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Python NervanaGPU.power方法代码示例

本文整理汇总了Python中nervanagpu.NervanaGPU.power方法的典型用法代码示例。如果您正苦于以下问题:Python NervanaGPU.power方法的具体用法?Python NervanaGPU.power怎么用?Python NervanaGPU.power使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在nervanagpu.NervanaGPU的用法示例。


在下文中一共展示了NervanaGPU.power方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。

示例1: GPU

# 需要导入模块: from nervanagpu import NervanaGPU [as 别名]
# 或者: from nervanagpu.NervanaGPU import power [as 别名]

#.........这里部分代码省略.........
            order (int): The order or p upon which the norm is calculated.
                         Valid values include:
                         None, inf, -inf, 0, 1, -1, 2, -2, ...
            axis (int): The axis along which to compute vector norms.
            out (GPUTensor): where to write the results to.  Must be
                             of the expected result shape.

        Returns:
            GPUTensor: p-norm of tsr along the specified axis.

        Raises:
            IndexError if invalid axis specified
            AttributeError if invalid order specified

        See Also:
            `numpy.linalg.norm`
        """
        if not isinstance(axis, int) or axis < 0 or axis >= len(tsr.shape):
            raise IndexError("invalid axis value: %s", axis)
        if not isinstance(order, (int, float)):
            raise AttributeError("invalid order value: %s", order)
        if out is None:
            raise AttributeError("No output tensor speficied", order)
        if order == float('Inf'):
            self.ng.max(self.fabs(tsr), axis, out)
        elif order == float('-Inf'):
            self.ng.min(self.fabs(tsr), axis, out)
        elif order == 0:
            tmp = self.zeros(tsr.shape)
            self.ng.not_equal(tsr, tmp, tmp)
            self.ng.sum(tmp, axis, out)
        else:
            tmp = self.empty(tsr.shape)
            self.ng.power(self.fabs(tsr), order, tmp)
            self.ng.sum(tmp, axis, out)
            self.ng.power(out, (1.0 / order), out)
        return out

    def mean(self, tsr, axes, out):
        """
        Calculates the arithmetic mean of the elements along the specified
        axes.

        Arguments:
            tsr (GPUTensor): Input tensor
            axes (int): Axis along which the reduction is performed. If axes
                        is None,  the tensor is flattened and reduced over
                        both dimensions.
            out (GPUTensor): Output tensor
        """
        if axes is None:
            sze = tsr.shape[0]*tsr.shape[1]
            self.ng.mean(tsr.reshape(sze, 1), axis=0, out=out)
        else:
            self.ng.mean(tsr, axis=axes, out=out)
        return out

    def min(self, tsr, axes, out):
        """
        Calculates the minimum of the elements along the specified
        axes.

        Arguments:
            tsr (GPUTensor): Input tensor
            axes (int): Axis along which the reduction is performed. If axes
                        is None,  the tensor is flattened and reduced over
开发者ID:neuroidss,项目名称:neon,代码行数:70,代码来源:gpu.py


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