diff --git a/models/Model_Quick96/Model.py b/models/Model_Quick96/Model.py
index b9a94c3..6b66041 100644
--- a/models/Model_Quick96/Model.py
+++ b/models/Model_Quick96/Model.py
@@ -141,8 +141,9 @@ class Quick96Model(ModelBase):
                     self.CA_conv_weights_list += [layer.weights[0]] #- is Conv2D kernel_weights
 
         if self.is_training_mode:
-            self.src_dst_opt      = RMSprop(lr=2e-4, lr_dropout=0.3)
-            self.src_dst_mask_opt = RMSprop(lr=2e-4, lr_dropout=0.3)
+            lr_dropout = 0.3 if nnlib.device.backend != 'plaidML' else 0.0
+            self.src_dst_opt      = RMSprop(lr=2e-4, lr_dropout=lr_dropout)
+            self.src_dst_mask_opt = RMSprop(lr=2e-4, lr_dropout=lr_dropout)
                 
             target_src_masked = self.model.target_src*self.model.target_srcm
             target_dst_masked = self.model.target_dst*self.model.target_dstm
diff --git a/models/Model_SAEHD/Model.py b/models/Model_SAEHD/Model.py
index cc9217c..180b2a1 100644
--- a/models/Model_SAEHD/Model.py
+++ b/models/Model_SAEHD/Model.py
@@ -65,9 +65,12 @@ class SAEHDModel(ModelBase):
         default_bg_style_power = self.options.get('bg_style_power', 0.0)
 
         if is_first_run or ask_override:
-            default_lr_dropout = self.options.get('lr_dropout', False)
-            self.options['lr_dropout'] = io.input_bool ( f"Use learning rate dropout? (y/n, ?:help skip:{yn_str[default_lr_dropout]} ) : ", default_lr_dropout, help_message="When the face is trained enough, you can enable this option to get extra sharpness for less amount of iterations.")
-
+            if nnlib.device.backend != 'plaidML':
+                default_lr_dropout = self.options.get('lr_dropout', False)
+                self.options['lr_dropout'] = io.input_bool ( f"Use learning rate dropout? (y/n, ?:help skip:{yn_str[default_lr_dropout]} ) : ", default_lr_dropout, help_message="When the face is trained enough, you can enable this option to get extra sharpness for less amount of iterations.")
+            else:
+                self.options['lr_dropout'] = False
+                
             default_random_warp = self.options.get('random_warp', True)
             self.options['random_warp'] = io.input_bool (f"Enable random warp of samples? ( y/n, ?:help skip:{yn_str[default_random_warp]}) : ", default_random_warp, help_message="Random warp is required to generalize facial expressions of both faces. When the face is trained enough, you can disable it to get extra sharpness for less amount of iterations.")