






# 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

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


lowerCamelCase__							=     {
    """configuration_efficientnet""": [
        """EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """EfficientNetConfig""",
        """EfficientNetOnnxConfig""",
    ]
}

try:
     if not is_vision_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     ["""EfficientNetImageProcessor"""]

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__							=     [
         """EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """EfficientNetForImageClassification""",
         """EfficientNetModel""",
         """EfficientNetPreTrainedModel""",
     ]

if TYPE_CHECKING:
     from .configuration_efficientnet import (
         EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP,
         EfficientNetConfig,
         EfficientNetOnnxConfig,
     )

     try:
          if not is_vision_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .image_processing_efficientnet import EfficientNetImageProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_efficientnet import (
              EFFICIENTNET_PRETRAINED_MODEL_ARCHIVE_LIST,
              EfficientNetForImageClassification,
              EfficientNetModel,
              EfficientNetPreTrainedModel,
          )

else:
     import sys

     lowerCamelCase__							=     _LazyModule(__name__, globals()["""__file__"""], _import_structure)










import math

lowerCamelCase__							=     10
lowerCamelCase__							=     7
lowerCamelCase__							=     BALLS_PER_COLOUR * NUM_COLOURS






def   UpperCamelCase  (       snake_case__     :   int = 20  ):




     '''simple docstring'''






     __snake_case			:Dict          =						math.comb(snake_case__	,snake_case__  )
     __snake_case			:int          =						math.comb(NUM_BALLS - BALLS_PER_COLOUR	,snake_case__  )

     __snake_case			:List[str]          =						NUM_COLOURS * (1 - missing_colour / total)

     return f'''{result:.9f}'''


if __name__ == "__main__":
     print(solution(20))


