"""simple docstring"""





from typing import List, Optional, Tuple

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer


lowerCAmelCase_     =	logging.get_logger(__name__)

lowerCAmelCase_     =	{'''vocab_file''': '''vocab.json''', '''merges_file''': '''merges.txt''', '''tokenizer_file''': '''tokenizer.json'''}

lowerCAmelCase_     =	{
    '''vocab_file''': {
        '''allegro/herbert-base-cased''': '''https://huggingface.co/allegro/herbert-base-cased/resolve/main/vocab.json'''
    },
    '''merges_file''': {
        '''allegro/herbert-base-cased''': '''https://huggingface.co/allegro/herbert-base-cased/resolve/main/merges.txt'''
    },
}

lowerCAmelCase_     =	{'''allegro/herbert-base-cased''': 514}
lowerCAmelCase_     =	{}




class  _snake_case		(    __snake_case ):







				"""simple docstring"""






				a			=						VOCAB_FILES_NAMES
				a			=						PRETRAINED_VOCAB_FILES_MAP
				a			=						PRETRAINED_INIT_CONFIGURATION
				a			=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				a			=						HerbertTokenizer





				def __init__(      self							:							int      ,    _A							:							List[Any]=None      ,    _A							:							Optional[Any]=None      ,    _A							:							int=None      ,    _A							:							Any="<s>"      ,    _A							:							Union[str, Any]="<unk>"      ,    _A							:							List[Any]="<pad>"      ,    _A							:							str="<mask>"      ,    _A							:							Any="</s>"      ,    **_A							:							str      ,    ):



											"""simple docstring"""







											super().__init__(
											    _A      ,    _A      ,    tokenizer_file=_A      ,    cls_token=_A      ,    unk_token=_A      ,    pad_token=_A      ,    mask_token=_A      ,    sep_token=_A      ,    **_A      ,    )





				def 		_lowerCAmelCase		(      self							:							Any      ,    _A							:							List[int]      ,    _A							:							Optional[List[int]] = None):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						List[str]			  =    [self.cls_token_id]
											_SCREAMING_SNAKE_CASE		:						Optional[int]			  =    [self.sep_token_id]
											if token_ids_a is None:
																		return cls + token_ids_a + sep

											return cls + token_ids_a + sep + token_ids_a + sep





				def 		_lowerCAmelCase		(      self							:							str      ,    _A							:							List[int]      ,    _A							:							Optional[List[int]] = None      ,    _A							:							bool = False):



											"""simple docstring"""







											if already_has_special_tokens:
																		return super().get_special_tokens_mask(
																		    token_ids_a=_A      ,    token_ids_a=_A      ,    already_has_special_tokens=_A)

											if token_ids_a is None:
																		return [1] + ([0] * len(_A)) + [1]
											return [1] + ([0] * len(_A)) + [1] + ([0] * len(_A)) + [1]





				def 		_lowerCAmelCase		(      self							:							int      ,    _A							:							List[int]      ,    _A							:							Optional[List[int]] = None):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Union[str, Any]			  =    [self.sep_token_id]
											_SCREAMING_SNAKE_CASE		:						Any			  =    [self.cls_token_id]

											if token_ids_a is None:
																		return len(cls + token_ids_a + sep) * [0]
											return len(cls + token_ids_a + sep) * [0] + len(token_ids_a + sep) * [1]





				def 		_lowerCAmelCase		(      self							:							Any      ,    _A							:							str      ,    _A							:							Optional[str] = None):



											"""simple docstring"""







											_SCREAMING_SNAKE_CASE		:						Tuple			  =    self._tokenizer.model.save(_A      ,    name=_A)
											return tuple(_A)



"""simple docstring"""





import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey




class  _snake_case		:







				"""simple docstring"""






				def __init__(      self							:							int      ,    _A							:							List[Any]      ,    _A							:							int      ,    _A							:							int):



											"""simple docstring"""







											if dst_width < 0 or dst_height < 0:
																		raise ValueError("""Destination width/height should be > 0""")

											_SCREAMING_SNAKE_CASE		:						str			  =    img
											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    img.shape[1]
											_SCREAMING_SNAKE_CASE		:						Tuple			  =    img.shape[0]
											_SCREAMING_SNAKE_CASE		:						Any			  =    dst_width
											_SCREAMING_SNAKE_CASE		:						Any			  =    dst_height

											_SCREAMING_SNAKE_CASE		:						Any			  =    self.src_w / self.dst_w
											_SCREAMING_SNAKE_CASE		:						Dict			  =    self.src_h / self.dst_h

											_SCREAMING_SNAKE_CASE		:						Optional[Any]			  =    (
											    np.ones((self.dst_h, self.dst_w, 3)      ,    np.uinta) * 2_5_5
											)





				def 		_lowerCAmelCase		(      self							:							Tuple):



											"""simple docstring"""







											for i in range(self.dst_h):
																		for j in range(self.dst_w):
																									_SCREAMING_SNAKE_CASE		:						Any			  =    self.img[self.get_y(_A)][self.get_x(_A)]





				def 		_lowerCAmelCase		(      self							:							int      ,    _A							:							int):



											"""simple docstring"""







											return int(self.ratio_x * x)





				def 		_lowerCAmelCase		(      self							:							str      ,    _A							:							int):



											"""simple docstring"""







											return int(self.ratio_y * y)


if __name__ == "__main__":
			lowerCAmelCase_ ,					lowerCAmelCase_     =	800, 600
			lowerCAmelCase_     =	imread('''image_data/lena.jpg''', 1)
			lowerCAmelCase_     =	NearestNeighbour(im, dst_w, dst_h)
			n.process()

			imshow(
			    F"Image resized from: {im.shape[1]}x{im.shape[0]} to {dst_w}x{dst_h}", n.output
			)
			waitKey(0)
			destroyAllWindows()


