


# 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


SCREAMING_SNAKE_CASE			:			Optional[Any]        =     {
    '''configuration_efficientnet''': [
        '''EFFICIENTNET_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''EfficientNetConfig''',
        '''EfficientNetOnnxConfig''',
    ]
}

try:
	if not is_vision_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	SCREAMING_SNAKE_CASE			:			Optional[int]        =     ['''EfficientNetImageProcessor''']

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	SCREAMING_SNAKE_CASE			:			Union[str, Any]        =     [
	    '''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

	SCREAMING_SNAKE_CASE			:			Tuple        =     _LazyModule(__name__, globals()["__file__"], _import_structure)



import functools






def _lowerCamelCase  (		snake_case     , snake_case  ):

							# Validation
							if not isinstance(snake_case     , snake_case  ) or not all(isinstance(snake_case     , snake_case  ) for day in days  ):
														raise ValueError('The parameter days should be a list of integers'  )

							if len(snake_case  ) != 3 or not all(isinstance(snake_case     , snake_case  ) for cost in costs  ):
														raise ValueError('The parameter costs should be a list of three integers'  )

							if len(snake_case  ) == 0:
														return 0

							if min(snake_case  ) <= 0:
														raise ValueError('All days elements should be greater than 0'  )

							if max(snake_case  ) >= 366:
														raise ValueError('All days elements should be less than 366'  )

							_lowerCAmelCase							=							set(snake_case  )

							@functools.cache
							def dynamic_programming(snake_case  ) -> int:
														if index > 365:
																					return 0

														if index not in days_set:
																					return dynamic_programming(index + 1  )

														return min(
														    costs[0] + dynamic_programming(index + 1  )     , costs[1] + dynamic_programming(index + 7  )     , costs[2] + dynamic_programming(index + 30  )     , )

							return dynamic_programming(1  )


if __name__ == "__main__":
				import doctest

				doctest.testmod()






