



'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


__lowerCAmelCase									=   logging.get_logger(__name__)

__lowerCAmelCase									=   {'''vocab_file''': '''vocab.txt''', '''tokenizer_file''': '''tokenizer.json'''}

__lowerCAmelCase									=   {
    '''vocab_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'''
        ),
    },
    '''tokenizer_file''': {
        '''yjernite/retribert-base-uncased''': (
            '''https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'''
        ),
    },
}

__lowerCAmelCase									=   {
    '''yjernite/retribert-base-uncased''': 512,
}


__lowerCAmelCase									=   {
    '''yjernite/retribert-base-uncased''': {'''do_lower_case''': True},
}

class 	__magic_name__						(    _UpperCamelCase   ):
							lowerCAmelCase       :    Optional[Any]   				=					VOCAB_FILES_NAMES
							lowerCAmelCase       :    Optional[int]   				=					PRETRAINED_VOCAB_FILES_MAP
							lowerCAmelCase       :    Optional[Any]   				=					PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							lowerCAmelCase       :    Any   				=					PRETRAINED_INIT_CONFIGURATION
							lowerCAmelCase       :    List[str]   				=					RetriBertTokenizer
							lowerCAmelCase       :    Tuple   				=					['input_ids', 'attention_mask']







							def __init__(							self					:       str	,_UpperCAmelCase					:       List[Any]=None	,_UpperCAmelCase					:       Optional[Any]=None	,_UpperCAmelCase					:       Optional[int]=True	,_UpperCAmelCase					:       Union[str, Any]="[UNK]"	,_UpperCAmelCase					:       List[Any]="[SEP]"	,_UpperCAmelCase					:       str="[PAD]"	,_UpperCAmelCase					:       int="[CLS]"	,_UpperCAmelCase					:       str="[MASK]"	,_UpperCAmelCase					:       int=True	,_UpperCAmelCase					:       Tuple=None	,**_UpperCAmelCase					:       str	,):
									super().__init__(
									    _UpperCAmelCase	,tokenizer_file=_UpperCAmelCase	,do_lower_case=_UpperCAmelCase	,unk_token=_UpperCAmelCase	,sep_token=_UpperCAmelCase	,pad_token=_UpperCAmelCase	,cls_token=_UpperCAmelCase	,mask_token=_UpperCAmelCase	,tokenize_chinese_chars=_UpperCAmelCase	,strip_accents=_UpperCAmelCase	,**_UpperCAmelCase	,)

									_a     :      List[Any]        =							json.loads(self.backend_tokenizer.normalizer.__getstate__()		)
									if (
									    normalizer_state.get('lowercase'	,_UpperCAmelCase		) != do_lower_case
									    or normalizer_state.get('strip_accents'	,_UpperCAmelCase		) != strip_accents
									    or normalizer_state.get('handle_chinese_chars'	,_UpperCAmelCase		) != tokenize_chinese_chars
									):
											_a     :      List[Any]        =							getattr(_UpperCAmelCase	,normalizer_state.pop('type'		)		)
											_a     :      Union[str, Any]        =							do_lower_case
											_a     :      Optional[int]        =							strip_accents
											_a     :      Dict        =							tokenize_chinese_chars
											_a     :      Dict        =							normalizer_class(**_UpperCAmelCase		)

									_a     :      Dict        =							do_lower_case







							def 							__lowercase			(							self					:       Tuple	,_UpperCAmelCase					:       Any	,_UpperCAmelCase					:       Union[str, Any]=None		):
									_a     :      Any        =							[self.cls_token_id] + token_ids_a + [self.sep_token_id]

									if token_ids_a:
											output += token_ids_a + [self.sep_token_id]

									return output







							def 							__lowercase			(							self					:       List[str]	,_UpperCAmelCase					:       List[int]	,_UpperCAmelCase					:       Optional[List[int]] = None		):
									_a     :      Optional[int]        =							[self.sep_token_id]
									_a     :      Optional[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 							__lowercase			(							self					:       List[Any]	,_UpperCAmelCase					:       str	,_UpperCAmelCase					:       Optional[str] = None		):
									_a     :      Tuple        =							self._tokenizer.model.save(_UpperCAmelCase	,name=_UpperCAmelCase		)
									return tuple(_UpperCAmelCase		)









'''simple docstring'''

from pathlib import Path

import cva
import numpy as np
from matplotlib import pyplot as plt



def      __lowerCamelCase     (      lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_						,			lowerCAmelCase_  )			->      np.ndarray:
		_a     :      Union[str, Any]        =							cva.getAffineTransform(lowerCAmelCase_						,			lowerCAmelCase_  )
		return cva.warpAffine(lowerCAmelCase_						,			lowerCAmelCase_						,			(rows, cols)  )


if __name__ == "__main__":
							# read original image
							__lowerCAmelCase									=   cva.imread(
							    str(Path(__file__).resolve().parent.parent / '''image_data''' / '''lena.jpg''')
							)
							# turn image in gray scale value
							__lowerCAmelCase									=   cva.cvtColor(image, cva.COLOR_BGR2GRAY)
							# get image shape
							__lowerCAmelCase			,					__lowerCAmelCase									=   gray_img.shape

							# set different points to rotate image
							__lowerCAmelCase									=   np.array([[50, 50], [200, 50], [50, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [200, 50], [100, 250]], np.floataa)
							__lowerCAmelCase									=   np.array([[50, 50], [150, 50], [120, 200]], np.floataa)
							__lowerCAmelCase									=   np.array([[10, 100], [80, 50], [180, 250]], np.floataa)

							# add all rotated images in a list
							__lowerCAmelCase									=   [
							    gray_img,
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							    get_rotation(gray_img, ptsa, ptsa, img_rows, img_cols),
							]

							# plot different image rotations
							__lowerCAmelCase									=   plt.figure(1)
							__lowerCAmelCase									=   ['''Original''', '''Rotation 1''', '''Rotation 2''', '''Rotation 3''']
							for i, image in enumerate(images):
														plt.subplot(2, 2, i + 1), plt.imshow(image, '''gray''')
														plt.title(titles[i])
														plt.axis('''off''')
														plt.subplots_adjust(left=0.0, bottom=0.05, right=1.0, top=0.95)
							plt.show()




