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

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


UpperCAmelCase					      =							logging.get_logger(__name__)

UpperCAmelCase					      =							{
    "vocab_file": "vocab.txt",
    "merges_file": "bpe.codes",
}

UpperCAmelCase					      =							{
    "vocab_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/vocab.txt",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/vocab.txt",
    },
    "merges_file": {
        "vinai/phobert-base": "https://huggingface.co/vinai/phobert-base/resolve/main/bpe.codes",
        "vinai/phobert-large": "https://huggingface.co/vinai/phobert-large/resolve/main/bpe.codes",
    },
}

UpperCAmelCase					      =							{
    "vinai/phobert-base": 2_5_6,
    "vinai/phobert-large": 2_5_6,
}






def        SCREAMING_SNAKE_CASE_      (		lowerCAmelCase_:			Optional[Any]  ):
      snake_case_  :      Tuple  	=							set()
      snake_case_  :      Tuple  	=							word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)  )
            snake_case_  :      Optional[int]  	=							char

      snake_case_  :      Optional[int]  	=							set(snake_case__  )
      return pairs





class        snake_case__							(					lowercase_				):
   _SCREAMING_SNAKE_CASE						:			Optional[int]         =   VOCAB_FILES_NAMES
   _SCREAMING_SNAKE_CASE						:			int         =   PRETRAINED_VOCAB_FILES_MAP
   _SCREAMING_SNAKE_CASE						:			Optional[Any]         =   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES



   def __init__(					self : str      ,						A__ : Tuple      ,						A__ : Optional[int]      ,						A__ : str="<s>"      ,						A__ : List[Any]="</s>"      ,						A__ : int="</s>"      ,						A__ : List[Any]="<s>"      ,						A__ : Optional[int]="<unk>"      ,						A__ : Dict="<pad>"      ,						A__ : int="<mask>"      ,						**A__ : Optional[Any]      ,						)				->  List[str]:




         '''simple docstring'''




         super().__init__(
             bos_token=a__      ,						eos_token=a__      ,						unk_token=a__      ,						sep_token=a__      ,						cls_token=a__      ,						pad_token=a__      ,						mask_token=a__      ,						**a__      ,						)

         snake_case_  :      str  	=							vocab_file
         snake_case_  :      Optional[Any]  	=							merges_file

         snake_case_  :      int  	=							{}
         snake_case_  :      Any  	=							0
         snake_case_  :      Tuple  	=							1
         snake_case_  :      Optional[int]  	=							2
         snake_case_  :      Any  	=							3

         self.add_from_file(a__ )

         snake_case_  :      str  	=							{v: k for k, v in self.encoder.items()}

         with open(a__      ,						encoding="utf-8" ) as merges_handle:
               snake_case_  :      Tuple  	=							merges_handle.read().split("\n" )[:-1]
         snake_case_  :      List[Any]  	=							[tuple(merge.split()[:-1] ) for merge in merges]
         snake_case_  :      List[str]  	=							dict(zip(a__      ,						range(len(a__ ) ) ) )
         snake_case_  :      Any  	=							{}



   def        UpperCAmelCase__							(					self : str      ,						A__ : Optional[Any]      ,						A__ : Dict = None )				->  List[int]:




         '''simple docstring'''




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



   def        UpperCAmelCase__							(					self : Optional[int]      ,						A__ : List[Any]      ,						A__ : Union[str, Any] = None      ,						A__ : List[str] = False )				->  List[int]:




         '''simple docstring'''




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

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



   def        UpperCAmelCase__							(					self : Dict      ,						A__ : List[str]      ,						A__ : Tuple = None )				->  List[int]:




         '''simple docstring'''




         snake_case_  :      Union[str, Any]  	=							[self.sep_token_id]
         snake_case_  :      str  	=							[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]



   @property
   def        UpperCAmelCase__							(					self : List[str] )				->  Union[str, Any]:




         '''simple docstring'''




         return len(self.encoder )



   def        UpperCAmelCase__							(					self : Union[str, Any] )				->  Optional[int]:




         '''simple docstring'''




         return dict(self.encoder      ,						**self.added_tokens_encoder )



   def        UpperCAmelCase__							(					self : List[str]      ,						A__ : int )				->  Optional[int]:




         '''simple docstring'''




         if token in self.cache:
               return self.cache[token]
         snake_case_  :      Tuple  	=							tuple(a__ )
         snake_case_  :      Optional[int]  	=							tuple(list(word[:-1] ) + [word[-1] + "</w>"] )
         snake_case_  :      List[str]  	=							get_pairs(a__ )

         if not pairs:
               return token

         while True:
               snake_case_  :      Optional[int]  	=							min(a__      ,						key=lambda A__ : self.bpe_ranks.get(a__      ,						float("inf" ) ) )
               if bigram not in self.bpe_ranks:
                     break
               snake_case_  :      Any  	=							bigram
               snake_case_  :      Tuple  	=							[]
               snake_case_  :      Optional[Any]  	=							0
               while i < len(a__ ):
                     try:
                           snake_case_  :      Tuple  	=							word.index(a__      ,						a__ )
                     except ValueError:
                           new_word.extend(word[i:] )
                           break
                     else:
                           new_word.extend(word[i:j] )
                           snake_case_  :      List[Any]  	=							j

                     if word[i] == first and i < len(a__ ) - 1 and word[i + 1] == second:
                           new_word.append(first + second )
                           i += 2
                     else:
                           new_word.append(word[i] )
                           i += 1
               snake_case_  :      int  	=							tuple(a__ )
               snake_case_  :      List[str]  	=							new_word
               if len(a__ ) == 1:
                     break
               else:
                     snake_case_  :      Union[str, Any]  	=							get_pairs(a__ )
         snake_case_  :      str  	=							"""@@ """.join(a__ )
         snake_case_  :      Optional[int]  	=							word[:-4]
         snake_case_  :      Dict  	=							word
         return word



   def        UpperCAmelCase__							(					self : Any      ,						A__ : Any )				->  Optional[int]:




         '''simple docstring'''




         snake_case_  :      int  	=							[]

         snake_case_  :      List[str]  	=							re.findall(r"\S+\n?"      ,						a__ )

         for token in words:
               split_tokens.extend(list(self.bpe(a__ ).split(" " ) ) )
         return split_tokens



   def        UpperCAmelCase__							(					self : Optional[int]      ,						A__ : Union[str, Any] )				->  Optional[Any]:




         '''simple docstring'''




         return self.encoder.get(a__      ,						self.encoder.get(self.unk_token ) )



   def        UpperCAmelCase__							(					self : Optional[int]      ,						A__ : List[str] )				->  Optional[int]:




         '''simple docstring'''




         return self.decoder.get(a__      ,						self.unk_token )



   def        UpperCAmelCase__							(					self : Any      ,						A__ : Tuple )				->  int:




         '''simple docstring'''




         snake_case_  :      List[Any]  	=							""" """.join(a__ ).replace("@@ "      ,						"" ).strip()
         return out_string



   def        UpperCAmelCase__							(					self : Tuple      ,						A__ : Optional[int]      ,						A__ : Any = None )				->  Tuple[str]:




         '''simple docstring'''




         if not os.path.isdir(a__ ):
               logger.error(f"Vocabulary path ({save_directory}) should be a directory" )
               return
         snake_case_  :      Union[str, Any]  	=							os.path.join(
             a__      ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"] )
         snake_case_  :      Optional[int]  	=							os.path.join(
             a__      ,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"] )

         if os.path.abspath(self.vocab_file ) != os.path.abspath(a__ ):
               copyfile(self.vocab_file      ,						a__ )

         if os.path.abspath(self.merges_file ) != os.path.abspath(a__ ):
               copyfile(self.merges_file      ,						a__ )

         return out_vocab_file, out_merge_file



   def        UpperCAmelCase__							(					self : Optional[Any]      ,						A__ : Tuple )				->  List[Any]:




         '''simple docstring'''




         if isinstance(a__      ,						a__ ):
               try:
                     with open(a__      ,						"r"      ,						encoding="utf-8" ) as fd:
                           self.add_from_file(a__ )
               except FileNotFoundError as fnfe:
                     raise fnfe
               except UnicodeError:
                     raise Exception(f"Incorrect encoding detected in {f}, please rebuild the dataset" )
               return

         snake_case_  :      Dict  	=							f.readlines()
         for lineTmp in lines:
               snake_case_  :      str  	=							lineTmp.strip()
               snake_case_  :      int  	=							line.rfind(" " )
               if idx == -1:
                     raise ValueError("Incorrect dictionary format, expected '<token> <cnt>'" )
               snake_case_  :      str  	=							line[:idx]
               snake_case_  :      Tuple  	=							len(self.encoder )











from ...configuration_utils import PretrainedConfig


lowerCamelCase__       		=  {
    """google/tapas-base-finetuned-sqa""": (
        """https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-wtq""": (
        """https://huggingface.co/google/tapas-base-finetuned-wtq/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-wikisql-supervised""": (
        """https://huggingface.co/google/tapas-base-finetuned-wikisql-supervised/resolve/main/config.json"""
    ),
    """google/tapas-base-finetuned-tabfact""": (
        """https://huggingface.co/google/tapas-base-finetuned-tabfact/resolve/main/config.json"""
    ),
}




class       snake_case__ (				lowercase_):

       '''simple docstring'''
       lowerCamelCase				:					Tuple								=			"tapas"



       def __init__(				self      ,    a__=3_05_22      ,    a__=7_68      ,    a__=12      ,    a__=12      ,    a__=30_72      ,    a__="gelu"      ,    a__=0.1      ,    a__=0.1      ,    a__=10_24      ,    a__=[3, 2_56, 2_56, 2, 2_56, 2_56, 10]      ,    a__=0.02      ,    a__=1e-12      ,    a__=0      ,    a__=10.0      ,    a__=0      ,    a__=1.0      ,    a__=None      ,    a__=1.0      ,    a__=False      ,    a__=None      ,    a__=1.0      ,    a__=1.0      ,    a__=False      ,    a__=False      ,    a__="ratio"      ,    a__=None      ,    a__=None      ,    a__=64      ,    a__=32      ,    a__=False      ,    a__=True      ,    a__=False      ,    a__=False      ,    a__=True      ,    a__=False      ,    a__=None      ,    a__=None      ,    **a__      ,    )			->   Any:






            '''simple docstring'''





            super().__init__(pad_token_id=a__      ,    **a__     )

            # BERT hyperparameters (with updated max_position_embeddings and type_vocab_sizes)
            __snake_case      :Optional[Any] 							=    vocab_size
            __snake_case      :Tuple 							=    hidden_size
            __snake_case      :Tuple 							=    num_hidden_layers
            __snake_case      :Any 							=    num_attention_heads
            __snake_case      :List[str] 							=    hidden_act
            __snake_case      :List[str] 							=    intermediate_size
            __snake_case      :int 							=    hidden_dropout_prob
            __snake_case      :List[Any] 							=    attention_probs_dropout_prob
            __snake_case      :Any 							=    max_position_embeddings
            __snake_case      :Optional[int] 							=    type_vocab_sizes
            __snake_case      :Tuple 							=    initializer_range
            __snake_case      :Any 							=    layer_norm_eps

            # Fine-tuning task hyperparameters
            __snake_case      :Optional[int] 							=    positive_label_weight
            __snake_case      :Optional[Any] 							=    num_aggregation_labels
            __snake_case      :Dict 							=    aggregation_loss_weight
            __snake_case      :str 							=    use_answer_as_supervision
            __snake_case      :int 							=    answer_loss_importance
            __snake_case      :List[Any] 							=    use_normalized_answer_loss
            __snake_case      :List[str] 							=    huber_loss_delta
            __snake_case      :Any 							=    temperature
            __snake_case      :Optional[int] 							=    aggregation_temperature
            __snake_case      :List[str] 							=    use_gumbel_for_cells
            __snake_case      :Optional[int] 							=    use_gumbel_for_aggregation
            __snake_case      :Optional[Any] 							=    average_approximation_function
            __snake_case      :Union[str, Any] 							=    cell_selection_preference
            __snake_case      :Tuple 							=    answer_loss_cutoff
            __snake_case      :Union[str, Any] 							=    max_num_rows
            __snake_case      :Optional[int] 							=    max_num_columns
            __snake_case      :str 							=    average_logits_per_cell
            __snake_case      :Union[str, Any] 							=    select_one_column
            __snake_case      :Optional[int] 							=    allow_empty_column_selection
            __snake_case      :Optional[Any] 							=    init_cell_selection_weights_to_zero
            __snake_case      :Tuple 							=    reset_position_index_per_cell
            __snake_case      :Any 							=    disable_per_token_loss

            # Aggregation hyperparameters
            __snake_case      :List[str] 							=    aggregation_labels
            __snake_case      :int 							=    no_aggregation_label_index

            if isinstance(self.aggregation_labels      ,    a__     ):
                 __snake_case      :Any 							=    {int(a__     ): v for k, v in aggregation_labels.items()}


