'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
    is_vision_available,
)


_A		:      Dict						   ={
    '''configuration_tvlt''': ['''TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TvltConfig'''],
    '''feature_extraction_tvlt''': ['''TvltFeatureExtractor'''],
    '''processing_tvlt''': ['''TvltProcessor'''],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      Optional[Any]						   =[
     '''TVLT_PRETRAINED_MODEL_ARCHIVE_LIST''',
     '''TvltModel''',
     '''TvltForPreTraining''',
     '''TvltForAudioVisualClassification''',
     '''TvltPreTrainedModel''',
 ]

try:
 if not is_vision_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 _A		:      List[str]						   =['''TvltImageProcessor''']


if TYPE_CHECKING:
 from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
 from .processing_tvlt import TvltProcessor
 from .feature_extraction_tvlt import TvltFeatureExtractor

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tvlt import (
      TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
      TvltForAudioVisualClassification,
      TvltForPreTraining,
      TvltModel,
      TvltPreTrainedModel,
  )

 try:
  if not is_vision_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .image_processing_tvlt import TvltImageProcessor


else:
 import sys

 _A		:      Dict						   =_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
'''simple docstring'''
def 				__UpperCamelCase (					__UpperCAmelCase  :					float ,   __UpperCAmelCase  :					float ,   __UpperCAmelCase  :					float			)							->	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'''			)

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

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

  return [red, green, blue]







def 				__UpperCamelCase (					__UpperCAmelCase  :					int ,   __UpperCAmelCase  :					int ,   __UpperCAmelCase  :					int			)							->	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'''			)

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

  if chroma == 0:
    lowercase				:							Dict									=   0.0
  elif value == float_red:
    lowercase				:							Tuple									=   60 * (0 + (float_green - float_blue) / chroma)
  elif value == float_green:
    lowercase				:							Optional[int]									=   60 * (2 + (float_blue - float_red) / chroma)
  else:
    lowercase				:							Dict									=   60 * (4 + (float_red - float_green) / chroma)

  lowercase				:							List[str]									=   (hue + 360) % 360

  return [hue, saturation, value]







def 				__UpperCamelCase (					__UpperCAmelCase  :					list[float] ,   __UpperCAmelCase  :					list[float]			)							->	bool:
  lowercase				:							int									=   abs(hsv_a[0] - hsv_a[0]			) < 0.2
  lowercase				:							Optional[int]									=   abs(hsv_a[1] - hsv_a[1]			) < 0.002
  lowercase				:							Dict									=   abs(hsv_a[2] - hsv_a[2]			) < 0.002

  return check_hue and check_saturation and check_value