





import json
import os
from typing import Dict, List, Optional, Tuple

import regex as re

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


_SCREAMING_SNAKE_CASE 		=						logging.get_logger(__name__)


_SCREAMING_SNAKE_CASE 		=						{
    """vocab_file""": """vocab.json""",
    """merges_file""": """merges.txt""",
    """tokenizer_config_file""": """tokenizer_config.json""",
}

_SCREAMING_SNAKE_CASE 		=						{
    """vocab_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/vocab.json"""
    },
    """merges_file""": {
        """facebook/blenderbot_small-90M""": """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/merges.txt"""
    },
    """tokenizer_config_file""": {
        """facebook/blenderbot_small-90M""": (
            """https://huggingface.co/facebook/blenderbot_small-90M/resolve/main/tokenizer_config.json"""
        )
    },
}

_SCREAMING_SNAKE_CASE 		=						{"""facebook/blenderbot_small-90M""": 5_12}


def 							SCREAMING_SNAKE_CASE__  (      __a				):
	snake_case_						:     List[str]     =		set()
	snake_case_						:     str     =		word[0]
	for char in word[1:]:
		pairs.add((prev_char, char)				)
		snake_case_						:     Dict     =		char

	snake_case_						:     List[Any]     =		set(__a				)
	return pairs


class SCREAMING_SNAKE_CASE_  (   snake_case_   ):
						__magic_name__:     str	 =    VOCAB_FILES_NAMES
						__magic_name__:     Tuple	 =    PRETRAINED_VOCAB_FILES_MAP
						__magic_name__:     int	 =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						__magic_name__:     List[Any]	 =    ["input_ids", "attention_mask"]






						def __init__( self : str						,				_A : Any						,				_A : List[str]						,				_A : Optional[int]="__start__"						,				_A : List[str]="__end__"						,				_A : Dict="__unk__"						,				_A : Union[str, Any]="__null__"						,				**_A : List[Any]						,				)							->      Tuple:







							"""simple docstring"""


							super().__init__(unk_token=_A						,				bos_token=_A						,				eos_token=_A						,				pad_token=_A						,				**_A		)

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






						@property
						def UpperCAmelCase_			( self : Dict		)							->      int:







							"""simple docstring"""


							return len(self.encoder		)






						def UpperCAmelCase_			( self : Tuple		)							->      Dict:







							"""simple docstring"""


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






						def UpperCAmelCase_			( self : Dict						,				_A : str		)							->      str:







							"""simple docstring"""


							if token in self.cache:
								return self.cache[token]
							snake_case_						:     Optional[Any]     =		re.sub('([.,!?()])'						,				R' \1'						,				_A		)
							snake_case_						:     List[str]     =		re.sub('(\')'						,				R' \1 '						,				_A		)
							snake_case_						:     Dict     =		re.sub(R'\s{2,}'						,				' '						,				_A		)
							if "\n" in token:
								snake_case_						:     Dict     =		token.replace('\n'						,				' __newln__'		)

							snake_case_						:     Dict     =		token.split(' '		)
							snake_case_						:     List[Any]     =		[]
							for token in tokens:
								if not len(_A		):
									continue

								snake_case_						:     Optional[int]     =		token.lower()
								snake_case_						:     Optional[int]     =		tuple(_A		)
								snake_case_						:     Tuple     =		tuple(list(word[:-1]		) + [word[-1] + '</w>']		)
								snake_case_						:     Tuple     =		get_pairs(_A		)

								if not pairs:
									words.append(_A		)
									continue

								while True:
									snake_case_						:     List[Any]     =		min(_A						,				key=lambda _A		: self.bpe_ranks.get(_A						,				float('inf'		)		)		)
									if bigram not in self.bpe_ranks:
										break
									snake_case_						:     List[str]     =		bigram
									snake_case_						:     Optional[Any]     =		[]
									snake_case_						:     Any     =		0

									while i < len(_A		):
										try:
											snake_case_						:     List[Any]     =		word.index(_A						,				_A		)
											new_word.extend(word[i:j]		)
											snake_case_						:     Any     =		j
										except ValueError:
											new_word.extend(word[i:]		)
											break

										if word[i] == first and i < len(_A		) - 1 and word[i + 1] == second:
											new_word.append(first + second		)
											i += 2
										else:
											new_word.append(word[i]		)
											i += 1
									snake_case_						:     Optional[Any]     =		tuple(_A		)
									snake_case_						:     str     =		new_word
									if len(_A		) == 1:
										break
									else:
										snake_case_						:     str     =		get_pairs(_A		)
								snake_case_						:     List[str]     =		'@@ '.join(_A		)
								snake_case_						:     Tuple     =		word[:-4]

								snake_case_						:     Union[str, Any]     =		word
								words.append(_A		)
							return " ".join(_A		)






						def UpperCAmelCase_			( self : List[str]						,				_A : str		)							->      List[str]:







							"""simple docstring"""


							snake_case_						:     Dict     =		[]

							snake_case_						:     List[str]     =		re.findall(R'\S+\n?'						,				_A		)

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






						def UpperCAmelCase_			( self : Dict						,				_A : str		)							->      int:







							"""simple docstring"""


							snake_case_						:     Any     =		token.lower()
							return self.encoder.get(_A						,				self.encoder.get(self.unk_token		)		)






						def UpperCAmelCase_			( self : int						,				_A : int		)							->      str:







							"""simple docstring"""


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






						def UpperCAmelCase_			( self : List[Any]						,				_A : List[str]		)							->      str:







							"""simple docstring"""


							snake_case_						:     str     =		' '.join(_A		).replace('@@ '						,				''		).strip()
							return out_string






						def UpperCAmelCase_			( self : Union[str, Any]						,				_A : str						,				_A : Optional[str] = None		)							->      Tuple[str]:







							"""simple docstring"""


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

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

							snake_case_						:     Any     =		0
							with open(_A						,				'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!'		)
										snake_case_						:     Optional[Any]     =		token_index
									writer.write(' '.join(_A		) + '\n'		)
									index += 1

							return vocab_file, merge_file












from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_SCREAMING_SNAKE_CASE 		=						{
    """configuration_informer""": [
        """INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """InformerConfig""",
    ],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						_SCREAMING_SNAKE_CASE 		=						[
						    """INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST""",
						    """InformerForPrediction""",
						    """InformerModel""",
						    """InformerPreTrainedModel""",
						]


if TYPE_CHECKING:
						from .configuration_informer import INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, InformerConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_informer import (
												    INFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
												    InformerForPrediction,
												    InformerModel,
												    InformerPreTrainedModel,
												)

else:
						import sys

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

