   :     Union[str, Any]									=			attn_pdrop
										lowercase_   :     Any									=			layer_norm_epsilon
										lowercase_   :     Optional[int]									=			initializer_range
										lowercase_   :     Tuple									=			summary_type
										lowercase_   :     List[Any]									=			summary_use_proj
										lowercase_   :     Union[str, Any]									=			summary_activation
										lowercase_   :     Optional[int]									=			summary_first_dropout
										lowercase_   :     int									=			summary_proj_to_labels
										lowercase_   :     Any									=			scale_attn_weights
										lowercase_   :     str									=			use_cache
										lowercase_   :     str									=			scale_attn_by_inverse_layer_idx
										lowercase_   :     str									=			reorder_and_upcast_attn

										lowercase_   :     int									=			bos_token_id
										lowercase_   :     List[Any]									=			eos_token_id

										super().__init__(bos_token_id=lowercase_							,     eos_token_id=lowercase_							,     **lowercase_       )





class        __magic_name__		(       _UpperCAmelCase):







			def __init__(      self							:    List[Any]							,     lowercase_							:    int							,     lowercase_							:    str = "default"							,     lowercase_							:    Tuple = None							,     lowercase_							:    Any = False							,     ):
										super().__init__(lowercase_							,     task=lowercase_							,     patching_specs=lowercase_							,     use_past=lowercase_       )
										if not getattr(self._config							,     """pad_token_id"""							,     lowercase_       ):
																	# TODO: how to do that better?
																	lowercase_   :     Tuple									=			0







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    Optional[int]       ):
										lowercase_   :     str									=			OrderedDict({"""input_ids""": {0: """batch""", 1: """sequence"""}}       )
										if self.use_past:
																	self.fill_with_past_key_values_(lowercase_							,     direction="""inputs"""       )
																	lowercase_   :     Tuple									=			{0: """batch""", 1: """past_sequence + sequence"""}
										else:
																	lowercase_   :     Tuple									=			{0: """batch""", 1: """sequence"""}

										return common_inputs







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    Any       ):
										return self._config.n_layer







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    List[str]       ):
										return self._config.n_head







			def       SCREAMING_SNAKE_CASE_	(      self							:    Any							,     lowercase_							:    int							,     lowercase_							:    str = -1							,     lowercase_							:    str = -1							,     lowercase_							:    Optional[Any] = False							,     lowercase_							:    Dict = None							,     ):
										lowercase_   :     Optional[int]									=			super(lowercase_							,     self       ).generate_dummy_inputs(
										    lowercase_							,     batch_size=lowercase_							,     seq_length=lowercase_							,     is_pair=lowercase_							,     framework=lowercase_       )

										# We need to order the input in the way they appears in the forward()
										lowercase_   :     int									=			OrderedDict({"""input_ids""": common_inputs["""input_ids"""]}       )

										# Need to add the past_keys
										if self.use_past:
																	if not is_torch_available():
																								raise ValueError("""Cannot generate dummy past_keys inputs without PyTorch installed."""       )
																	else:
																								import torch

																								lowercase_		,		lowercase_   :     str									=			common_inputs["""input_ids"""].shape
																								# Not using the same length for past_key_values
																								lowercase_   :     Dict									=			seqlen + 2
																								lowercase_   :     Dict									=			(
																								    batch,
																								    self.num_attention_heads,
																								    past_key_values_length,
																								    self._config.hidden_size // self.num_attention_heads,
																								)
																								lowercase_   :     List[Any]									=			[
																								    (torch.zeros(lowercase_       ), torch.zeros(lowercase_       )) for _ in range(self.num_layers       )
																								]

										lowercase_   :     List[Any]									=			common_inputs["""attention_mask"""]
										if self.use_past:
																	lowercase_   :     List[Any]									=			ordered_inputs["""attention_mask"""].dtype
																	lowercase_   :     str									=			torch.cat(
																	    [ordered_inputs["""attention_mask"""], torch.ones(lowercase_							,     lowercase_							,     dtype=lowercase_       )]							,     dim=1       )

										return ordered_inputs







			@property
			def       SCREAMING_SNAKE_CASE_	(      self							:    List[str]       ):
										return 13









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


UpperCAmelCase__        =				logging.get_logger(__name__)

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

UpperCAmelCase__        =				{
    '''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''',
    },
}

UpperCAmelCase__        =				{
    '''microsoft/mpnet-base''': 512,
}

UpperCAmelCase__        =				{
    '''microsoft/mpnet-base''': {'''do_lower_case''': True},
}







class  lowerCamelCase__  (			lowerCAmelCase):
     SCREAMING_SNAKE_CASE__      =     VOCAB_FILES_NAMES
     SCREAMING_SNAKE_CASE__      =     PRETRAINED_VOCAB_FILES_MAP
     SCREAMING_SNAKE_CASE__      =     PRETRAINED_INIT_CONFIGURATION
     SCREAMING_SNAKE_CASE__      =     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     SCREAMING_SNAKE_CASE__      =     MPNetTokenizer
     SCREAMING_SNAKE_CASE__      =     ['''input_ids''', '''attention_mask''']





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

      _lowercase				 =json.loads(self.backend_tokenizer.normalizer.__getstate__()			)
      if (
          pre_tok_state.get('''lowercase'''						,	UpperCAmelCase			) != do_lower_case
          or pre_tok_state.get('''strip_accents'''						,	UpperCAmelCase			) != strip_accents
      ):
       _lowercase				 =getattr(UpperCAmelCase						,	pre_tok_state.pop('''type'''			)			)
       _lowercase				 =do_lower_case
       _lowercase				 =strip_accents
       _lowercase				 =pre_tok_class(**UpperCAmelCase			)

      _lowercase				 =do_lower_case





     @property
     def 	__A   (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 	__A   (self						,	UpperCAmelCase			)	->  Optional[int]:
      _lowercase				 =AddedToken(UpperCAmelCase						,	lstrip=UpperCAmelCase						,	rstrip=UpperCAmelCase			) if isinstance(UpperCAmelCase						,	UpperCAmelCase			) else value
      _lowercase				 =value





     def 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase=None			)	->  List[str]:
      _lowercase				 =[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 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase = None			)	->  List[int]:
      _lowercase				 =[self.sep_token_id]
      _lowercase				 =[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 	__A   (self						,	UpperCAmelCase						,	UpperCAmelCase = None			)	->  Tuple[str]:
      _lowercase				 =self._tokenizer.model.save(UpperCAmelCase						,	name=UpperCAmelCase			)
      return tuple(UpperCAmelCase			)

