filter norm

filter norm.py

random_direction1 = get_random_weights(copy_of_the_weights)
random_direction2 = get_random_weights(copy_of_the_weights)

for d1,d2,w in zip(random_direction1,random_direction2,copy_of_the_weights):
    
    w_norm  = w.view((w.shape[0],-1))  .norm(dim=(1),keepdim=True)[:,:,None,None]
    d_norm1 = d1.view((d1.shape[0],-1)).norm(dim=(1),keepdim=True)[:,:,None,None]
    d_norm2 = d2.view((d2.shape[0],-1)).norm(dim=(1),keepdim=True)[:,:,None,None]
    
    d1.data = d1.cuda() * (w_norm/(d_norm1.cuda()+1e-10))
    d2.data = d2.cuda() * (w_norm/(d_norm2.cuda()+1e-10))