



import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


__lowerCamelCase     :							List[Any]  							=				logging.get_logger(__name__)

__lowerCamelCase     :							List[str]  							=				{"vocab_file": "spiece.model"}

__lowerCamelCase     :							List[str]  							=				{
    "vocab_file": {
        "google/bigbird-roberta-base": "https://huggingface.co/google/bigbird-roberta-base/resolve/main/spiece.model",
        "google/bigbird-roberta-large": (
            "https://huggingface.co/google/bigbird-roberta-large/resolve/main/spiece.model"
        ),
        "google/bigbird-base-trivia-itc": (
            "https://huggingface.co/google/bigbird-base-trivia-itc/resolve/main/spiece.model"
        ),
    }
}

__lowerCamelCase     :							Union[str, Any]  							=				{
    "google/bigbird-roberta-base": 4_096,
    "google/bigbird-roberta-large": 4_096,
    "google/bigbird-base-trivia-itc": 4_096,
}





class  __magic_name__   (							A__						):
		lowercase      :       str          =VOCAB_FILES_NAMES
		lowercase      :       Optional[int]          =PRETRAINED_VOCAB_FILES_MAP
		lowercase      :       Tuple          =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowercase      :       Any          =['''input_ids''', '''attention_mask''']
		lowercase      :       List[int]          =[]






		def __init__(						self      :     Any				,		UpperCamelCase__      :     List[Any]				,		UpperCamelCase__      :     Optional[int]="<unk>"				,		UpperCamelCase__      :     List[str]="<s>"				,		UpperCamelCase__      :     int="</s>"				,		UpperCamelCase__      :     Tuple="<pad>"				,		UpperCamelCase__      :     Dict="[SEP]"				,		UpperCamelCase__      :     Optional[Any]="[MASK]"				,		UpperCamelCase__      :     str="[CLS]"				,		UpperCamelCase__      :     Optional[Dict[str, Any]] = None				,		**UpperCamelCase__      :     Any				,		)				->					None:
								'''simple docstring'''







								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 unk_token
								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 cls_token
								UpperCAmelCase         =    AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else sep_token

								# Mask token behave like a normal word, i.e. include the space before it
								UpperCAmelCase         =    AddedToken(UpperCamelCase__				,		lstrip=UpperCamelCase__				,		rstrip=UpperCamelCase__      ) if isinstance(UpperCamelCase__				,		UpperCamelCase__      ) else mask_token

								UpperCAmelCase         =    {} if sp_model_kwargs is None else sp_model_kwargs

								super().__init__(
								    bos_token=UpperCamelCase__				,		eos_token=UpperCamelCase__				,		unk_token=UpperCamelCase__				,		pad_token=UpperCamelCase__				,		sep_token=UpperCamelCase__				,		mask_token=UpperCamelCase__				,		cls_token=UpperCamelCase__				,		sp_model_kwargs=self.sp_model_kwargs				,		**UpperCamelCase__				,		)

								UpperCAmelCase         =    vocab_file

								UpperCAmelCase         =    spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.Load(UpperCamelCase__      )






		@property
		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]      )				->					Optional[Any]:
								'''simple docstring'''







								return self.sp_model.get_piece_size()






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[int]      )				->					int:
								'''simple docstring'''







								UpperCAmelCase         =    {self.convert_ids_to_tokens(UpperCamelCase__      ): i for i in range(self.vocab_size      )}
								vocab.update(self.added_tokens_encoder      )
								return vocab






		def __getstate__(						self      :     Union[str, Any]      )				->					Union[str, Any]:
								'''simple docstring'''







								UpperCAmelCase         =    self.__dict__.copy()
								UpperCAmelCase         =    None
								return state






		def __setstate__(						self      :     Any				,		UpperCamelCase__      :     Union[str, Any]      )				->					Optional[Any]:
								'''simple docstring'''







								UpperCAmelCase         =    d

								# for backward compatibility
								if not hasattr(self				,		"sp_model_kwargs"      ):
														UpperCAmelCase         =    {}

								UpperCAmelCase         =    spm.SentencePieceProcessor(**self.sp_model_kwargs      )
								self.sp_model.Load(self.vocab_file      )






		def SCREAMING_SNAKE_CASE_			(						self      :     int				,		UpperCamelCase__      :     str      )				->					List[str]:
								'''simple docstring'''







								return self.sp_model.encode(UpperCamelCase__				,		out_type=UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]				,		UpperCamelCase__      :     str      )				->					Union[str, Any]:
								'''simple docstring'''







								return self.sp_model.piece_to_id(UpperCamelCase__      )






		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]				,		UpperCamelCase__      :     Optional[Any]      )				->					Dict:
								'''simple docstring'''







								UpperCAmelCase         =    self.sp_model.IdToPiece(UpperCamelCase__      )
								return token






		def SCREAMING_SNAKE_CASE_			(						self      :     int				,		UpperCamelCase__      :     List[str]      )				->					List[Any]:
								'''simple docstring'''







								UpperCAmelCase         =    []
								UpperCAmelCase         =    ""
								UpperCAmelCase         =    False
								for token in tokens:
														# make sure that special tokens are not decoded using sentencepiece model
														if token in self.all_special_tokens:
																				if not prev_is_special:
																										out_string += " "
																				out_string += self.sp_model.decode(UpperCamelCase__      ) + token
																				UpperCAmelCase         =    True
																				UpperCAmelCase         =    []
														else:
																				current_sub_tokens.append(UpperCamelCase__      )
																				UpperCAmelCase         =    False
								out_string += self.sp_model.decode(UpperCamelCase__      )
								return out_string.strip()






		def SCREAMING_SNAKE_CASE_			(						self      :     str				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     bool = False				,		UpperCamelCase__      :     bool = None				,		UpperCamelCase__      :     bool = True				,		**UpperCamelCase__      :     str				,		)				->					str:
								'''simple docstring'''







								UpperCAmelCase         =    kwargs.pop("use_source_tokenizer"				,		UpperCamelCase__      )

								UpperCAmelCase         =    self.convert_ids_to_tokens(UpperCamelCase__				,		skip_special_tokens=UpperCamelCase__      )

								# To avoid mixing byte-level and unicode for byte-level BPT
								# we need to build string separately for added tokens and byte-level tokens
								# cf. https://github.com/huggingface/transformers/issues/1133
								UpperCAmelCase         =    []
								UpperCAmelCase         =    []
								for token in filtered_tokens:
														if skip_special_tokens and token in self.all_special_ids:
																				continue
														if token in self.added_tokens_encoder:
																				if current_sub_text:
																										sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__      )      )
																										UpperCAmelCase         =    []
																				sub_texts.append(UpperCamelCase__      )
														else:
																				current_sub_text.append(UpperCamelCase__      )
								if current_sub_text:
														sub_texts.append(self.convert_tokens_to_string(UpperCamelCase__      )      )

								# Mimic the behavior of the Rust tokenizer:
								# No space before [MASK] and [SEP]
								if spaces_between_special_tokens:
														UpperCAmelCase         =    re.sub(R" (\[(MASK|SEP)\])"				,		R"\1"				,		" ".join(UpperCamelCase__      )      )
								else:
														UpperCAmelCase         =    "".join(UpperCamelCase__      )

								UpperCAmelCase         =    (
								    clean_up_tokenization_spaces
								    if clean_up_tokenization_spaces is not None
								    else self.clean_up_tokenization_spaces
								)
								if clean_up_tokenization_spaces:
														UpperCAmelCase         =    self.clean_up_tokenization(UpperCamelCase__      )
														return clean_text
								else:
														return text






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple				,		UpperCamelCase__      :     str				,		UpperCamelCase__      :     Optional[str] = None      )				->					Tuple[str]:
								'''simple docstring'''







								if not os.path.isdir(UpperCamelCase__      ):
														logger.error(F'Vocabulary path ({save_directory}) should be a directory'      )
														return
								UpperCAmelCase         =    os.path.join(
								    UpperCamelCase__				,		(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]      )

								if os.path.abspath(self.vocab_file      ) != os.path.abspath(UpperCamelCase__      ) and os.path.isfile(self.vocab_file      ):
														copyfile(self.vocab_file				,		UpperCamelCase__      )
								elif not os.path.isfile(self.vocab_file      ):
														with open(UpperCamelCase__				,		"wb"      ) as fi:
																				UpperCAmelCase         =    self.sp_model.serialized_model_proto()
																				fi.write(UpperCamelCase__      )

								return (out_vocab_file,)






		def SCREAMING_SNAKE_CASE_			(						self      :     Any				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None      )				->					List[int]:
								'''simple docstring'''







								if token_ids_a is None:
														return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
								UpperCAmelCase         =    [self.cls_token_id]
								UpperCAmelCase         =    [self.sep_token_id]
								return cls + token_ids_a + sep + token_ids_a + sep






		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None				,		UpperCamelCase__      :     bool = False      )				->					List[int]:
								'''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__      )

								if token_ids_a is None:
														return [1] + ([0] * len(UpperCamelCase__      )) + [1]
								return [1] + ([0] * len(UpperCamelCase__      )) + [1] + ([0] * len(UpperCamelCase__      )) + [1]







		def SCREAMING_SNAKE_CASE_			(						self      :     List[Any]				,		UpperCamelCase__      :     List[int]				,		UpperCamelCase__      :     Optional[List[int]] = None      )				->					List[int]:
								'''simple docstring'''







								UpperCAmelCase         =    [self.sep_token_id]
								UpperCAmelCase         =    [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      ) * [0] + len(token_ids_a + sep      ) * [1]








import unittest

import torch
from torch import nn

from diffusers.models.activations import get_activation





class  __magic_name__   (							unittest.TestCase						):






		def SCREAMING_SNAKE_CASE_			(						self      :     int      )				->					str:
								'''simple docstring'''







								UpperCAmelCase         =     get_activation("swish"      )

								self.assertIsInstance(UpperCamelCase__				,		nn.SiLU      )

								self.assertEqual(act(torch.tensor(-1_00				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertNotEqual(act(torch.tensor(-1				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(0				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(20				,		dtype=torch.floataa      )      ).item()				,		20      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					List[Any]:
								'''simple docstring'''







								UpperCAmelCase         =     get_activation("silu"      )

								self.assertIsInstance(UpperCamelCase__				,		nn.SiLU      )

								self.assertEqual(act(torch.tensor(-1_00				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertNotEqual(act(torch.tensor(-1				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(0				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(20				,		dtype=torch.floataa      )      ).item()				,		20      )






		def SCREAMING_SNAKE_CASE_			(						self      :     Optional[Any]      )				->					int:
								'''simple docstring'''







								UpperCAmelCase         =     get_activation("mish"      )

								self.assertIsInstance(UpperCamelCase__				,		nn.Mish      )

								self.assertEqual(act(torch.tensor(-2_00				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertNotEqual(act(torch.tensor(-1				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(0				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(20				,		dtype=torch.floataa      )      ).item()				,		20      )







		def SCREAMING_SNAKE_CASE_			(						self      :     str      )				->					List[str]:
								'''simple docstring'''







								UpperCAmelCase         =     get_activation("gelu"      )

								self.assertIsInstance(UpperCamelCase__				,		nn.GELU      )

								self.assertEqual(act(torch.tensor(-1_00				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertNotEqual(act(torch.tensor(-1				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(0				,		dtype=torch.floataa      )      ).item()				,		0      )
								self.assertEqual(act(torch.tensor(20				,		dtype=torch.floataa      )      ).item()				,		20      )



