snapshot...

modules/deeplearning/icing.py

@@ -368,11 +368,11 @@ class IcingIntensityNN:
 
         fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_5', doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_4', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_6', doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_5', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_7', doBatchNorm=True)
 
-        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_5', doBatchNorm=True)
+        fc = build_residual_block(fc, drop_rate, fac*n_hidden, activation, 'Residual_Block_8', doBatchNorm=True)
 
         fc = tf.keras.layers.Dense(n_hidden, activation=activation)(fc)
         fc = tf.keras.layers.BatchNormalization()(fc)