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Python NervanaGPU.zeros方法代码示例

本文整理汇总了Python中nervanagpu.NervanaGPU.zeros方法的典型用法代码示例。如果您正苦于以下问题:Python NervanaGPU.zeros方法的具体用法?Python NervanaGPU.zeros怎么用?Python NervanaGPU.zeros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.zeros方法的2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 zeros [as 别名]

#.........这里部分代码省略.........
            logger.error("GPUTensor requires mean to be specified.")
            raise ValueError("mean not specified")
        self.ng.mean(self.ng.square(tsr-mean),  axis=axes, out=out)
        return out

    def fabs(self, x, out):
        """
        Calculates absolute value of the elements in a tensor

        Arguments:
            x (GPUTensor): Input tensor
            out (GPUTensor): Output tensor

        Returns:
            GPUTensor: reference to out
        """
        self.ng.fabs(x, out=out)
        return out

    def sqrt(self, x, out):
        """
        Calculates square root of the elements in a tensor

        Arguments:
            x (GPUTensor): Input tensor
            out (GPUTensor): Output tensor

        Returns:
            GPUTensor: reference to out
        """
        self.ng.sqrt(x, out=out)
        return out

    def zeros(self, shape, dtype=default_dtype, persist_values=True):
        """
        Allocate a new GPUTensor and fill it with zeros.

        Arguments:
            shape (tupel): Shape of the desired GPUTensor
            dtype (dtype): Optional datatype
            persist_values (bool, optional): If set to True (the default), the
                                             values assigned to this Tensor
                                             will persist across multiple begin
                                             and end calls.  Setting to False
                                             may provide a performance increase
                                             if values do not need to be
                                             maintained across such calls

        Returns:
            GPUTensor: output
        """
        return self.ng.zeros(shape, dtype=dtype)

    def ones(self, shape, dtype=default_dtype, persist_values=True):
        """
        Allocate a new GPUTensor and fill it with ones.

        Arguments:
            shape (tupel): Shape of the desired GPUTensor
            dtype (dtype): Optional datatype
            persist_values (bool, optional): If set to True (the default), the
                                             values assigned to this Tensor
                                             will persist across multiple begin
                                             and end calls.  Setting to False
                                             may provide a performance increase
                                             if values do not need to be
开发者ID:YouVentures,项目名称:neon,代码行数:70,代码来源:gpu.py

示例2: slicable

# 需要导入模块: from nervanagpu import NervanaGPU [as 别名]
# 或者: from nervanagpu.NervanaGPU import zeros [as 别名]
# cpu input arrays
cpuI = np.random.uniform(0.0, 9.4, slicable(dimI,1)).astype(np.float16).astype(np.float32)

# zero pad the last row of cpu input for the sake of numpy
if pool.op == "max":
    cpuI[-1,:] = np.finfo(cpuI.dtype).min
else:
    cpuI[-1,:] = 0

# cpu output arrays
cpuO = np.empty(dimO, dtype=np.float32)
cpuB = np.zeros(slicable(dimI,1), dtype=np.float32)

# give gpu the input array without zero padding (not needed)
devI = ng.array(cpuI[:-1,:].reshape(dimI), dtype=dtype)
devO = ng.zeros(dimO, dtype=dtype)
devB = ng.empty(dimI, dtype=dtype)

ng.fprop_pool(pool, devI, devO, repeat=repeat)

ng.bprop_pool(pool, devI, devO, devB, repeat=repeat)

def pixel_indices(kj, mt, pr, qs):

    C       = pool.C
    J,T,R,S = pool.JTRS
    D,H,W = pool.DHW
    HW    = H*W
    DHW   = D*H*W
    imax  = C*D*H*W
    idx   = []
开发者ID:KayneWest,项目名称:nervanagpu,代码行数:33,代码来源:pool_test.py


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