import json
import os
from typing import Optional, Tuple

import regex as re

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


__UpperCamelCase	: Tuple    		=  logging.get_logger(__name__)

__UpperCamelCase	: Tuple    		=  {
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
}

__UpperCamelCase	: Optional[Any]    		=  {
    """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"""},
}

__UpperCamelCase	: List[Any]    		=  {
    """ctrl""": 256,
}

__UpperCamelCase	: Union[str, 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    A			(					_lowercase		):
						SCREAMING_SNAKE_CASE							:					List[str]           =							set()
						SCREAMING_SNAKE_CASE							:					Optional[int]           =							word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)		)
												SCREAMING_SNAKE_CASE							:					Any           =							char

						SCREAMING_SNAKE_CASE							:					List[str]           =							set(UpperCamelCase__		)
						return pairs





class       lowercase__		(     lowercase_):
						UpperCamelCase_  =	VOCAB_FILES_NAMES
						UpperCamelCase_  =	PRETRAINED_VOCAB_FILES_MAP
						UpperCamelCase_  =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCamelCase_  =	CONTROL_CODES


						def __init__( self			:       int					,	UpperCamelCase__			:       List[str]					,	UpperCamelCase__			:       int					,	UpperCamelCase__			:       Dict="<unk>"					,	**UpperCamelCase__			:       Optional[Any]		):





												'''simple docstring'''





												super().__init__(unk_token=UpperCamelCase__					,	**UpperCamelCase__		)

												with open(UpperCamelCase__					,	encoding='''utf-8'''		) as vocab_handle:
																		SCREAMING_SNAKE_CASE							:					Any           =							json.load(UpperCamelCase__		)
												SCREAMING_SNAKE_CASE							:					str           =							{v: k for k, v in self.encoder.items()}
												with open(UpperCamelCase__					,	encoding='''utf-8'''		) as merges_handle:
																		SCREAMING_SNAKE_CASE							:					List[Any]           =							merges_handle.read().split('''\n'''		)[1:-1]
												SCREAMING_SNAKE_CASE							:					List[str]           =							[tuple(merge.split()		) for merge in merges]
												SCREAMING_SNAKE_CASE							:					Optional[int]           =							dict(zip(UpperCamelCase__					,	range(len(UpperCamelCase__		)		)		)		)
												SCREAMING_SNAKE_CASE							:					Any           =							{}


						@property
						def  __A ( self			:       Optional[Any]		):





												'''simple docstring'''





												return len(self.encoder		)


						def  __A ( self			:       int		):





												'''simple docstring'''





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


						def  __A ( self			:       str					,	UpperCamelCase__			:       Optional[int]		):





												'''simple docstring'''





												if token in self.cache:
																		return self.cache[token]
												SCREAMING_SNAKE_CASE							:					List[Any]           =							tuple(UpperCamelCase__		)
												SCREAMING_SNAKE_CASE							:					List[str]           =							tuple(list(word[:-1]		) + [word[-1] + '''</w>''']		)
												SCREAMING_SNAKE_CASE							:					List[str]           =							get_pairs(UpperCamelCase__		)

												if not pairs:
																		return token

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

																								if word[i] == first and i < len(UpperCamelCase__		) - 1 and word[i + 1] == second:
																														new_word.append(first + second		)
																														i += 2
																								else:
																														new_word.append(word[i]		)
																														i += 1
																		SCREAMING_SNAKE_CASE							:					str           =							tuple(UpperCamelCase__		)
																		SCREAMING_SNAKE_CASE							:					Dict           =							new_word
																		if len(UpperCamelCase__		) == 1:
																								break
																		else:
																								SCREAMING_SNAKE_CASE							:					Tuple           =							get_pairs(UpperCamelCase__		)
												SCREAMING_SNAKE_CASE							:					str           =							'''@@ '''.join(UpperCamelCase__		)
												SCREAMING_SNAKE_CASE							:					str           =							word[:-4]
												SCREAMING_SNAKE_CASE							:					Dict           =							word
												return word


						def  __A ( self			:       List[str]					,	UpperCamelCase__			:       Optional[Any]		):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:					Tuple           =							[]

												SCREAMING_SNAKE_CASE							:					int           =							re.findall(r'''\S+\n?'''					,	UpperCamelCase__		)

												for token in words:
																		split_tokens.extend(list(self.bpe(UpperCamelCase__		).split(''' '''		)		)		)
												return split_tokens


						def  __A ( self			:       Tuple					,	UpperCamelCase__			:       Tuple		):





												'''simple docstring'''





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


						def  __A ( self			:       Optional[Any]					,	UpperCamelCase__			:       Dict		):





												'''simple docstring'''





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


						def  __A ( self			:       List[str]					,	UpperCamelCase__			:       int		):





												'''simple docstring'''





												SCREAMING_SNAKE_CASE							:					List[str]           =							''' '''.join(UpperCamelCase__		).replace('''@@ '''					,	''''''		).strip()
												return out_string



						def  __A ( self			:       Dict					,	UpperCamelCase__			:       int					,	UpperCamelCase__			:       int = None		):





												'''simple docstring'''





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

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

												SCREAMING_SNAKE_CASE							:					str           =							0
												with open(UpperCamelCase__					,	'''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 UpperCamelCase__		: 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!'''		)
																														SCREAMING_SNAKE_CASE							:					Any           =							token_index
																								writer.write(''' '''.join(UpperCamelCase__		) + '''\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)
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


__UpperCamelCase	: Tuple    		=  {
    'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
    'configuration_maskformer_swin': ['MaskFormerSwinConfig'],
}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[Any]    		=  ['MaskFormerFeatureExtractor']
					__UpperCamelCase	: List[Any]    		=  ['MaskFormerImageProcessor']


try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					__UpperCamelCase	: Optional[int]    		=  [
					    'MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
					    'MaskFormerForInstanceSegmentation',
					    'MaskFormerModel',
					    'MaskFormerPreTrainedModel',
					]
					__UpperCamelCase	: Union[str, Any]    		=  [
					    'MaskFormerSwinBackbone',
					    'MaskFormerSwinModel',
					    'MaskFormerSwinPreTrainedModel',
					]

if TYPE_CHECKING:
					from .configuration_maskformer import MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, MaskFormerConfig
					from .configuration_maskformer_swin import MaskFormerSwinConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_maskformer import MaskFormerFeatureExtractor
										from .image_processing_maskformer import MaskFormerImageProcessor
					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_maskformer import (
										    MASKFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
										    MaskFormerForInstanceSegmentation,
										    MaskFormerModel,
										    MaskFormerPreTrainedModel,
										)
										from .modeling_maskformer_swin import (
										    MaskFormerSwinBackbone,
										    MaskFormerSwinModel,
										    MaskFormerSwinPreTrainedModel,
										)


else:
					import sys

					__UpperCamelCase	: List[str]    		=  _LazyModule(__name__, globals()['__file__'], _import_structure)





