

import json
import os
from typing import Optional, Tuple

import regex as re

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


SCREAMING_SNAKE_CASE		:Optional[Any]						=     logging.get_logger(__name__)

SCREAMING_SNAKE_CASE		:List[Any]						=     {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
}

SCREAMING_SNAKE_CASE		:Tuple						=     {
    """vocab_file""": {"""ctrl""": """https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-vocab.json"""},
    """merges_file""": {"""ctrl""": """https://raw.githubusercontent.com/salesforce/ctrl/master/ctrl-merges.txt"""},
}

SCREAMING_SNAKE_CASE		:Dict						=     {
    """ctrl""": 256,
}

SCREAMING_SNAKE_CASE		:List[Any]						=     {
    """Pregnancy""": 16_8629,
    """Christianity""": 7675,
    """Explain""": 10_6423,
    """Fitness""": 6_3440,
    """Saving""": 6_3163,
    """Ask""": 2_7171,
    """Ass""": 9_5985,
    """Joke""": 16_3509,
    """Questions""": 4_5622,
    """Thoughts""": 4_9605,
    """Retail""": 5_2342,
    """Feminism""": 16_4338,
    """Writing""": 1_1992,
    """Atheism""": 19_2263,
    """Netflix""": 4_8616,
    """Computing""": 3_9639,
    """Opinion""": 4_3213,
    """Alone""": 4_4967,
    """Funny""": 5_8917,
    """Gaming""": 4_0358,
    """Human""": 4088,
    """India""": 1331,
    """Joker""": 7_7138,
    """Diet""": 3_6206,
    """Legal""": 1_1859,
    """Norman""": 4939,
    """Tip""": 7_2689,
    """Weight""": 5_2343,
    """Movies""": 4_6273,
    """Running""": 2_3425,
    """Science""": 2090,
    """Horror""": 3_7793,
    """Confession""": 6_0572,
    """Finance""": 1_2250,
    """Politics""": 1_6360,
    """Scary""": 19_1985,
    """Support""": 1_2654,
    """Technologies""": 3_2516,
    """Teenage""": 6_6160,
    """Event""": 3_2769,
    """Learned""": 6_7460,
    """Notion""": 18_2770,
    """Wikipedia""": 3_7583,
    """Books""": 6665,
    """Extract""": 7_6050,
    """Confessions""": 10_2701,
    """Conspiracy""": 7_5932,
    """Links""": 6_3674,
    """Narcissus""": 15_0425,
    """Relationship""": 5_4766,
    """Relationships""": 13_4796,
    """Reviews""": 4_1671,
    """News""": 4256,
    """Translation""": 2_6820,
    """multilingual""": 12_8406,
}




def 			lowerCAmelCase(      SCREAMING_SNAKE_CASE_			)->						Tuple:



    """simple docstring"""






    UpperCamelCase_			  =						set()
    UpperCamelCase_			  =						word[0]
    for char in word[1:]:
        pairs.add((prev_char, char)			)
        UpperCamelCase_			  =						char

    UpperCamelCase_			  =						set(SCREAMING_SNAKE_CASE_			)
    return pairs






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:List[Any]										=      VOCAB_FILES_NAMES
     UpperCamelCase_	:List[Any]										=      PRETRAINED_VOCAB_FILES_MAP
     UpperCamelCase_	:int										=      PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCamelCase_	:int										=      CONTROL_CODES






     def __init__(				self		,						_lowercase		,						_lowercase		,						_lowercase="<unk>"		,						**_lowercase	)->     Optional[Any]:
         super().__init__(unk_token=_lowercase		,						**_lowercase	)

         with open(_lowercase		,						encoding="utf-8"	) as vocab_handle:
             UpperCamelCase_			  =						json.load(_lowercase	)
         UpperCamelCase_			  =						{v: k for k, v in self.encoder.items()}
         with open(_lowercase		,						encoding="utf-8"	) as merges_handle:
             UpperCamelCase_			  =						merges_handle.read().split("\n"	)[1:-1]
         UpperCamelCase_			  =						[tuple(merge.split()	) for merge in merges]
         UpperCamelCase_			  =						dict(zip(_lowercase		,						range(len(_lowercase	)	)	)	)
         UpperCamelCase_			  =						{}






     @property
     def 	UpperCAmelCase_				(				self	)->     Tuple:
         return len(self.encoder	)






     def 	UpperCAmelCase_				(				self	)->     Any:
         return dict(self.encoder		,						**self.added_tokens_encoder	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Tuple:
         if token in self.cache:
             return self.cache[token]
         UpperCamelCase_			  =						tuple(_lowercase	)
         UpperCamelCase_			  =						tuple(list(word[:-1]	) + [word[-1] + "</w>"]	)
         UpperCamelCase_			  =						get_pairs(_lowercase	)

         if not pairs:
             return token

         while True:
             UpperCamelCase_			  =						min(_lowercase		,						key=lambda _lowercase	: self.bpe_ranks.get(_lowercase		,						float("inf"	)	)	)
             if bigram not in self.bpe_ranks:
                 break
             UpperCamelCase_  ,       UpperCamelCase_			  =						bigram
             UpperCamelCase_			  =						[]
             UpperCamelCase_			  =						0
             while i < len(_lowercase	):
                 try:
                     UpperCamelCase_			  =						word.index(_lowercase		,						_lowercase	)
                 except ValueError:
                     new_word.extend(word[i:]	)
                     break
                 else:
                     new_word.extend(word[i:j]	)
                     UpperCamelCase_			  =						j

                 if word[i] == first and i < len(_lowercase	) - 1 and word[i + 1] == second:
                     new_word.append(first + second	)
                     i += 2
                 else:
                     new_word.append(word[i]	)
                     i += 1
             UpperCamelCase_			  =						tuple(_lowercase	)
             UpperCamelCase_			  =						new_word
             if len(_lowercase	) == 1:
                 break
             else:
                 UpperCamelCase_			  =						get_pairs(_lowercase	)
         UpperCamelCase_			  =						"@@ ".join(_lowercase	)
         UpperCamelCase_			  =						word[:-4]
         UpperCamelCase_			  =						word
         return word






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Dict:
         UpperCamelCase_			  =						[]

         UpperCamelCase_			  =						re.findall(r"\S+\n?"		,						_lowercase	)

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






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Optional[Any]:
         return self.encoder.get(_lowercase		,						self.encoder.get(self.unk_token	)	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     Optional[int]:
         return self.decoder.get(_lowercase		,						self.unk_token	)






     def 	UpperCAmelCase_				(				self		,						_lowercase	)->     List[Any]:
         UpperCamelCase_			  =						" ".join(_lowercase	).replace("@@ "		,						""	).strip()
         return out_string






     def 	UpperCAmelCase_				(				self		,						_lowercase		,						_lowercase = None	)->     Tuple[str]:
         if not os.path.isdir(_lowercase	):
             logger.error(F"Vocabulary path ({save_directory}) should be a directory"	)
             return
         UpperCamelCase_			  =						os.path.join(
             _lowercase		,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]	)
         UpperCamelCase_			  =						os.path.join(
             _lowercase		,						(filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["merges_file"]	)

         with open(_lowercase		,						"w"		,						encoding="utf-8"	) as f:
             f.write(json.dumps(self.encoder		,						indent=2		,						sort_keys=_lowercase		,						ensure_ascii=_lowercase	) + "\n"	)

         UpperCamelCase_			  =						0
         with open(_lowercase		,						"w"		,						encoding="utf-8"	) as writer:
             writer.write("#version: 0.2\n"	)
             for bpe_tokens, token_index in sorted(self.bpe_ranks.items()		,						key=lambda _lowercase	: kv[1]	):
                 if index != token_index:
                     logger.warning(
                         F"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
                         " Please check that the tokenizer is not corrupted!"	)
                     UpperCamelCase_			  =						token_index
                 writer.write(" ".join(_lowercase	) + "\n"	)
                 index += 1

         return vocab_file, merge_file

     # def decode(self, token_ids, skip_special_tokens=False, clean_up_tokenization_spaces=True):
     #     filtered_tokens = ' '.join(self.convert_ids_to_tokens(token_ids, skip_special_tokens=skip_special_tokens))
     #     tokens_generated_so_far = re.sub('(@@ )', '', string=filtered_tokens)
     #     tokens_generated_so_far = re.sub('(@@ ?$)', '', string=tokens_generated_so_far)
     #     return ''.join(tokens_generated_so_far)



import copy
from typing import Dict, List, Optional

from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING


SCREAMING_SNAKE_CASE		:Optional[Any]						=     {
    """facebook/mask2former-swin-small-coco-instance""": (
        """https://huggingface.co/facebook/mask2former-swin-small-coco-instance/blob/main/config.json"""
    )
    # See all Mask2Former models at https://huggingface.co/models?filter=mask2former
}

SCREAMING_SNAKE_CASE		:Union[str, Any]						=     logging.get_logger(__name__)






class 						__magic_name__					(							snake_case				):
     UpperCamelCase_	:Optional[int]										=      """mask2former"""
     UpperCamelCase_	:Dict										=      ["""swin"""]
     UpperCamelCase_	:List[Any]										=      {"""hidden_size""": """hidden_dim"""}






     def __init__(				self		,						_lowercase = None		,						_lowercase = 256		,						_lowercase = 256		,						_lowercase = 256		,						_lowercase = 1_024		,						_lowercase = "relu"		,						_lowercase = 6		,						_lowercase = 10		,						_lowercase = 8		,						_lowercase = 0.0		,						_lowercase = 2_048		,						_lowercase = False		,						_lowercase = False		,						_lowercase = 4		,						_lowercase = 255		,						_lowercase = 100		,						_lowercase = 0.1		,						_lowercase = 2.0		,						_lowercase = 5.0		,						_lowercase = 5.0		,						_lowercase = 12_544		,						_lowercase = 3.0		,						_lowercase = 0.75		,						_lowercase = 0.02		,						_lowercase = 1.0		,						_lowercase = True		,						_lowercase = [4, 8, 16, 32]		,						_lowercase = None		,						**_lowercase		,						)->     Union[str, Any]:
         if backbone_config is None:
             logger.info("`backbone_config` is `None`. Initializing the config with the default `Swin` backbone."	)
             UpperCamelCase_			  =						CONFIG_MAPPING["swin"](
                 image_size=224		,						in_channels=3		,						patch_size=4		,						embed_dim=96		,						depths=[2, 2, 18, 2]		,						num_heads=[3, 6, 12, 24]		,						window_size=7		,						drop_path_rate=0.3		,						use_absolute_embeddings=_lowercase		,						out_features=["stage1", "stage2", "stage3", "stage4"]		,						)

         if isinstance(_lowercase		,						_lowercase	):
             UpperCamelCase_			  =						backbone_config.pop("model_type"	)
             UpperCamelCase_			  =						CONFIG_MAPPING[backbone_model_type]
             UpperCamelCase_			  =						config_class.from_dict(_lowercase	)

         # verify that the backbone is supported
         if backbone_config.model_type not in self.backbones_supported:
             logger.warning_once(
                 F"Backbone {backbone_config.model_type} is not a supported model and may not be compatible with Mask2Former. "
                 F"Supported model types: {','.join(self.backbones_supported	)}"	)

         UpperCamelCase_			  =						backbone_config
         UpperCamelCase_			  =						feature_size
         UpperCamelCase_			  =						mask_feature_size
         UpperCamelCase_			  =						hidden_dim
         UpperCamelCase_			  =						encoder_feedforward_dim
         UpperCamelCase_			  =						activation_function
         UpperCamelCase_			  =						encoder_layers
         UpperCamelCase_			  =						decoder_layers
         UpperCamelCase_			  =						num_attention_heads
         UpperCamelCase_			  =						dropout
         UpperCamelCase_			  =						dim_feedforward
         UpperCamelCase_			  =						pre_norm
         UpperCamelCase_			  =						enforce_input_projection
         UpperCamelCase_			  =						common_stride
         UpperCamelCase_			  =						ignore_value
         UpperCamelCase_			  =						num_queries
         UpperCamelCase_			  =						no_object_weight
         UpperCamelCase_			  =						class_weight
         UpperCamelCase_			  =						mask_weight
         UpperCamelCase_			  =						dice_weight
         UpperCamelCase_			  =						train_num_points
         UpperCamelCase_			  =						oversample_ratio
         UpperCamelCase_			  =						importance_sample_ratio
         UpperCamelCase_			  =						init_std
         UpperCamelCase_			  =						init_xavier_std
         UpperCamelCase_			  =						use_auxiliary_loss
         UpperCamelCase_			  =						feature_strides
         UpperCamelCase_			  =						output_auxiliary_logits
         UpperCamelCase_			  =						decoder_layers

         super().__init__(**_lowercase	)






     @classmethod
     def 	UpperCAmelCase_				(				cls		,						_lowercase		,						**_lowercase	)->     Optional[int]:
         return cls(
             backbone_config=_lowercase		,						**_lowercase		,						)






     def 	UpperCAmelCase_				(				self	)->     Dict[str, any]:
         UpperCamelCase_			  =						copy.deepcopy(self.__dict__	)
         UpperCamelCase_			  =						self.backbone_config.to_dict()
         UpperCamelCase_			  =						self.__class__.model_type
         return output
