


"""simple docstring"""






def        A_					(					UpperCAmelCase__       ,   UpperCAmelCase__       ,   UpperCAmelCase__				)     ->     list[int]:



   if hue < 0 or hue > 360:
      raise Exception('hue should be between 0 and 360'				)

   if saturation < 0 or saturation > 1:
      raise Exception('saturation should be between 0 and 1'				)

   if value < 0 or value > 1:
      raise Exception('value should be between 0 and 1'				)

   a   :	Dict						=    value * saturation
   a   :	List[str]						=    hue / 60
   a   :	Tuple						=    chroma * (1 - abs(hue_section % 2 - 1				))
   a   :	Tuple						=    value - chroma

   if hue_section >= 0 and hue_section <= 1:
      a   :	str						=    round(255 * (chroma + match_value)				)
      a   :	Optional[int]						=    round(255 * (second_largest_component + match_value)				)
      a   :	List[str]						=    round(255 * (match_value)				)
   elif hue_section > 1 and hue_section <= 2:
      a   :	Union[str, Any]						=    round(255 * (second_largest_component + match_value)				)
      a   :	Optional[Any]						=    round(255 * (chroma + match_value)				)
      a   :	Tuple						=    round(255 * (match_value)				)
   elif hue_section > 2 and hue_section <= 3:
      a   :	str						=    round(255 * (match_value)				)
      a   :	List[Any]						=    round(255 * (chroma + match_value)				)
      a   :	Optional[int]						=    round(255 * (second_largest_component + match_value)				)
   elif hue_section > 3 and hue_section <= 4:
      a   :	Dict						=    round(255 * (match_value)				)
      a   :	List[str]						=    round(255 * (second_largest_component + match_value)				)
      a   :	List[Any]						=    round(255 * (chroma + match_value)				)
   elif hue_section > 4 and hue_section <= 5:
      a   :	str						=    round(255 * (second_largest_component + match_value)				)
      a   :	Union[str, Any]						=    round(255 * (match_value)				)
      a   :	Dict						=    round(255 * (chroma + match_value)				)
   else:
      a   :	Optional[Any]						=    round(255 * (chroma + match_value)				)
      a   :	List[Any]						=    round(255 * (match_value)				)
      a   :	Optional[Any]						=    round(255 * (second_largest_component + match_value)				)

   return [red, green, blue]




def        A_					(					UpperCAmelCase__       ,   UpperCAmelCase__       ,   UpperCAmelCase__				)     ->     list[float]:



   if red < 0 or red > 255:
      raise Exception('red should be between 0 and 255'				)

   if green < 0 or green > 255:
      raise Exception('green should be between 0 and 255'				)

   if blue < 0 or blue > 255:
      raise Exception('blue should be between 0 and 255'				)

   a   :	List[str]						=    red / 255
   a   :	int						=    green / 255
   a   :	int						=    blue / 255
   a   :	Optional[Any]						=    max(UpperCamelCase_       ,   UpperCamelCase_       ,   UpperCamelCase_				)
   a   :	List[Any]						=    value - min(UpperCamelCase_       ,   UpperCamelCase_       ,   UpperCamelCase_				)
   a   :	List[Any]						=    0 if value == 0 else chroma / value

   if chroma == 0:
      a   :	Union[str, Any]						=    0.0
   elif value == float_red:
      a   :	List[Any]						=    60 * (0 + (float_green - float_blue) / chroma)
   elif value == float_green:
      a   :	Tuple						=    60 * (2 + (float_blue - float_red) / chroma)
   else:
      a   :	Dict						=    60 * (4 + (float_red - float_green) / chroma)

   a   :	Optional[int]						=    (hue + 360) % 360

   return [hue, saturation, value]




def        A_					(					UpperCAmelCase__       ,   UpperCAmelCase__				)     ->     bool:
   a   :	Optional[Any]						=    abs(hsv_a[0] - hsv_a[0]				) < 0.2
   a   :	int						=    abs(hsv_a[1] - hsv_a[1]				) < 0.0_0_2
   a   :	Any						=    abs(hsv_a[2] - hsv_a[2]				) < 0.0_0_2

   return check_hue and check_saturation and check_value













from transformers import (
    DPRContextEncoderTokenizer,
    DPRContextEncoderTokenizerFast,
    DPRQuestionEncoderTokenizer,
    DPRQuestionEncoderTokenizerFast,
    DPRReaderOutput,
    DPRReaderTokenizer,
    DPRReaderTokenizerFast,
)
from transformers.testing_utils import require_tokenizers, slow
from transformers.tokenization_utils_base import BatchEncoding

from ..bert.test_tokenization_bert import BertTokenizationTest


@require_tokenizers
class      __SCREAMING_SNAKE_CASE       ( __lowercase):
						_SCREAMING_SNAKE_CASE						:							Tuple				=       DPRContextEncoderTokenizer
						_SCREAMING_SNAKE_CASE						:							Any				=       DPRContextEncoderTokenizerFast
						_SCREAMING_SNAKE_CASE						:							str				=       True




@require_tokenizers
class      __SCREAMING_SNAKE_CASE       ( __lowercase):
						_SCREAMING_SNAKE_CASE						:							Optional[Any]				=       DPRQuestionEncoderTokenizer
						_SCREAMING_SNAKE_CASE						:							List[Any]				=       DPRQuestionEncoderTokenizerFast
						_SCREAMING_SNAKE_CASE						:							Optional[Any]				=       True




@require_tokenizers
class      __SCREAMING_SNAKE_CASE       ( __lowercase):
						_SCREAMING_SNAKE_CASE						:							Any				=       DPRReaderTokenizer
						_SCREAMING_SNAKE_CASE						:							int				=       DPRReaderTokenizerFast
						_SCREAMING_SNAKE_CASE						:							List[str]				=       True






						@slow
						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    self.tokenizer_class.from_pretrained('bert-base-uncased' )

												lowerCAmelCase__         =    tokenizer.encode('question sequence'  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    tokenizer.encode('title sequence'  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    tokenizer.encode('text sequence ' * 4  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    [[1_01] + text_a + [1_02] + text_a + [1_02] + text_a]
												lowerCAmelCase__         =    BatchEncoding({'input_ids': input_ids} )

												lowerCAmelCase__         =    [[0] * len(input_ids[0] )]
												lowerCAmelCase__         =    [[0] * len(input_ids[0] )]
												lowerCAmelCase__         =    [0]
												lowerCAmelCase__         =    DPRReaderOutput(_UpperCamelCase  ,    _UpperCamelCase  ,    _UpperCamelCase )

												lowerCAmelCase__    ,							lowerCAmelCase__         =    8, 9
												lowerCAmelCase__         =    10
												lowerCAmelCase__         =    10
												lowerCAmelCase__         =    tokenizer.decode_best_spans(_UpperCamelCase  ,    _UpperCamelCase )
												self.assertEqual(predicted_spans[0].start_index  ,    _UpperCamelCase )
												self.assertEqual(predicted_spans[0].end_index  ,    _UpperCamelCase )
												self.assertEqual(predicted_spans[0].doc_id  ,    0 )







						@slow
						def    UpperCamelCase__   (						self ):






												"""simple docstring"""
												lowerCAmelCase__         =    self.tokenizer_class.from_pretrained('bert-base-uncased' )

												lowerCAmelCase__         =    tokenizer.encode('question sequence'  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    tokenizer.encode('title sequence'  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    tokenizer.encode('text sequence'  ,    add_special_tokens=_UpperCamelCase )
												lowerCAmelCase__         =    [1_01] + text_a + [1_02] + text_a + [1_02] + text_a
												lowerCAmelCase__         =    tokenizer(questions=['question sequence']  ,    titles=['title sequence']  ,    texts=['text sequence'] )
												self.assertIn('input_ids'  ,    _UpperCamelCase )
												self.assertIn('attention_mask'  ,    _UpperCamelCase )
												self.assertListEqual(encoded_input['input_ids'][0]  ,    _UpperCamelCase )





