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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
     from .tokenization_barthez import BarthezTokenizer
else:
     lowerCamelCase__    :		Union[str, Any]          =   None

lowerCamelCase__    :		List[str]          =   logging.get_logger(__name__)

lowerCamelCase__    :		Union[str, Any]          =   {"""vocab_file""": """sentencepiece.bpe.model""", """tokenizer_file""": """tokenizer.json"""}

lowerCamelCase__    :		int          =   {
    """vocab_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model"""
        ),
    },
    """tokenizer_file""": {
        """moussaKam/mbarthez""": """https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez""": """https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json""",
        """moussaKam/barthez-orangesum-title""": (
            """https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json"""
        ),
    },
}

lowerCamelCase__    :		Optional[Any]          =   {
    """moussaKam/mbarthez""": 1_0_2_4,
    """moussaKam/barthez""": 1_0_2_4,
    """moussaKam/barthez-orangesum-title""": 1_0_2_4,
}

lowerCamelCase__    :		Tuple          =   """▁"""



class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     int        =			VOCAB_FILES_NAMES
 __lowerCAmelCase  :     Optional[Any]        =			PRETRAINED_VOCAB_FILES_MAP
 __lowerCAmelCase  :     Dict        =			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 __lowerCAmelCase  :     str        =			['input_ids', 'attention_mask']
 __lowerCAmelCase  :     Union[str, Any]        =			BarthezTokenizer


 def __init__(					self					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_=None					,  SCREAMING_SNAKE_CASE_="<s>"					,  SCREAMING_SNAKE_CASE_="</s>"					,  SCREAMING_SNAKE_CASE_="</s>"					,  SCREAMING_SNAKE_CASE_="<s>"					,  SCREAMING_SNAKE_CASE_="<unk>"					,  SCREAMING_SNAKE_CASE_="<pad>"					,  SCREAMING_SNAKE_CASE_="<mask>"					,  **SCREAMING_SNAKE_CASE_					,  ):


   '''simple docstring'''




   lowercase__  :   int    		=      AddedToken(SCREAMING_SNAKE_CASE_					,  lstrip=SCREAMING_SNAKE_CASE_					,  rstrip=SCREAMING_SNAKE_CASE_) if isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_) else mask_token

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

   lowercase__  :   List[Any]    		=      vocab_file
   lowercase__  :   Any    		=      False if not self.vocab_file else True


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   if token_ids_a is None:
     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
   lowercase__  :   Optional[Any]    		=      [self.cls_token_id]
   lowercase__  :   Optional[int]    		=      [self.sep_token_id]
   return cls + token_ids_a + sep + sep + token_ids_a + sep


 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   lowercase__  :   Dict    		=      [self.sep_token_id]
   lowercase__  :   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]



 def      lowercase__     (					self					,  SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   if not self.can_save_slow_tokenizer:
     raise ValueError(
         """Your fast tokenizer does not have the necessary information to save the vocabulary for a slow """
         """tokenizer.""")

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

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

   return (out_vocab_file,)








import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig


lowerCamelCase__    :		List[str]          =   logging.get_logger(__name__)

lowerCamelCase__    :		str          =   {
    """Intel/dpt-large""": """https://huggingface.co/Intel/dpt-large/resolve/main/config.json""",
    # See all DPT models at https://huggingface.co/models?filter=dpt
}



class       _snake_case   (	UpperCAmelCase_							):
 __lowerCAmelCase  :     Optional[int]        =			'dpt'


 def __init__(					self					,  SCREAMING_SNAKE_CASE_=7_68					,  SCREAMING_SNAKE_CASE_=12					,  SCREAMING_SNAKE_CASE_=12					,  SCREAMING_SNAKE_CASE_=30_72					,  SCREAMING_SNAKE_CASE_="gelu"					,  SCREAMING_SNAKE_CASE_=0.0					,  SCREAMING_SNAKE_CASE_=0.0					,  SCREAMING_SNAKE_CASE_=0.0_2					,  SCREAMING_SNAKE_CASE_=1E-12					,  SCREAMING_SNAKE_CASE_=3_84					,  SCREAMING_SNAKE_CASE_=16					,  SCREAMING_SNAKE_CASE_=3					,  SCREAMING_SNAKE_CASE_=False					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=[2, 5, 8, 11]					,  SCREAMING_SNAKE_CASE_="project"					,  SCREAMING_SNAKE_CASE_=[4, 2, 1, 0.5]					,  SCREAMING_SNAKE_CASE_=[96, 1_92, 3_84, 7_68]					,  SCREAMING_SNAKE_CASE_=2_56					,  SCREAMING_SNAKE_CASE_=-1					,  SCREAMING_SNAKE_CASE_=False					,  SCREAMING_SNAKE_CASE_=True					,  SCREAMING_SNAKE_CASE_=0.4					,  SCREAMING_SNAKE_CASE_=2_55					,  SCREAMING_SNAKE_CASE_=0.1					,  SCREAMING_SNAKE_CASE_=[1, 10_24, 24, 24]					,  SCREAMING_SNAKE_CASE_=[0, 1]					,  SCREAMING_SNAKE_CASE_=None					,  **SCREAMING_SNAKE_CASE_					,  ):


   '''simple docstring'''




   super().__init__(**SCREAMING_SNAKE_CASE_)

   lowercase__  :   List[str]    		=      hidden_size
   lowercase__  :   str    		=      is_hybrid

   if self.is_hybrid:
     if backbone_config is None:
       logger.info("""Initializing the config with a `BiT` backbone.""")
       lowercase__  :   Any    		=      {
           """global_padding""": """same""",
           """layer_type""": """bottleneck""",
           """depths""": [3, 4, 9],
           """out_features""": ["""stage1""", """stage2""", """stage3"""],
           """embedding_dynamic_padding""": True,
       }
       lowercase__  :   Optional[Any]    		=      BitConfig(**SCREAMING_SNAKE_CASE_)
     elif isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):
       logger.info("""Initializing the config with a `BiT` backbone.""")
       lowercase__  :   List[Any]    		=      BitConfig(**SCREAMING_SNAKE_CASE_)
     elif isinstance(SCREAMING_SNAKE_CASE_					,  SCREAMING_SNAKE_CASE_):
       lowercase__  :   int    		=      backbone_config
     else:
       raise ValueError(
           f'backbone_config must be a dictionary or a `PretrainedConfig`, got {backbone_config.__class__}.')

     lowercase__  :   Optional[Any]    		=      backbone_featmap_shape
     lowercase__  :   List[str]    		=      neck_ignore_stages

     if readout_type != "project":
       raise ValueError("""Readout type must be 'project' when using `DPT-hybrid` mode.""")
   else:
     lowercase__  :   Optional[int]    		=      None
     lowercase__  :   Union[str, Any]    		=      None
     lowercase__  :   Tuple    		=      []

   lowercase__  :   List[str]    		=      num_hidden_layers
   lowercase__  :   Union[str, Any]    		=      num_attention_heads
   lowercase__  :   List[Any]    		=      intermediate_size
   lowercase__  :   Optional[Any]    		=      hidden_act
   lowercase__  :   int    		=      hidden_dropout_prob
   lowercase__  :   str    		=      attention_probs_dropout_prob
   lowercase__  :   Dict    		=      initializer_range
   lowercase__  :   Tuple    		=      layer_norm_eps
   lowercase__  :   List[str]    		=      image_size
   lowercase__  :   Tuple    		=      patch_size
   lowercase__  :   Tuple    		=      num_channels
   lowercase__  :   Dict    		=      qkv_bias
   lowercase__  :   List[Any]    		=      backbone_out_indices
   if readout_type not in ["ignore", "add", "project"]:
     raise ValueError("""Readout_type must be one of ['ignore', 'add', 'project']""")
   lowercase__  :   Dict    		=      readout_type
   lowercase__  :   Tuple    		=      reassemble_factors
   lowercase__  :   Any    		=      neck_hidden_sizes
   lowercase__  :   Dict    		=      fusion_hidden_size
   lowercase__  :   Tuple    		=      head_in_index
   lowercase__  :   Tuple    		=      use_batch_norm_in_fusion_residual
   # auxiliary head attributes (semantic segmentation)
   lowercase__  :   Tuple    		=      use_auxiliary_head
   lowercase__  :   int    		=      auxiliary_loss_weight
   lowercase__  :   Union[str, Any]    		=      semantic_loss_ignore_index
   lowercase__  :   str    		=      semantic_classifier_dropout



 def      lowercase__     (					self):


   '''simple docstring'''




   lowercase__  :   Optional[int]    		=      copy.deepcopy(self.__dict__)

   if output["backbone_config"] is not None:
     lowercase__  :   Optional[Any]    		=      self.backbone_config.to_dict()

   lowercase__  :   Dict    		=      self.__class__.model_type
   return output






