DGCN/initialization_utils.py at master · CongWeilin/DGCN · GitHub

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import math

import torch


def uniform(size, tensor):
    if tensor is not None:
        bound = 1.0 / math.sqrt(size)
        tensor.data.uniform_(-bound, bound)


def kaiming_uniform(tensor, fan, a):
    if tensor is not None:
        bound = math.sqrt(6 / ((1 + a**2) * fan))
        tensor.data.uniform_(-bound, bound)


def glorot(tensor):
    if tensor is not None:
        stdv = math.sqrt(6.0 / (tensor.size(-2) + tensor.size(-1)))
        tensor.data.uniform_(-stdv, stdv)


def glorot_orthogonal(tensor, scale):
    if tensor is not None:
        torch.nn.init.orthogonal_(tensor.data)
        scale /= ((tensor.size(-2) + tensor.size(-1)) * tensor.var())
        tensor.data *= scale.sqrt()


def zeros(tensor):
    if tensor is not None:
        tensor.data.fill_(0)


def ones(tensor):
    if tensor is not None:
        tensor.data.fill_(1)