



import json
import os
from typing import Optional, Tuple

import regex as re

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


UpperCAmelCase_									=							logging.get_logger(__name__)

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

UpperCAmelCase_									=							{
    "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_									=							{
    "ctrl": 2_5_6,
}

UpperCAmelCase_									=							{
    "Pregnancy": 1_6_8_6_2_9,
    "Christianity": 7_6_7_5,
    "Explain": 1_0_6_4_2_3,
    "Fitness": 6_3_4_4_0,
    "Saving": 6_3_1_6_3,
    "Ask": 2_7_1_7_1,
    "Ass": 9_5_9_8_5,
    "Joke": 1_6_3_5_0_9,
    "Questions": 4_5_6_2_2,
    "Thoughts": 4_9_6_0_5,
    "Retail": 5_2_3_4_2,
    "Feminism": 1_6_4_3_3_8,
    "Writing": 1_1_9_9_2,
    "Atheism": 1_9_2_2_6_3,
    "Netflix": 4_8_6_1_6,
    "Computing": 3_9_6_3_9,
    "Opinion": 4_3_2_1_3,
    "Alone": 4_4_9_6_7,
    "Funny": 5_8_9_1_7,
    "Gaming": 4_0_3_5_8,
    "Human": 4_0_8_8,
    "India": 1_3_3_1,
    "Joker": 7_7_1_3_8,
    "Diet": 3_6_2_0_6,
    "Legal": 1_1_8_5_9,
    "Norman": 4_9_3_9,
    "Tip": 7_2_6_8_9,
    "Weight": 5_2_3_4_3,
    "Movies": 4_6_2_7_3,
    "Running": 2_3_4_2_5,
    "Science": 2_0_9_0,
    "Horror": 3_7_7_9_3,
    "Confession": 6_0_5_7_2,
    "Finance": 1_2_2_5_0,
    "Politics": 1_6_3_6_0,
    "Scary": 1_9_1_9_8_5,
    "Support": 1_2_6_5_4,
    "Technologies": 3_2_5_1_6,
    "Teenage": 6_6_1_6_0,
    "Event": 3_2_7_6_9,
    "Learned": 6_7_4_6_0,
    "Notion": 1_8_2_7_7_0,
    "Wikipedia": 3_7_5_8_3,
    "Books": 6_6_6_5,
    "Extract": 7_6_0_5_0,
    "Confessions": 1_0_2_7_0_1,
    "Conspiracy": 7_5_9_3_2,
    "Links": 6_3_6_7_4,
    "Narcissus": 1_5_0_4_2_5,
    "Relationship": 5_4_7_6_6,
    "Relationships": 1_3_4_7_9_6,
    "Reviews": 4_1_6_7_1,
    "News": 4_2_5_6,
    "Translation": 2_6_8_2_0,
    "multilingual": 1_2_8_4_0_6,
}
def 							UpperCAmelCase__		(				_SCREAMING_SNAKE_CASE   :	Tuple				)->Union[str, Any]:
						_lowerCAmelCase 			=  set()
						_lowerCAmelCase 			=  word[0]
						for char in word[1:]:
												pairs.add((prev_char, char)				)
												_lowerCAmelCase 			=  char

						_lowerCAmelCase 			=  set(_SCREAMING_SNAKE_CASE				)
						return pairs





class 		UpperCAmelCase						(						snake_case_				):
			SCREAMING_SNAKE_CASE__							=     VOCAB_FILES_NAMES
			SCREAMING_SNAKE_CASE__							=     PRETRAINED_VOCAB_FILES_MAP
			SCREAMING_SNAKE_CASE__							=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			SCREAMING_SNAKE_CASE__							=     CONTROL_CODES





			def __init__(	self       ,     _lowerCAmelCase       ,     _lowerCAmelCase       ,     _lowerCAmelCase="<unk>"       ,     **_lowerCAmelCase			):
									super().__init__(unk_token=_lowerCAmelCase       ,     **_lowerCAmelCase			)

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





			@property
			def 	__lowerCAmelCase							(	self			):
									return len(self.encoder			)





			def 	__lowerCAmelCase							(	self			):
									return dict(self.encoder       ,     **self.added_tokens_encoder			)





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

									if not pairs:
															return token

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

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





			def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
									_lowerCAmelCase 			=  []

									_lowerCAmelCase 			=  re.findall(R'''\S+\n?'''       ,     _lowerCAmelCase			)

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





			def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
									return self.encoder.get(_lowerCAmelCase       ,     self.encoder.get(self.unk_token			)			)





			def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
									return self.decoder.get(_lowerCAmelCase       ,     self.unk_token			)





			def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase			):
									_lowerCAmelCase 			=  ''' '''.join(_lowerCAmelCase			).replace('''@@ '''       ,     ''''''			).strip()
									return out_string





			def 	__lowerCAmelCase							(	self       ,     _lowerCAmelCase       ,     _lowerCAmelCase = None			):
									if not os.path.isdir(_lowerCAmelCase			):
															logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''			)
															return
									_lowerCAmelCase 			=  os.path.join(
									    _lowerCAmelCase       ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']			)
									_lowerCAmelCase 			=  os.path.join(
									    _lowerCAmelCase       ,     (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''merges_file''']			)

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

									_lowerCAmelCase 			=  0
									with open(_lowerCAmelCase       ,     '''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 _lowerCAmelCase			: 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!'''			)
																											_lowerCAmelCase 			=  token_index
																					writer.write(''' '''.join(_lowerCAmelCase			) + '''\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_tf_available,
    is_torch_available,
    is_vision_available,
)


UpperCAmelCase_									=							{"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxConfig"]}

try:
    if not is_vision_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase_									=							["DeiTFeatureExtractor"]
    UpperCAmelCase_									=							["DeiTImageProcessor"]

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase_									=							[
        "DEIT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "DeiTForImageClassification",
        "DeiTForImageClassificationWithTeacher",
        "DeiTForMaskedImageModeling",
        "DeiTModel",
        "DeiTPreTrainedModel",
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    UpperCAmelCase_									=							[
        "TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST",
        "TFDeiTForImageClassification",
        "TFDeiTForImageClassificationWithTeacher",
        "TFDeiTForMaskedImageModeling",
        "TFDeiTModel",
        "TFDeiTPreTrainedModel",
    ]


if TYPE_CHECKING:
    from .configuration_deit import DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, DeiTConfig, DeiTOnnxConfig

    try:
        if not is_vision_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .feature_extraction_deit import DeiTFeatureExtractor
        from .image_processing_deit import DeiTImageProcessor

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_deit import (
            DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            DeiTForImageClassification,
            DeiTForImageClassificationWithTeacher,
            DeiTForMaskedImageModeling,
            DeiTModel,
            DeiTPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_deit import (
            TF_DEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFDeiTForImageClassification,
            TFDeiTForImageClassificationWithTeacher,
            TFDeiTForMaskedImageModeling,
            TFDeiTModel,
            TFDeiTPreTrainedModel,
        )


else:
    import sys

    UpperCAmelCase_									=							_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)