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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


__lowerCAmelCase					:			int			      =		logging.get_logger(__name__)

__lowerCAmelCase					:			Optional[Any]			      =		{"vocab_file": "spiece.model"}

__lowerCAmelCase					:			Tuple			      =		{
    "vocab_file": {
        "bert_for_seq_generation": (
            "https://huggingface.co/google/bert_for_seq_generation_L-24_bbc_encoder/resolve/main/spiece.model"
        ),
    }
}

__lowerCAmelCase					:			List[str]			      =		{"bert_for_seq_generation": 512}


class 						__lowerCAmelCase	(	lowerCAmelCase_      ):



      """simple docstring"""







      A__	:			str        =    VOCAB_FILES_NAMES
      A__	:			List[str]        =    PRETRAINED_VOCAB_FILES_MAP
      A__	:			Optional[Any]        =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      A__	:			List[int]        =    []
      A__	:			Union[str, Any]        =    ['''input_ids''', '''attention_mask''']




      def __init__(      self		:       Optional[Any]				,       _snake_case		:       Dict				,       _snake_case		:       Dict="<s>"				,       _snake_case		:       List[Any]="</s>"				,       _snake_case		:       Any="<unk>"				,       _snake_case		:       int="<pad>"				,       _snake_case		:       List[Any]="<::::>"				,       _snake_case		:       Optional[Dict[str, Any]] = None				,       **_snake_case		:       List[Any]				,       ):
          __lowercase		:			Dict	    =       {} if sp_model_kwargs is None else sp_model_kwargs

          # Add extra_ids to the special token list
          super().__init__(
              bos_token=_snake_case				,       eos_token=_snake_case				,       unk_token=_snake_case				,       pad_token=_snake_case				,       sep_token=_snake_case				,       sp_model_kwargs=self.sp_model_kwargs				,       **_snake_case				,       )

          __lowercase		:			Tuple	    =       vocab_file

          __lowercase		:			int	    =       spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(_snake_case				)




      @property
      def 		snake_case_			(      self		:       Tuple				):
          return self.sp_model.get_piece_size()




      def 		snake_case_			(      self		:       List[str]				):
          __lowercase		:			Tuple	    =       {self.convert_ids_to_tokens(_snake_case				): i for i in range(self.vocab_size				)}
          vocab.update(self.added_tokens_encoder				)
          return vocab




      def __getstate__(      self		:       Union[str, Any]				):
          __lowercase		:			Dict	    =       self.__dict__.copy()
          __lowercase		:			Dict	    =       None
          return state




      def __setstate__(      self		:       Dict				,       _snake_case		:       Dict				):
          __lowercase		:			Optional[int]	    =       d

          # for backward compatibility
          if not hasattr(self				,       '''sp_model_kwargs'''				):
              __lowercase		:			Dict	    =       {}

          __lowercase		:			Tuple	    =       spm.SentencePieceProcessor(**self.sp_model_kwargs				)
          self.sp_model.Load(self.vocab_file				)




      def 		snake_case_			(      self		:       Any				,       _snake_case		:       str				):
          return self.sp_model.encode(_snake_case				,       out_type=_snake_case				)




      def 		snake_case_			(      self		:       str				,       _snake_case		:       Optional[Any]				):
          return self.sp_model.piece_to_id(_snake_case				)




      def 		snake_case_			(      self		:       List[str]				,       _snake_case		:       Tuple				):
          __lowercase		:			Dict	    =       self.sp_model.IdToPiece(_snake_case				)
          return token




      def 		snake_case_			(      self		:       Any				,       _snake_case		:       List[str]				):
          __lowercase		:			List[Any]	    =       []
          __lowercase		:			List[Any]	    =       ''''''
          for token in tokens:
              # make sure that special tokens are not decoded using sentencepiece model
              if token in self.all_special_tokens:
                  out_string += self.sp_model.decode(_snake_case				) + token
                  __lowercase		:			Tuple	    =       []
              else:
                  current_sub_tokens.append(_snake_case				)
          out_string += self.sp_model.decode(_snake_case				)
          return out_string.strip()




      def 		snake_case_			(      self		:       Optional[Any]				,       _snake_case		:       str				,       _snake_case		:       Optional[str] = None				):
          if not os.path.isdir(_snake_case				):
              logger.error(F'Vocabulary path ({save_directory}) should be a directory'				)
              return
          __lowercase		:			List[str]	    =       os.path.join(
              _snake_case				,       (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

          if os.path.abspath(self.vocab_file				) != os.path.abspath(_snake_case				) and os.path.isfile(self.vocab_file				):
              copyfile(self.vocab_file				,       _snake_case				)
          elif not os.path.isfile(self.vocab_file				):
              with open(_snake_case				,       '''wb'''				) as fi:
                  __lowercase		:			Union[str, Any]	    =       self.sp_model.serialized_model_proto()
                  fi.write(_snake_case				)

          return (out_vocab_file,)




import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_torch


if is_torch_available():
 import torch

 from transformers.activations import gelu_new, gelu_python, get_activation


@require_torch
class 						__lowerCAmelCase	(	unittest.TestCase      ):



      """simple docstring"""







      def 		snake_case_			(      self		:       Optional[Any]				):
          __lowercase		:			Union[str, Any]	    =       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
          __lowercase		:			Any	    =       get_activation('''gelu'''				)
          self.assertTrue(torch.allclose(gelu_python(_snake_case				)				,       torch_builtin(_snake_case				)				)				)
          self.assertFalse(torch.allclose(gelu_python(_snake_case				)				,       gelu_new(_snake_case				)				)				)




      def 		snake_case_			(      self		:       Dict				):
          __lowercase		:			Any	    =       torch.tensor([-100, -1, -0.1, 0, 0.1, 1.0, 100]				)
          __lowercase		:			List[str]	    =       get_activation('''gelu'''				)
          __lowercase		:			Optional[Any]	    =       get_activation('''gelu_10'''				)

          __lowercase		:			Tuple	    =       torch_builtin(_snake_case				)
          __lowercase		:			List[Any]	    =       geluaa(_snake_case				)

          __lowercase		:			Tuple	    =       torch.where(y_gelu_aa < 10.0				,       1				,       0				)

          self.assertTrue(torch.max(_snake_case				).item() == 10.0				)
          self.assertTrue(torch.allclose(y_gelu * clipped_mask				,       y_gelu_aa * clipped_mask				)				)




      def 		snake_case_			(      self		:       Any				):
          get_activation('''gelu'''				)
          get_activation('''gelu_10'''				)
          get_activation('''gelu_fast'''				)
          get_activation('''gelu_new'''				)
          get_activation('''gelu_python'''				)
          get_activation('''gelu_pytorch_tanh'''				)
          get_activation('''linear'''				)
          get_activation('''mish'''				)
          get_activation('''quick_gelu'''				)
          get_activation('''relu'''				)
          get_activation('''sigmoid'''				)
          get_activation('''silu'''				)
          get_activation('''swish'''				)
          get_activation('''tanh'''				)
          with self.assertRaises(_snake_case				):
              get_activation('''bogus'''				)
          with self.assertRaises(_snake_case				):
              get_activation(_snake_case				)




      def 		snake_case_			(      self		:       Dict				):
          __lowercase		:			Union[str, Any]	    =       get_activation('''gelu'''				)
          __lowercase		:			List[str]	    =       1
          __lowercase		:			Union[str, Any]	    =       get_activation('''gelu'''				)
          self.assertEqual(acta.a				,       1				)
          with self.assertRaises(_snake_case				):
              __lowercase		:			Tuple	    =       acta.a


