def reset_parameters(self):
self.psi_1.reset_parameters()
for psi in self.psi_stack:
psi.reset_parameters()
reset(self.mlp)
self.sum_weights = Parameter(torch.ones(self.num_psi + 1))
def reset_parameters(self):
reset(self.mlp)
if self.msg_norm is not None:
self.msg_norm.reset_parameters()
if self.t and isinstance(self.t, Tensor):
self.t.data.fill_(self.initial_t)
if self.p and isinstance(self.p, Tensor):
self.p.data.fill_(self.initial_p)
def reset_parameters(self):
reset(self.msg_up_nn)
reset(self.msg_boundaries_nn)
reset(self.update_up_nn)
reset(self.update_boundaries_nn)
reset(self.combine_nn)
self.eps1.data.fill_(self.initial_eps)
self.eps2.data.fill_(self.initial_eps)
def reset_parameters(self):
if self.edge_dim is not None:
self.edge_encoder.reset_parameters()
for nn in self.pre_nns:
reset(nn)
for nn in self.post_nns:
reset(nn)
self.lin.reset_parameters()
def test_reset():
nn = Lin(16, 16)
w = nn.weight.clone()
reset(nn)
assert not nn.weight.tolist() == w.tolist()
nn = Seq(Lin(16, 16), ReLU(), Lin(16, 16))
w_1, w_2 = nn[0].weight.clone(), nn[2].weight.clone()
reset(nn)
assert not nn[0].weight.tolist() == w_1.tolist()
assert not nn[2].weight.tolist() == w_2.tolist()
def reset_parameters(self):
reset(self.k_lin)
reset(self.q_lin)
reset(self.v_lin)
reset(self.a_lin)
ones(self.skip)
ones(self.p_rel)
glorot(self.a_rel)
glorot(self.m_rel)
def reset_parameters(self):
reset(self.nn)
if self.root_weight:
self.lin.reset_parameters()
zeros(self.bias)
def reset_parameters(self):
reset(self.edge_encoder)
reset(self.mlp)
self.eps.data.fill_(self.initial_eps)
def reset_parameters(self):
reset(self.edge_encoder)
reset(self.mlp)
def reset_parameters(self):
reset(self.fc1)
reset(self.fc3)
reset(self.fc4)
def reset_parameters(self):
reset(self.scorer)
reset(self.encoder)
reset(self.pool)
def reset_parameters(self):
reset(self.gate_nn)
reset(self.nn)
def reset_parameters(self):
reset(self.layer)
def reset_parameters(self):
reset(self.layer1)
reset(self.layerg)
reset(self.layer2)
reset(self.layerg2)
reset(self.layer3)
reset(self.layerg3)
reset(self.layer4)
reset(self.layer5)
def reset_parameters(self):
reset(self.mlp1)
reset(self.mlp2)
reset(self.conv)
def reset_parameters(self):
reset(self.nn)
uniform(self.in_channels, self.root)
uniform(self.in_channels, self.bias)
def reset_parameters(self):
reset(self.attn)
def reset_parameters(self):
for psi in self.psi1_stack:
psi.reset_parameters()
# self.psi_2.reset_parameters()
reset(self.mlp)
def reset_parameters(self):
reset(self.edge_nn)
reset(self.message_lstm)
if self.root:
reset(self.root)
zeros(self.bias)
def reset_parameters(self):
self.lamb.data.fill_(self.initial_lamb)
reset(self.optimizer)
reset(self.potential)
def reset_parameters(self):
reset(self.nn1)
self.eps.data.fill_(self.initial_eps)
def reset_parameters(self):
self.psi_1.reset_parameters()
self.psi_2.reset_parameters()
reset(self.mlp)
def reset_parameters(self):
reset(self.conv)
def __init__(self, encoder, discriminator, decoder=None):
super(ARGA, self).__init__(encoder, decoder)
self.discriminator = discriminator
reset(self.discriminator)
def reset_parameters(self):
for conv in self.convs.values():
reset(conv)
def reset_parameters(self):
super(ARGA, self).reset_parameters()
reset(self.discriminator)
def reset_parameters(self):
reset(self.local_nn)
reset(self.global_nn)
def reset_parameters(self):
reset(self.encoder)
reset(self.decoder)
def reset_parameters(self):
reset(self.nn)
def reset_parameters(self):
reset(self.proj)
glorot(self.lin_src)
glorot(self.lin_dst)
self.k_lin.reset_parameters()
glorot(self.q)