

def 				_UpperCAmelCase							(	a__     ,  a__     ,  a__):

			'''simple docstring'''



			if common_ratio == 1:
						# Formula for sum if common ratio is 1
						return num_of_terms * first_term

			# Formula for finding sum of n terms of a GeometricProgression
			return (first_term / (1 - common_ratio)) * (1 - common_ratio**num_of_terms)





# 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,
)


__snake_case							:			Any      		= {
    """configuration_convnextv2""": [
        """CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ConvNextV2Config""",
    ]
}

try:
	if not is_torch_available():
		raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
	pass
else:
	__snake_case							:			Dict      		= [
	    """CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST""",
	    """ConvNextV2ForImageClassification""",
	    """ConvNextV2Model""",
	    """ConvNextV2PreTrainedModel""",
	    """ConvNextV2Backbone""",
	]


if TYPE_CHECKING:
	from .configuration_convnextva import (
	    CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP,
	    ConvNextVaConfig,
	)

	try:
		if not is_torch_available():
			raise OptionalDependencyNotAvailable()
	except OptionalDependencyNotAvailable:
		pass
	else:
		from .modeling_convnextva import (
		    CONVNEXTV2_PRETRAINED_MODEL_ARCHIVE_LIST,
		    ConvNextVaBackbone,
		    ConvNextVaForImageClassification,
		    ConvNextVaModel,
		    ConvNextVaPreTrainedModel,
		)

else:
	import sys

	__snake_case							:			Dict      		= _LazyModule(__name__, globals()["""__file__"""], _import_structure)


