




import json
import os
import unittest

from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
    VOCAB_FILES_NAMES,
    BlenderbotSmallTokenizer,
)

from ...test_tokenization_common import TokenizerTesterMixin







class a (     UpperCamelCase_       ,						unittest.TestCase  ):
						"""simple docstring"""

						UpperCamelCase_	:       Optional[Any]       	=		BlenderbotSmallTokenizer
						UpperCamelCase_	:       List[str]       	=		False






						def     UpperCAmelCase_      ( self :     Union[str, Any]				)    ->						List[str]:
													"""simple docstring"""


													super().setUp()

													__lowercase      =    ['__start__', 'adapt', 'act', 'ap@@', 'te', '__end__', '__unk__']
													__lowercase      =    dict(zip(__a				,							range(len(__a				)				)				)				)

													__lowercase      =    ['#version: 0.2', 'a p', 't e</w>', 'ap t</w>', 'a d', 'ad apt</w>', 'a c', 'ac t</w>', '']
													__lowercase      =    {'unk_token': '__unk__', 'bos_token': '__start__', 'eos_token': '__end__'}

													__lowercase      =    os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES['''vocab_file''']				)
													__lowercase      =    os.path.join(self.tmpdirname				,							VOCAB_FILES_NAMES['''merges_file''']				)
													with open(self.vocab_file				,							'''w'''				,							encoding='''utf-8'''				) as fp:
																				fp.write(json.dumps(__a				) + '''\n'''				)
													with open(self.merges_file				,							'''w'''				,							encoding='''utf-8'''				) as fp:
																				fp.write('''\n'''.join(__a				)				)






						def     UpperCAmelCase_      ( self :     List[Any]				,							**lowerCamelCase__ :     Union[str, Any]				)    ->						Tuple:
													"""simple docstring"""


													kwargs.update(self.special_tokens_map				)
													return BlenderbotSmallTokenizer.from_pretrained(self.tmpdirname				,							**__a				)






						def     UpperCAmelCase_      ( self :     List[str]				,							lowerCamelCase__ :     Optional[int]				)    ->						int:
													"""simple docstring"""


													__lowercase      =    'adapt act apte'
													__lowercase      =    'adapt act apte'
													return input_text, output_text






						def     UpperCAmelCase_      ( self :     List[str]				)    ->						Union[str, Any]:
													"""simple docstring"""


													__lowercase      =    BlenderbotSmallTokenizer(self.vocab_file				,							self.merges_file				,							**self.special_tokens_map				)
													__lowercase      =    'adapt act apte'
													__lowercase      =    ['adapt', 'act', 'ap@@', 'te']
													__lowercase      =    tokenizer.tokenize(__a				)
													self.assertListEqual(__a				,							__a				)

													__lowercase      =    [tokenizer.bos_token] + tokens + [tokenizer.eos_token]

													__lowercase      =    [0, 1, 2, 3, 4, 5]
													self.assertListEqual(tokenizer.convert_tokens_to_ids(__a				)				,							__a				)






						def     UpperCAmelCase_      ( self :     Optional[int]				)    ->						Tuple:
													"""simple docstring"""


													__lowercase      =    BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''				)
													assert tok('''sam'''				).input_ids == [1_384]
													__lowercase      =    'I am a small frog.'
													__lowercase      =    tok([src_text]				,							padding=__a				,							truncation=__a				)['input_ids']
													__lowercase      =    tok.batch_decode(__a				,							skip_special_tokens=__a				,							clean_up_tokenization_spaces=__a				)[0]
													assert src_text != decoded  # I wish it did!
													assert decoded == "i am a small frog ."






						def     UpperCAmelCase_      ( self :     str				)    ->						Dict:
													"""simple docstring"""


													__lowercase      =    BlenderbotSmallTokenizer.from_pretrained('''facebook/blenderbot-90M'''				)
													__lowercase      =    'I am a small frog .'
													__lowercase      =    '.'
													__lowercase      =    tok(__a				)['input_ids']
													__lowercase      =    tok(__a				)['input_ids']

													assert encoded[-1] == encoded_dot[0]







import cva
import numpy as np







class a :
						"""simple docstring"""

						def __init__( self :     Dict				,							lowerCamelCase__ :     float				,							lowerCamelCase__ :     int				)    ->						Dict:
													"""simple docstring"""


													if k in (0.0_4, 0.0_6):
																				__lowercase      =    k
																				__lowercase      =    window_size
													else:
																				raise ValueError('''invalid k value'''				)






						def __str__( self :     int				)    ->						str:
													"""simple docstring"""


													return str(self.k				)






						def     UpperCAmelCase_      ( self :     Dict				,							lowerCamelCase__ :     str				)    ->						tuple[cva.Mat, list[list[int]]]:
													"""simple docstring"""


													__lowercase      =    cva.imread(lowerCamelCase__				,							0				)
													__lowercase     ,     __lowercase      =    img.shape
													__lowercase      =    []
													__lowercase      =    img.copy()
													__lowercase      =    cva.cvtColor(lowerCamelCase__				,							cva.COLOR_GRAY2RGB				)
													__lowercase     ,     __lowercase      =    np.gradient(lowerCamelCase__				)
													__lowercase      =    dx**2
													__lowercase      =    dy**2
													__lowercase      =    dx * dy
													__lowercase      =    0.0_4
													__lowercase      =    self.window_size // 2
													for y in range(lowerCamelCase__				,							h - offset				):
																				for x in range(lowerCamelCase__				,							w - offset				):
																											__lowercase      =    ixx[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()
																											__lowercase      =    iyy[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()
																											__lowercase      =    ixy[
																											    y - offset : y + offset + 1, x - offset : x + offset + 1
																											].sum()

																											__lowercase      =    (wxx * wyy) - (wxy**2)
																											__lowercase      =    wxx + wyy
																											__lowercase      =    det - k * (trace**2)
																											# Can change the value
																											if r > 0.5:
																																		corner_list.append([x, y, r]				)
																																		color_img.itemset((y, x, 0)				,							0				)
																																		color_img.itemset((y, x, 1)				,							0				)
																																		color_img.itemset((y, x, 2)				,							255				)
													return color_img, corner_list


if __name__ == "__main__":
			UpperCAmelCase__				     = HarrisCorner(0.04, 3)
			UpperCAmelCase__     ,							UpperCAmelCase__				     = edge_detect.detect("path_to_image")
			cva.imwrite("detect.png", color_img)






