



"""simple docstring"""


from __future__ import annotations

def 			_lowerCAmelCase				(       lowercase_						):
						if len(lowercase_						) < 2:
												raise ValueError('Monogons and Digons are not polygons in the Euclidean space'						)
						if any(i <= 0 for i in nums						):
												raise ValueError('All values must be greater than 0'						)
						UpperCAmelCase					=			nums.copy()
						copy_nums.sort()
						return copy_nums[-1] < sum(copy_nums[:-1]						)


if __name__ == "__main__":
				import doctest

				doctest.testmod()










"""simple docstring"""


# Copyright 2022 The HuggingFace Team and The OpenBMB 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_tokenizers_available, is_torch_available


snake_case_    					=	{
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
				if not is_torch_available():
								raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
				pass
else:
				snake_case_    					=	[
				    """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
				    """CpmAntForCausalLM""",
				    """CpmAntModel""",
				    """CpmAntPreTrainedModel""",
				]


if TYPE_CHECKING:
				from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
				from .tokenization_cpmant import CpmAntTokenizer

				try:
								if not is_torch_available():
												raise OptionalDependencyNotAvailable()
				except OptionalDependencyNotAvailable:
								pass
				else:
								from .modeling_cpmant import (
								    CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
								    CpmAntForCausalLM,
								    CpmAntModel,
								    CpmAntPreTrainedModel,
								)


else:
				import sys

				snake_case_    					=	_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)





