





# 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,
)


_UpperCamelCase    :							Union[str, Any]      =       {
    """configuration_convnextv2""": [
        """CONVNEXTV2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """ConvNextV2Config""",
    ]
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    _UpperCamelCase    :							Optional[Any]      =       [
        """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

    _UpperCamelCase    :							Optional[int]      =       _LazyModule(__name__, globals()["""__file__"""], _import_structure)


from itertools import combinations, product


def 							lowerCAmelCase__    (       a__  ,			a__  ,			a__  ,			a__      )	->bool:




  '''simple docstring'''

  if xa == ya == 0 or xa == ya == 0:
    return False
  _UpperCamelCase				=  xa * xa + ya * ya
  _UpperCamelCase				=  xa * xa + ya * ya
  _UpperCamelCase				=  (xa - xa) * (xa - xa) + (ya - ya) * (ya - ya)
  return (
      a_square + b_square == c_square
      or a_square + c_square == b_square
      or b_square + c_square == a_square
  )


def 							lowerCAmelCase__    (       a__ = 50      )	->int:




  '''simple docstring'''

  return sum(
      1
      for pta, pta in combinations(product(range(limit + 1      )  ,			repeat=2      )  ,			2      )
      if is_right(*a__  ,			*a__      )      )


if __name__ == "__main__":
   print(F"{solution() = }")




