Update Fitting.py

Author: GeiduanLiu

source/train/Fitting.py

@@ -219,9 +219,9 @@ def build (self,
                     layer = tf.concat([layer, ext_aparam], axis = 1)
                 for ii in range(0,len(self.n_neuron)) :
                     if ii >= 1 and self.n_neuron[ii] == self.n_neuron[ii-1] :
-                        layer+= one_layer(layer, self.n_neuron[ii], name='layer_'+str(ii)+'_type_'+str(type_i)+suffix, reuse=True, seed = self.seed, use_timestep = self.resnet_dt, precision = self.fitting_precision)
+                        layer+= one_layer(layer, self.n_neuron[ii], name='layer_'+str(ii)+'_type_'+str(type_i)+suffix, reuse=True, seed = self.seed, use_timestep = self.resnet_dt, activation_fn = self.fitting_activation_fn, precision = self.fitting_precision)
                     else :
-                        layer = one_layer(layer, self.n_neuron[ii], name='layer_'+str(ii)+'_type_'+str(type_i)+suffix, reuse=True, seed = self.seed, precision = self.fitting_precision)
+                        layer = one_layer(layer, self.n_neuron[ii], name='layer_'+str(ii)+'_type_'+str(type_i)+suffix, reuse=True, seed = self.seed, activation_fn = self.fitting_activation_fn, precision = self.fitting_precision)
                 zero_layer = one_layer(layer, 1, activation_fn = None, bavg = type_bias_ae, name='final_layer_type_'+str(type_i)+suffix, reuse=True, seed = self.seed, precision = self.fitting_precision)
                 final_layer += self.atom_ener[type_i] - zero_layer