本文整理匯總了Python中nervanagpu.NervanaGPU.zeros方法的典型用法代碼示例。如果您正苦於以下問題：Python NervanaGPU.zeros方法的具體用法？Python NervanaGPU.zeros怎麽用？Python NervanaGPU.zeros使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類nervanagpu.NervanaGPU的用法示例。
在下文中一共展示了NervanaGPU.zeros方法的2個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: GPU
# 需要導入模塊: from nervanagpu import NervanaGPU [as 別名]
# 或者: from nervanagpu.NervanaGPU import zeros [as 別名]
#.........這裏部分代碼省略.........
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示例2: slicable
# 需要導入模塊: from nervanagpu import NervanaGPU [as 別名]
# 或者: from nervanagpu.NervanaGPU import zeros [as 別名]
# 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 = []