

import unittest

from transformers import BlenderbotTokenizer, BlenderbotTokenizerFast
from transformers.utils import cached_property



class 		a_	(							unittest.TestCase					):



      """simple docstring"""







      @cached_property
      def 	_lowerCAmelCase					(				self					:							Optional[Any]    ):
           return BlenderbotTokenizer.from_pretrained('facebook/blenderbot-3B'    )
      @cached_property
      def 	_lowerCAmelCase					(				self					:							Optional[Any]    ):
           return BlenderbotTokenizerFast.from_pretrained('facebook/blenderbot-3B'    )
      def 	_lowerCAmelCase					(				self					:							int    ):
           SCREAMING_SNAKE_CASE										=self.tokenizer_ab
           SCREAMING_SNAKE_CASE										=' I am a small frog.'
           SCREAMING_SNAKE_CASE										=tok([src_text]      ,padding=snake_case      ,truncation=snake_case    )['input_ids']
           SCREAMING_SNAKE_CASE										=tok.batch_decode(snake_case      ,skip_special_tokens=snake_case      ,clean_up_tokenization_spaces=snake_case    )[0]
           assert src_text == decoded
      def 	_lowerCAmelCase					(				self					:							Optional[int]    ):
           SCREAMING_SNAKE_CASE										=self.rust_tokenizer_ab
           SCREAMING_SNAKE_CASE										=' I am a small frog.'
           SCREAMING_SNAKE_CASE										=tok([src_text]      ,padding=snake_case      ,truncation=snake_case    )['input_ids']
           SCREAMING_SNAKE_CASE										=tok.batch_decode(snake_case      ,skip_special_tokens=snake_case      ,clean_up_tokenization_spaces=snake_case    )[0]
           assert src_text == decoded
      def 	_lowerCAmelCase					(				self					:							Tuple    ):
           assert self.tokenizer_ab.add_prefix_space
           assert self.tokenizer_ab([' Sam', 'Sam']    ).input_ids == [[5502, 2], [5502, 2]]


      def 	_lowerCAmelCase					(				self					:							Optional[int]    ):
           assert self.rust_tokenizer_ab.add_prefix_space
           assert self.rust_tokenizer_ab([' Sam', 'Sam']    ).input_ids == [[5502, 2], [5502, 2]]




import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey

from digital_image_processing.filters.convolve import img_convolve







def       snake_case__    (       lowerCAmelCase_      ):





     """simple docstring"""







     SCREAMING_SNAKE_CASE										=np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]]      )
     SCREAMING_SNAKE_CASE										=np.array([[1, 2, 1], [0, 0, 0], [-1, -2, -1]]      )

     SCREAMING_SNAKE_CASE										=np.abs(img_convolve(lowerCAmelCase_,   lowerCAmelCase_      )      )
     SCREAMING_SNAKE_CASE										=np.abs(img_convolve(lowerCAmelCase_,   lowerCAmelCase_      )      )
     # modify the pix within [0, 255]
     SCREAMING_SNAKE_CASE										=dst_x * 255 / np.max(lowerCAmelCase_      )
     SCREAMING_SNAKE_CASE										=dst_y * 255 / np.max(lowerCAmelCase_      )

     SCREAMING_SNAKE_CASE										=np.sqrt((np.square(lowerCAmelCase_      )) + (np.square(lowerCAmelCase_      ))      )
     SCREAMING_SNAKE_CASE										=dst_xy * 255 / np.max(lowerCAmelCase_      )
     SCREAMING_SNAKE_CASE										=dst_xy.astype(np.uinta      )

     SCREAMING_SNAKE_CASE										=np.arctana(lowerCAmelCase_,   lowerCAmelCase_      )
     return dst, theta


if __name__ == "__main__":
 # read original image
 _lowerCamelCase								=imread("../image_data/lena.jpg")
 # turn image in gray scale value
 _lowerCamelCase								=cvtColor(img, COLOR_BGR2GRAY)

 _lowerCamelCase	,			_lowerCamelCase								=sobel_filter(gray)

 # show result images
 imshow("sobel filter", sobel_grad)
 imshow("sobel theta", sobel_theta)
 waitKey(0)

