Function Truncated_initializer

model/meta_graph.py:5–13

(m)

import numpy as np
from torch.nn import functional as F
def Truncated_initializer(m):
    # sample u1:
    size = m.size()
    u1 = torch.rand(size)*(1-np.exp(-2)) + np.exp(-2)
    # sample u2:
    u2 = torch.rand(size)
    # sample the truncated gaussian ~TN(0,1,[-2,2]):
    z = torch.sqrt(-2*torch.log(u1)) * torch.cos(2*np.pi*u2)
    m.data = z


class GraphConvolution(nn.Module):