



from typing import TYPE_CHECKING

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


lowercase_	       =			{
    "configuration_efficientformer": [
        "EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "EfficientFormerConfig",
    ]
}

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

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    "EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "EfficientFormerForImageClassification",
				    "EfficientFormerForImageClassificationWithTeacher",
				    "EfficientFormerModel",
				    "EfficientFormerPreTrainedModel",
				]

try:
				if not is_tf_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				lowercase_	       =			[
				    "TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
				    "TFEfficientFormerForImageClassification",
				    "TFEfficientFormerForImageClassificationWithTeacher",
				    "TFEfficientFormerModel",
				    "TFEfficientFormerPreTrainedModel",
				]

if TYPE_CHECKING:
				from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

				try:
								if not is_vision_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .image_processing_efficientformer import EfficientFormerImageProcessor

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_efficientformer import (
								    EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    EfficientFormerForImageClassification,
								    EfficientFormerForImageClassificationWithTeacher,
								    EfficientFormerModel,
								    EfficientFormerPreTrainedModel,
								)
				try:
								if not is_tf_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_tf_efficientformer import (
								    TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
								    TFEfficientFormerForImageClassification,
								    TFEfficientFormerForImageClassificationWithTeacher,
								    TFEfficientFormerModel,
								    TFEfficientFormerPreTrainedModel,
								)

else:
				import sys

				lowercase_	       =			_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)








def 					__lowerCAmelCase		(  __lowerCamelCase	:    int	)  ->						list:
					__lowerCAmelCase	   =int(__lowerCamelCase	)
					if n_element < 1:
										__lowerCAmelCase	   =ValueError("""a should be a positive number"""	)
										raise my_error

					__lowerCAmelCase	   =[1]
					__lowerCAmelCase   ,	__lowerCAmelCase   ,	__lowerCAmelCase	   =(0, 0, 0)
					__lowerCAmelCase	   =1
					while index < n_element:
										while hamming_list[i] * 2 <= hamming_list[-1]:
															i += 1
										while hamming_list[j] * 3 <= hamming_list[-1]:
															j += 1
										while hamming_list[k] * 5 <= hamming_list[-1]:
															k += 1
										hamming_list.append(
										    min(hamming_list[i] * 2				,   hamming_list[j] * 3				,   hamming_list[k] * 5	)	)
										index += 1
					return hamming_list


if __name__ == "__main__":
				lowercase_	       =			input('''Enter the last number (nth term) of the Hamming Number Series: ''')
				print('''Formula of Hamming Number Series => 2^i * 3^j * 5^k''')
				lowercase_	       =			hamming(int(n))
				print('''-----------------------------------------------------''')
				print(F"The list with nth numbers is: {hamming_numbers}")
				print('''-----------------------------------------------------''')




