



import json
import os
from typing import Optional, Tuple

import regex as re

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


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

lowerCAmelCase__		:					Dict							={
    "vocab_file": "vocab.json",
    "merges_file": "merges.txt",
}

lowerCAmelCase__		:					List[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"},
}

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

lowerCAmelCase__		:					str							={
    "Pregnancy": 168629,
    "Christianity": 7675,
    "Explain": 106423,
    "Fitness": 63440,
    "Saving": 63163,
    "Ask": 27171,
    "Ass": 95985,
    "Joke": 163509,
    "Questions": 45622,
    "Thoughts": 49605,
    "Retail": 52342,
    "Feminism": 164338,
    "Writing": 11992,
    "Atheism": 192263,
    "Netflix": 48616,
    "Computing": 39639,
    "Opinion": 43213,
    "Alone": 44967,
    "Funny": 58917,
    "Gaming": 40358,
    "Human": 4088,
    "India": 1331,
    "Joker": 77138,
    "Diet": 36206,
    "Legal": 11859,
    "Norman": 4939,
    "Tip": 72689,
    "Weight": 52343,
    "Movies": 46273,
    "Running": 23425,
    "Science": 2090,
    "Horror": 37793,
    "Confession": 60572,
    "Finance": 12250,
    "Politics": 16360,
    "Scary": 191985,
    "Support": 12654,
    "Technologies": 32516,
    "Teenage": 66160,
    "Event": 32769,
    "Learned": 67460,
    "Notion": 182770,
    "Wikipedia": 37583,
    "Books": 6665,
    "Extract": 76050,
    "Confessions": 102701,
    "Conspiracy": 75932,
    "Links": 63674,
    "Narcissus": 150425,
    "Relationship": 54766,
    "Relationships": 134796,
    "Reviews": 41671,
    "News": 4256,
    "Translation": 26820,
    "multilingual": 128406,
}






def      __lowercase       (			a__       )    ->			Optional[Any]:
							__SCREAMING_SNAKE_CASE									= set()
							__SCREAMING_SNAKE_CASE									= word[0]
							for char in word[1:]:
														pairs.add((prev_char, char)       )
														__SCREAMING_SNAKE_CASE									= char

							__SCREAMING_SNAKE_CASE									= set(_UpperCAmelCase       )
							return pairs







class        UpperCAmelCase_  (       snake_case__	):

						'''simple docstring'''




						UpperCamelCase__      :			List[Any]      =  VOCAB_FILES_NAMES
						UpperCamelCase__      :			Optional[Any]      =  PRETRAINED_VOCAB_FILES_MAP
						UpperCamelCase__      :			Tuple      =  PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						UpperCamelCase__      :			Optional[Any]      =  CONTROL_CODES






						def __init__(   self				,							_A				,							_A				,							_A="<unk>"				,							**_A		):







													'''simple docstring'''

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

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






						@property
						def 	_A     (   self		):







													'''simple docstring'''

													return len(self.encoder		)






						def 	_A     (   self		):







													'''simple docstring'''

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






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													if token in self.cache:
																				return self.cache[token]
													__SCREAMING_SNAKE_CASE									= tuple(UpperCAmelCase_		)
													__SCREAMING_SNAKE_CASE									= tuple(list(word[:-1]		) + [word[-1] + '</w>']		)
													__SCREAMING_SNAKE_CASE									= get_pairs(UpperCAmelCase_		)

													if not pairs:
																				return token

													while True:
																				__SCREAMING_SNAKE_CASE									= min(UpperCAmelCase_				,							key=lambda _A		: self.bpe_ranks.get(UpperCAmelCase_				,							float('inf'		)		)		)
																				if bigram not in self.bpe_ranks:
																											break
																				__SCREAMING_SNAKE_CASE									= bigram
																				__SCREAMING_SNAKE_CASE									= []
																				__SCREAMING_SNAKE_CASE									= 0
																				while i < len(UpperCAmelCase_		):
																											try:
																																		__SCREAMING_SNAKE_CASE									= word.index(UpperCAmelCase_				,							UpperCAmelCase_		)
																											except ValueError:
																																		new_word.extend(word[i:]		)
																																		break
																											else:
																																		new_word.extend(word[i:j]		)
																																		__SCREAMING_SNAKE_CASE									= 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									= tuple(UpperCAmelCase_		)
																				__SCREAMING_SNAKE_CASE									= new_word
																				if len(UpperCAmelCase_		) == 1:
																											break
																				else:
																											__SCREAMING_SNAKE_CASE									= get_pairs(UpperCAmelCase_		)
													__SCREAMING_SNAKE_CASE									= "@@ ".join(UpperCAmelCase_		)
													__SCREAMING_SNAKE_CASE									= word[:-4]
													__SCREAMING_SNAKE_CASE									= word
													return word






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= []

													__SCREAMING_SNAKE_CASE									= re.findall(r'\S+\n?'				,							UpperCAmelCase_		)

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






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

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






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

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






						def 	_A     (   self				,							_A		):







													'''simple docstring'''

													__SCREAMING_SNAKE_CASE									= " ".join(UpperCAmelCase_		).replace('@@ '				,							''		).strip()
													return out_string






						def 	_A     (   self				,							_A				,							_A = None		):







													'''simple docstring'''

													if not os.path.isdir(UpperCAmelCase_		):
																				logger.error(f"""Vocabulary path ({save_directory}) should be a directory"""		)
																				return
													__SCREAMING_SNAKE_CASE									= os.path.join(
													    UpperCAmelCase_				,							(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file']		)
													__SCREAMING_SNAKE_CASE									= 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									= 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 _A		: 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									= 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_flax_available,
    is_tf_available,
    is_torch_available,
)


lowerCAmelCase__		:					str							={'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__		:					Optional[int]							=[
			    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
			    '''ViTMAEForPreTraining''',
			    '''ViTMAELayer''',
			    '''ViTMAEModel''',
			    '''ViTMAEPreTrainedModel''',
			]

try:
			if not is_tf_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			lowerCAmelCase__		:					List[str]							=[
			    '''TFViTMAEForPreTraining''',
			    '''TFViTMAEModel''',
			    '''TFViTMAEPreTrainedModel''',
			]

if TYPE_CHECKING:
			from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_vit_mae import (
						    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
						    ViTMAEForPreTraining,
						    ViTMAELayer,
						    ViTMAEModel,
						    ViTMAEPreTrainedModel,
						)

			try:
						if not is_tf_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
			import sys

			lowerCAmelCase__		:					Optional[int]							=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






