



"""simple docstring"""
import json
from typing import Iterator, List, Union

from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
class 				lowerCamelCase  (			_lowerCAmelCase				):






					'''simple docstring'''





					def __init__(       self:							List[Any]						,     snake_case:							str = "▁"						,     snake_case:							bool = True						,     snake_case:							Union[str, AddedToken] = "<unk>"						,     snake_case:							Union[str, AddedToken] = "</s>"						,     snake_case:							Union[str, AddedToken] = "<pad>"						,     )   ->	Any:
											snake_case_ :Any						=			{
											    """pad""": {"""id""": 0, """token""": pad_token},
											    """eos""": {"""id""": 1, """token""": eos_token},
											    """unk""": {"""id""": 2, """token""": unk_token},
											}

											snake_case_ :Dict						=			[None] * len(self.special_tokens						)
											for token_dict in self.special_tokens.values():
																	snake_case_ :Tuple						=			token_dict["""token"""]

											snake_case_ :Union[str, Any]						=			Tokenizer(Unigram()						)

											snake_case_ :Tuple						=			normalizers.Sequence(
											    [
											        normalizers.Nmt(),
											        normalizers.NFKC(),
											        normalizers.Replace(Regex(""" {2,}"""						)						,     """ """						),
											        normalizers.Lowercase(),
											    ]						)
											snake_case_ :str						=			pre_tokenizers.Sequence(
											    [
											        pre_tokenizers.Metaspace(replacement=snake_case						,     add_prefix_space=snake_case						),
											        pre_tokenizers.Digits(individual_digits=snake_case						),
											        pre_tokenizers.Punctuation(),
											    ]						)
											snake_case_ :Dict						=			decoders.Metaspace(replacement=snake_case						,     add_prefix_space=snake_case						)

											snake_case_ :str						=			TemplateProcessing(
											    single=f"""$A {self.special_tokens['eos']['token']}"""						,     special_tokens=[(self.special_tokens["""eos"""]["""token"""], self.special_tokens["""eos"""]["""id"""])]						,     )

											snake_case_ :Tuple						=			{
											    """model""": """SentencePieceUnigram""",
											    """replacement""": replacement,
											    """add_prefix_space""": add_prefix_space,
											}

											super().__init__(snake_case						,     snake_case						)






					def    lowerCAmelCase_				(       self:							Dict						,     snake_case:							Union[str, List[str]]						,     snake_case:							int = 8_000						,     snake_case:							bool = True						,     )   ->	int:
											snake_case_ :List[Any]						=			trainers.UnigramTrainer(
											    vocab_size=snake_case						,     special_tokens=self.special_tokens_list						,     show_progress=snake_case						,     )

											if isinstance(snake_case						,     snake_case						):
																	snake_case_ :int						=			[files]
											self._tokenizer.train(snake_case						,     trainer=snake_case						)

											self.add_unk_id()






					def    lowerCAmelCase_				(       self:							Dict						,     snake_case:							Union[Iterator[str], Iterator[Iterator[str]]]						,     snake_case:							int = 8_000						,     snake_case:							bool = True						,     )   ->	List[str]:
											snake_case_ :Optional[Any]						=			trainers.UnigramTrainer(
											    vocab_size=snake_case						,     special_tokens=self.special_tokens_list						,     show_progress=snake_case						,     )

											self._tokenizer.train_from_iterator(snake_case						,     trainer=snake_case						)

											self.add_unk_id()






					def    lowerCAmelCase_				(       self:							List[Any]						)   ->	Tuple:
											snake_case_ :Dict						=			json.loads(self._tokenizer.to_str()						)

											snake_case_ :Optional[int]						=			self.special_tokens["""unk"""]["""id"""]

											snake_case_ :Optional[int]						=			Tokenizer.from_str(json.dumps(snake_case						)						)


import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image


if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
					SCREAMING_SNAKE_CASE							:Any							 =				{
					    'linear': PIL.Image.Resampling.BILINEAR,
					    'bilinear': PIL.Image.Resampling.BILINEAR,
					    'bicubic': PIL.Image.Resampling.BICUBIC,
					    'lanczos': PIL.Image.Resampling.LANCZOS,
					    'nearest': PIL.Image.Resampling.NEAREST,
					}
else:
					SCREAMING_SNAKE_CASE							:int							 =				{
					    'linear': PIL.Image.LINEAR,
					    'bilinear': PIL.Image.BILINEAR,
					    'bicubic': PIL.Image.BICUBIC,
					    'lanczos': PIL.Image.LANCZOS,
					    'nearest': PIL.Image.NEAREST,
					}


def 						UpperCAmelCase			(	a_						)		->	Optional[Any]:







				"""simple docstring"""



				__A   			= (images / 2 + 0.5).clamp(0		,   1						)
				__A   			= images.cpu().permute(0		,   2		,   3		,   1						).float().numpy()
				__A   			= numpy_to_pil(a_						)
				return images


def 						UpperCAmelCase			(	a_						)		->	int:







				"""simple docstring"""



				if images.ndim == 3:
								__A   			= images[None, ...]
				__A   			= (images * 2_5_5).round().astype("uint8"						)
				if images.shape[-1] == 1:
								# special case for grayscale (single channel) images
								__A   			= [Image.fromarray(image.squeeze()		,   mode="L"						) for image in images]
				else:
								__A   			= [Image.fromarray(a_						) for image in images]

				return pil_images
