

'''simple docstring'''

from typing import Dict, List, Optional, Tuple

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging


lowercase__            =     logging.get_logger(__name__)




class 			A_					(							_A				):






     '''simple docstring'''



     UpperCAmelCase_		:      List[Any]    						=    ["""input_ids""", """attention_mask"""]


     def __init__(						self					:	Tuple	,     lowercase_					:	Any="[PAD]"	,     lowercase_					:	List[str]="[BOS]"	,     lowercase_					:	str="[EOS]"	,     lowercase_					:	Optional[Any]="[MASK]"	,     lowercase_					:	Optional[int]="[CLS]"	,     lowercase_					:	List[str]="[SEP]"	,     lowercase_					:	Union[str, Any]=2_048	,     **lowercase_					:	Tuple	,     )		->      None:
      UpperCAmelCase			:      List[Any]		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else pad_token
      UpperCAmelCase			:      str		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else bos_token
      UpperCAmelCase			:      int		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else eos_token
      UpperCAmelCase			:      Any		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else mask_token
      UpperCAmelCase			:      List[str]		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else cls_token
      UpperCAmelCase			:      Union[str, Any]		   =					AddedToken(__A	,     lstrip=__A	,     rstrip=__A			) if isinstance(__A	,     __A			) else sep_token

      super().__init__(
          pad_token=__A	,     bos_token=__A	,     eos_token=__A	,     mask_token=__A	,     cls_token=__A	,     sep_token=__A	,     model_max_length=__A	,     **__A	,     )

      UpperCAmelCase			:      Union[str, Any]		   =					2**8  # utf is 8 bits

      # define special tokens dict
      UpperCAmelCase			:      Tuple		   =					{
          self.pad_token: 0,
          self.bos_token: 1,
          self.eos_token: 2,
          self.mask_token: 3,
          self.cls_token: 4,
          self.sep_token: 5,
      }
      UpperCAmelCase			:      Tuple		   =					len(self.special_tokens_encoder			)
      UpperCAmelCase			:      List[str]		   =					{v: k for k, v in self.special_tokens_encoder.items()}


     def   UpperCAmelCase_			(						self					:	List[Any]			)		->      Dict[str, int]:
      UpperCAmelCase			:      Optional[int]		   =					self.special_tokens_encoder.copy()
      vocab.update(self.added_tokens_encoder			)
      for i in range(self._utf_vocab_size			):
       UpperCAmelCase			:      int		   =					chr(__A			)
       UpperCAmelCase			:      List[Any]		   =					i + len(self.special_tokens_encoder			)
      return vocab


     @property
     def   UpperCAmelCase_			(						self					:	str			)		->      Dict:
      return self._utf_vocab_size + self._num_special_tokens


     def   UpperCAmelCase_			(						self					:	Any	,     lowercase_					:	List[int]	,     lowercase_					:	Optional[List[int]] = None	,     lowercase_					:	bool = False			)		->      List[int]:





      if already_has_special_tokens:
       return super().get_special_tokens_mask(
           token_ids_a=__A	,     token_ids_a=__A	,     already_has_special_tokens=__A			)

      # normal case: some special tokens
      if token_ids_a is None:
       return [1] + [0] * len(__A			) + [1]
      return [1] + ([0] * len(__A			)) + [1] + ([0] * len(__A			)) + [1]


     def   UpperCAmelCase_			(						self					:	Optional[int]	,     lowercase_					:	List[int]	,     lowercase_					:	Optional[List[int]] = None			)		->      List[int]:





      if token_ids_a is None:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
      else:
       return [self.cls_token_id] + token_ids_a + [self.sep_token_id] + token_ids_a + [self.sep_token_id]


     def   UpperCAmelCase_			(						self					:	Dict	,     lowercase_					:	str			)		->      List[str]:
      UpperCAmelCase			:      Optional[Any]		   =					[chr(__A			) for i in text.encode('utf-8'			)]
      return tokens


     def   UpperCAmelCase_			(						self					:	Optional[Any]	,     lowercase_					:	str			)		->      int:





      if token in self.special_tokens_encoder:
       UpperCAmelCase			:      Tuple		   =					self.special_tokens_encoder[token]
      elif token in self.added_tokens_encoder:
       UpperCAmelCase			:      Optional[Any]		   =					self.added_tokens_encoder[token]
      elif len(__A			) != 1:
       UpperCAmelCase			:      Optional[int]		   =					self.unk_token_id
      else:
       UpperCAmelCase			:      Dict		   =					ord(__A			) + self._num_special_tokens
      return token_id


     def   UpperCAmelCase_			(						self					:	Dict	,     lowercase_					:	Tuple			)		->      Union[str, Any]:





      if index in self.special_tokens_decoder:
       UpperCAmelCase			:      Optional[int]		   =					self.special_tokens_decoder[index]
      elif index in self.added_tokens_decoder:
       UpperCAmelCase			:      List[str]		   =					self.added_tokens_decoder[index]
      else:
       UpperCAmelCase			:      List[str]		   =					chr(index - self._num_special_tokens			)
      return token


     def   UpperCAmelCase_			(						self					:	List[str]	,     lowercase_					:	Union[str, Any]			)		->      Optional[int]:
      UpperCAmelCase			:      List[Any]		   =					B''
      for token in tokens:
       if token in self.special_tokens_decoder:
        UpperCAmelCase			:      Optional[Any]		   =					self.special_tokens_decoder[token].encode('utf-8'			)
       elif token in self.added_tokens_decoder:
        UpperCAmelCase			:      Dict		   =					self.special_tokens_decoder[token].encode('utf-8'			)
       elif token in self.special_tokens_encoder:
        UpperCAmelCase			:      List[Any]		   =					token.encode('utf-8'			)
       elif token in self.added_tokens_encoder:
        UpperCAmelCase			:      Any		   =					token.encode('utf-8'			)
       else:
        UpperCAmelCase			:      Any		   =					bytes([ord(__A			)]			)
       bstring += tok_string
      UpperCAmelCase			:      List[Any]		   =					bstring.decode('utf-8'	,     errors='replace'			)
      return string




     def   UpperCAmelCase_			(						self					:	Tuple	,     lowercase_					:	str	,     lowercase_					:	Optional[str] = None			)		->      Tuple[str]:
      return ()









'''simple docstring'''







from functools import partial
from typing import Any, Callable, Dict, List, Type, TypeVar, Union, overload

import torch
import torch.nn as nn
import torch.types
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	bool						) ->							torch.Tensor:
							# The first operation in a checkpoint can't be in-place, but it's
							# nice to have in-place addition during inference. Thus...
							if not inplace:
														lowerCAmelCase__  =   ma + ma
							else:
														ma += ma

							return ma
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	List[int]						) ->							torch.Tensor:
							lowerCAmelCase__  =   -1 * len(UpperCAmelCase_						)
							lowerCAmelCase__  =   list(range(len(tensor.shape[:zero_index]						)						)						)
							return tensor.permute(first_inds + [zero_index + i for i in inds]						)
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	int						) ->							torch.Tensor:
							return t.reshape(t.shape[:-no_dims] + (-1,)						)
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	int					, UpperCAmelCase_      :	float = 1E-4						) ->							torch.Tensor:
							lowerCAmelCase__  =   mask.expand(*value.shape						)
							return torch.sum(mask * value					, dim=UpperCAmelCase_						) / (eps + torch.sum(UpperCAmelCase_					, dim=UpperCAmelCase_						))
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	torch.types.Number = 2.31_25					, UpperCAmelCase_      :	torch.types.Number = 21.68_75					, UpperCAmelCase_      :	int = 64						) ->							torch.Tensor:
							lowerCAmelCase__  =   torch.linspace(UpperCAmelCase_					, UpperCAmelCase_					, no_bins - 1					, device=pts.device						)
							lowerCAmelCase__  =   torch.sqrt(torch.sum((pts.unsqueeze(-2						) - pts.unsqueeze(-3						)) ** 2					, dim=-1						)						)
							return torch.bucketize(UpperCAmelCase_					, UpperCAmelCase_						)
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[list], Any]					, UpperCAmelCase_      :	List[dict]						) ->							dict:
							lowerCAmelCase__  =   dicts[0]
							lowerCAmelCase__  =   {}
							for k, v in first.items():
														lowerCAmelCase__  =   [d[k] for d in dicts]
														if isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
																					lowerCAmelCase__  =   dict_multimap(UpperCAmelCase_					, UpperCAmelCase_						)
														else:
																					lowerCAmelCase__  =   fn(UpperCAmelCase_						)

							return new_dict
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	torch.Tensor						) ->							torch.Tensor:
							lowerCAmelCase__  =   v_bins.view(((1,) * len(x.shape						)) + (len(UpperCAmelCase_						),)						)
							lowerCAmelCase__  =   x[..., None] - reshaped_bins
							lowerCAmelCase__  =   torch.argmin(torch.abs(UpperCAmelCase_						)					, dim=-1						)
							return nn.functional.one_hot(UpperCAmelCase_					, num_classes=len(UpperCAmelCase_						)						).float()
def 			_lowerCAmelCase(      UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	torch.Tensor					, UpperCAmelCase_      :	int = 0					, UpperCAmelCase_      :	int = 0						) ->							torch.Tensor:
							lowerCAmelCase__  =   []
							for i, s in enumerate(data.shape[:no_batch_dims]						):
														lowerCAmelCase__  =   torch.arange(UpperCAmelCase_						)
														lowerCAmelCase__  =   r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape						) - i - 1)))						)
														ranges.append(UpperCAmelCase_						)

							lowerCAmelCase__  =   [slice(UpperCAmelCase_						) for _ in range(len(data.shape						) - no_batch_dims						)]
							lowerCAmelCase__  =   inds
							ranges.extend(UpperCAmelCase_						)
							# Matt note: Editing this to get around the behaviour of using a list as an array index changing
							# in recent Numpy versions
							return data[tuple(UpperCAmelCase_						)]


_UpperCamelCase  						=			TypeVar("""T""")
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[T], Any]					, UpperCAmelCase_      :	Dict[Any, Union[dict, list, tuple, T]]					, UpperCAmelCase_      :	Type[T]						) ->							Dict[Any, Union[dict, list, tuple, Any]]:
							lowerCAmelCase__  =   {}
							for k, v in dic.items():
														if isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
																					lowerCAmelCase__  =   dict_map(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_						)
														else:
																					lowerCAmelCase__  =   tree_map(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_						)

							return new_dict
@overload
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[T], Any]					, UpperCAmelCase_      :	T					, UpperCAmelCase_      :	Type[T]						) ->							Any:
							...
@overload
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[T], Any]					, UpperCAmelCase_      :	dict					, UpperCAmelCase_      :	Type[T]						) ->							dict:
							...
@overload
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[T], Any]					, UpperCAmelCase_      :	list					, UpperCAmelCase_      :	Type[T]						) ->							list:
							...
@overload
def 			_lowerCAmelCase(      UpperCAmelCase_      :	Callable[[T], Any]					, UpperCAmelCase_      :	tuple					, UpperCAmelCase_      :	Type[T]						) ->							tuple:
							...
def 			_lowerCAmelCase(      UpperCAmelCase_      :	str					, UpperCAmelCase_      :	Dict					, UpperCAmelCase_      :	Union[str, Any]						) ->							List[str]:
							if isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
														return dict_map(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_						)
							elif isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
														return [tree_map(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_						) for x in tree]
							elif isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
														return tuple(tree_map(UpperCAmelCase_					, UpperCAmelCase_					, UpperCAmelCase_						) for x in tree						)
							elif isinstance(UpperCAmelCase_					, UpperCAmelCase_						):
														return fn(UpperCAmelCase_						)
							else:
														print(type(UpperCAmelCase_						)						)
														raise ValueError("""Not supported"""						)






_UpperCamelCase  						=			partial(tree_map, leaf_type=torch.Tensor)





