use direct amplitude

tetraku/tetraku/networks/naqs/__init__.py

@@ -200,7 +200,7 @@ def generate(self, batch_size, alpha=1):
         real_amplitude = amplitude_phase.exp()
         real_probability = (real_amplitude.conj() * real_amplitude).real
         x = torch.index_select(x, 1, self.ordering)
-        return x.reshape([x.size(0), self.L1, self.L2, self.orbit_num]), real_amplitude, real_probability, multiplicity
+        return x.reshape([x.size(0), self.L1, self.L2, self.orbit_num]), real_amplitude, torch.ones_like(real_probability), torch.ones_like(multiplicity)
 
 
 def network(state, spin_up, spin_down, hidden_size, ordering=+1):