Пример #1
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    def __neg__(self):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(_neg, self, None)
Пример #2
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    def __pos__(self):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.abs, self, None)
Пример #3
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    def __xor__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.bitwise_xor, self, other)
Пример #4
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    def __inv__(self):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.bitwise_not, self, None)
Пример #5
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    def __truediv__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.true_divide, self, other)
Пример #6
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    def __sub__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.sub, self, other)
Пример #7
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    def __rpow__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.pow, other, self)
Пример #8
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    def __rfloordiv__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        return CompositionalMetric(torch.floor_divide, other, self)
Пример #9
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    def __rand__(self, other: Any):
        from pytorch_lightning.metrics.compositional import CompositionalMetric

        # swap them since bitwise_and only supports that way and it's commutative
        return CompositionalMetric(torch.bitwise_and, self, other)