
# 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


lowerCamelCase__    :		Dict          =   {
    '''configuration_xmod''': [
        '''XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''XmodConfig''',
        '''XmodOnnxConfig''',
    ],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     lowerCamelCase__    :		int          =   [
         '''XMOD_PRETRAINED_MODEL_ARCHIVE_LIST''',
         '''XmodForCausalLM''',
         '''XmodForMaskedLM''',
         '''XmodForMultipleChoice''',
         '''XmodForQuestionAnswering''',
         '''XmodForSequenceClassification''',
         '''XmodForTokenClassification''',
         '''XmodModel''',
         '''XmodPreTrainedModel''',
     ]

if TYPE_CHECKING:
     from .configuration_xmod import XMOD_PRETRAINED_CONFIG_ARCHIVE_MAP, XmodConfig, XmodOnnxConfig

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_xmod import (
              XMOD_PRETRAINED_MODEL_ARCHIVE_LIST,
              XmodForCausalLM,
              XmodForMaskedLM,
              XmodForMultipleChoice,
              XmodForQuestionAnswering,
              XmodForSequenceClassification,
              XmodForTokenClassification,
              XmodModel,
              XmodPreTrainedModel,
          )

else:
     import sys

     lowerCamelCase__    :		Union[str, Any]          =   _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)








def 		UpperCamelCase	(      lowercase_ = 10_00   )		->	int:


  '''simple docstring'''






  return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1   )   )


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






