diff --git a/models/Model_DEV_FUNIT/Model.py b/models/Model_DEV_FUNIT/Model.py
index a9cfb67..0382d18 100644
--- a/models/Model_DEV_FUNIT/Model.py
+++ b/models/Model_DEV_FUNIT/Model.py
@@ -33,6 +33,12 @@ class FUNITModel(ModelBase):
         else:
             self.options['face_type'] = self.options.get('face_type', default_face_type)
             
+        if (is_first_run or ask_override) and 'tensorflow' in self.device_config.backend:
+            def_optimizer_mode = self.options.get('optimizer_mode', 1)
+            self.options['optimizer_mode'] = io.input_int ("Optimizer mode? ( 1,2,3 ?:help skip:%d) : " % (def_optimizer_mode), def_optimizer_mode, help_message="1 - no changes. 2 - allows you to train x2 bigger network consuming RAM. 3 - allows you to train x3 bigger network consuming huge amount of RAM and slower, depends on CPU power.")
+        else:
+            self.options['optimizer_mode'] = self.options.get('optimizer_mode', 1)
+            
     #override
     def onInitialize(self, batch_size=-1, **in_options):
         exec(nnlib.code_import_all, locals(), globals())
@@ -58,7 +64,8 @@ class FUNITModel(ModelBase):
                             num_classes=person_id_max_count,
                             subpixel_decoder=True,
                             initialize_weights=self.is_first_run(),     
-                            is_training=self.is_training_mode                       
+                            is_training=self.is_training_mode,
+                            tf_cpu_mode=self.options['optimizer_mode']-1
                            )
                              
         if not self.is_first_run():
diff --git a/models/Model_TrueFace/Model.py b/models/Model_TrueFace/Model.py
index 883be09..82ff024 100644
--- a/models/Model_TrueFace/Model.py
+++ b/models/Model_TrueFace/Model.py
@@ -31,6 +31,12 @@ class TrueFaceModel(ModelBase):
             self.options['face_type'] = io.input_str ("Half or Full face? (h/f, ?:help skip:f) : ", default_face_type, ['h','f'], help_message="").lower()
         else:
             self.options['face_type'] = self.options.get('face_type', default_face_type)
+            
+        if (is_first_run or ask_override) and 'tensorflow' in self.device_config.backend:
+            def_optimizer_mode = self.options.get('optimizer_mode', 1)
+            self.options['optimizer_mode'] = io.input_int ("Optimizer mode? ( 1,2,3 ?:help skip:%d) : " % (def_optimizer_mode), def_optimizer_mode, help_message="1 - no changes. 2 - allows you to train x2 bigger network consuming RAM. 3 - allows you to train x3 bigger network consuming huge amount of RAM and slower, depends on CPU power.")
+        else:
+            self.options['optimizer_mode'] = self.options.get('optimizer_mode', 1)
 
     #override
     def onInitialize(self, batch_size=-1, **in_options):
@@ -55,7 +61,8 @@ class TrueFaceModel(ModelBase):
                             num_classes=2,
                             subpixel_decoder=True,
                             initialize_weights=self.is_first_run(),
-                            is_training=self.is_training_mode
+                            is_training=self.is_training_mode,
+                            tf_cpu_mode=self.options['optimizer_mode']-1
                            )
 
         if not self.is_first_run():
diff --git a/nnlib/FUNIT.py b/nnlib/FUNIT.py
index f6d72bc..dd02f6e 100644
--- a/nnlib/FUNIT.py
+++ b/nnlib/FUNIT.py
@@ -30,7 +30,8 @@ class FUNIT(object):
                         load_weights_locally=False,
                         weights_file_root=None,
 
-                        is_training=True
+                        is_training=True,
+                        tf_cpu_mode=0,
                         ):
         exec( nnlib.import_all(), locals(), globals() )
 
@@ -47,8 +48,8 @@ class FUNIT(object):
 
         self.dis = modelify ( FUNIT.DiscriminatorFlow(nf=dis_nf, n_res_blks=dis_res_blks, num_classes=num_classes) ) (Input(bgr_shape))
 
-        self.G_opt = RMSprop(lr=0.0001, decay=0.0001, tf_cpu_mode=2 if 'tensorflow' in nnlib.active_DeviceConfig.backend else 0)
-        self.D_opt = RMSprop(lr=0.0001, decay=0.0001, tf_cpu_mode=2 if 'tensorflow' in nnlib.active_DeviceConfig.backend else 0)
+        self.G_opt = RMSprop(lr=0.0001, decay=0.0001, tf_cpu_mode=tf_cpu_mode)
+        self.D_opt = RMSprop(lr=0.0001, decay=0.0001, tf_cpu_mode=tf_cpu_mode)
 
         xa = Input(bgr_shape, name="xa")
         la = Input(label_shape, dtype="int32", name="la")