




from typing import Dict, List, Optional, Tuple

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


_a				     =  logging.get_logger(__name__)





class __lowerCamelCase			(				snake_case__):





	"""simple docstring"""






	UpperCamelCase__								=				["input_ids", "attention_mask"]

	def __init__(							self	,   UpperCAmelCase="[PAD]"	,   UpperCAmelCase="[BOS]"	,   UpperCAmelCase="[EOS]"	,   UpperCAmelCase="[MASK]"	,   UpperCAmelCase="[CLS]"	,   UpperCAmelCase="[SEP]"	,   UpperCAmelCase=2048	,   **UpperCAmelCase	,   ):
							"""simple docstring"""







							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else pad_token
							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else bos_token
							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else eos_token
							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else mask_token
							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else cls_token
							_UpperCAmelCase     =      AddedToken(UpperCAmelCase	,   lstrip=UpperCAmelCase	,   rstrip=UpperCAmelCase   ) if isinstance(UpperCAmelCase	,   UpperCAmelCase   ) else sep_token

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

							_UpperCAmelCase     =      2**8  # utf is 8 bits

							# define special tokens dict
							_UpperCAmelCase     =      {
							    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     =      len(self.special_tokens_encoder   )
							_UpperCAmelCase     =      {v: k for k, v in self.special_tokens_encoder.items()}

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







							_UpperCAmelCase     =      self.special_tokens_encoder.copy()
							vocab.update(self.added_tokens_encoder   )
							for i in range(self._utf_vocab_size   ):
													_UpperCAmelCase     =      chr(UpperCAmelCase   )
													_UpperCAmelCase     =      i + len(self.special_tokens_encoder   )
							return vocab

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







							return self._utf_vocab_size + self._num_special_tokens

	def 	UpperCamelCase   (							self	,   UpperCAmelCase	,   UpperCAmelCase = None	,   UpperCAmelCase = False   ):
							"""simple docstring"""







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

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

	def 	UpperCamelCase   (							self	,   UpperCAmelCase	,   UpperCAmelCase = None   ):
							"""simple docstring"""







							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	,   UpperCAmelCase   ):
							"""simple docstring"""







							_UpperCAmelCase     =      [chr(UpperCAmelCase   ) for i in text.encode('utf-8'   )]
							return tokens

	def 	UpperCamelCase   (							self	,   UpperCAmelCase   ):
							"""simple docstring"""







							if token in self.special_tokens_encoder:
													_UpperCAmelCase     =      self.special_tokens_encoder[token]
							elif token in self.added_tokens_encoder:
													_UpperCAmelCase     =      self.added_tokens_encoder[token]
							elif len(UpperCAmelCase   ) != 1:
													_UpperCAmelCase     =      self.unk_token_id
							else:
													_UpperCAmelCase     =      ord(UpperCAmelCase   ) + self._num_special_tokens
							return token_id

	def 	UpperCamelCase   (							self	,   UpperCAmelCase   ):
							"""simple docstring"""







							if index in self.special_tokens_decoder:
													_UpperCAmelCase     =      self.special_tokens_decoder[index]
							elif index in self.added_tokens_decoder:
													_UpperCAmelCase     =      self.added_tokens_decoder[index]
							else:
													_UpperCAmelCase     =      chr(index - self._num_special_tokens   )
							return token

	def 	UpperCamelCase   (							self	,   UpperCAmelCase   ):
							"""simple docstring"""







							_UpperCAmelCase     =      b''
							for token in tokens:
													if token in self.special_tokens_decoder:
																			_UpperCAmelCase     =      self.special_tokens_decoder[token].encode('utf-8'   )
													elif token in self.added_tokens_decoder:
																			_UpperCAmelCase     =      self.special_tokens_decoder[token].encode('utf-8'   )
													elif token in self.special_tokens_encoder:
																			_UpperCAmelCase     =      token.encode('utf-8'   )
													elif token in self.added_tokens_encoder:
																			_UpperCAmelCase     =      token.encode('utf-8'   )
													else:
																			_UpperCAmelCase     =      bytes([ord(UpperCAmelCase   )]   )
													bstring += tok_string
							_UpperCAmelCase     =      bstring.decode('utf-8'	,   errors='replace'   )
							return string

	def 	UpperCamelCase   (							self	,   UpperCAmelCase	,   UpperCAmelCase = None   ):
							"""simple docstring"""







							return ()








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 __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  torch.Tensor:





						"""simple docstring"""



						if not inplace:
												_UpperCAmelCase     =      ma + ma
						else:
												ma += ma

						return ma


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  torch.Tensor:





						"""simple docstring"""



						_UpperCAmelCase     =      -1 * len(__lowerCAmelCase     )
						_UpperCAmelCase     =      list(range(len(tensor.shape[:zero_index]     )     )     )
						return tensor.permute(first_inds + [zero_index + i for i in inds]     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  torch.Tensor:





						"""simple docstring"""



						return t.reshape(t.shape[:-no_dims] + (-1,)     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase = 1E-4     )->  torch.Tensor:





						"""simple docstring"""



						_UpperCAmelCase     =      mask.expand(*value.shape     )
						return torch.sum(mask * value			,		dim=__lowerCAmelCase     ) / (eps + torch.sum(__lowerCAmelCase			,		dim=__lowerCAmelCase     ))


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase = 2.31_25			,		__lowerCAmelCase = 21.68_75			,		__lowerCAmelCase = 64     )->  torch.Tensor:





						"""simple docstring"""



						_UpperCAmelCase     =      torch.linspace(__lowerCAmelCase			,		__lowerCAmelCase			,		no_bins - 1			,		device=pts.device     )
						_UpperCAmelCase     =      torch.sqrt(torch.sum((pts.unsqueeze(-2     ) - pts.unsqueeze(-3     )) ** 2			,		dim=-1     )     )
						return torch.bucketize(__lowerCAmelCase			,		__lowerCAmelCase     )


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  dict:





						"""simple docstring"""



						_UpperCAmelCase     =      dicts[0]
						_UpperCAmelCase     =      {}
						for k, v in first.items():
												_UpperCAmelCase     =      [d[k] for d in dicts]
												if isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
																		_UpperCAmelCase     =      dict_multimap(__lowerCAmelCase			,		__lowerCAmelCase     )
												else:
																		_UpperCAmelCase     =      fn(__lowerCAmelCase     )

						return new_dict


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase     )->  torch.Tensor:





						"""simple docstring"""



						_UpperCAmelCase     =      v_bins.view(((1,) * len(x.shape     )) + (len(__lowerCAmelCase     ),)     )
						_UpperCAmelCase     =      x[..., None] - reshaped_bins
						_UpperCAmelCase     =      torch.argmin(torch.abs(__lowerCAmelCase     )			,		dim=-1     )
						return nn.functional.one_hot(__lowerCAmelCase			,		num_classes=len(__lowerCAmelCase     )     ).float()


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase = 0			,		__lowerCAmelCase = 0     )->  torch.Tensor:





						"""simple docstring"""



						_UpperCAmelCase     =      []
						for i, s in enumerate(data.shape[:no_batch_dims]     ):
												_UpperCAmelCase     =      torch.arange(__lowerCAmelCase     )
												_UpperCAmelCase     =      r.view(*(*((1,) * i), -1, *((1,) * (len(inds.shape     ) - i - 1)))     )
												ranges.append(__lowerCAmelCase     )

						_UpperCAmelCase     =      [slice(__lowerCAmelCase     ) for _ in range(len(data.shape     ) - no_batch_dims     )]
						_UpperCAmelCase     =      inds
						ranges.extend(__lowerCAmelCase     )
						# 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(__lowerCAmelCase     )]


_a				     =  TypeVar('''T''')


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  Dict[Any, Union[dict, list, tuple, Any]]:





						"""simple docstring"""



						_UpperCAmelCase     =      {}
						for k, v in dic.items():
												if isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
																		_UpperCAmelCase     =      dict_map(__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )
												else:
																		_UpperCAmelCase     =      tree_map(__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )

						return new_dict


@overload
def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  Any:





						"""simple docstring"""



						...


@overload
def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  dict:





						"""simple docstring"""



						...


@overload
def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  list:





						"""simple docstring"""



						...


@overload
def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  tuple:





						"""simple docstring"""



						...


def __A   (				__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )->  List[Any]:





						"""simple docstring"""



						if isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
												return dict_map(__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     )
						elif isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
												return [tree_map(__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     ) for x in tree]
						elif isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
												return tuple(tree_map(__lowerCAmelCase			,		__lowerCAmelCase			,		__lowerCAmelCase     ) for x in tree     )
						elif isinstance(__lowerCAmelCase			,		__lowerCAmelCase     ):
												return fn(__lowerCAmelCase     )
						else:
												print(type(__lowerCAmelCase     )     )
												raise ValueError('Not supported'     )

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