Fix LoRA config display issue

bmaltais · Jan 6, 2024 · f579563 · f579563
1 parent 1992e19
commit f579563
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Showing 3 changed files with 73 additions and 17 deletions.
diff --git a/.release b/.release
@@ -1 +1 @@
-v22.4.1
+v22.5.0
diff --git a/README.md b/README.md
@@ -503,6 +503,10 @@ masterpiece, best quality, 1boy, in business suit, standing at street, looking b
 
 
 ## Change History
+* 2024/01/10 (v22.5.0)
+- Merged sd-scripts updates
+- Fix LoRA config display after load that would sometime hide some of the feilds
+
 * 2024/01/02 (v22.4.1)
 - Minor bug fixed and enhancements.
 

diff --git a/lora_gui.py b/lora_gui.py
@@ -125,15 +125,22 @@ def save_configuration(
     caption_dropout_rate,
     optimizer,
     optimizer_args,
-    lr_scheduler_args,max_grad_norm,
+    lr_scheduler_args,
+    max_grad_norm,
     noise_offset_type,
     noise_offset,
     adaptive_noise_scale,
     multires_noise_iterations,
     multires_noise_discount,
     LoRA_type,
     factor,
-    use_cp,use_tucker,use_scalar,rank_dropout_scale,constrain,rescaled,train_norm,
+    use_cp,
+    use_tucker,
+    use_scalar,
+    rank_dropout_scale,
+    constrain,
+    rescaled,
+    train_norm,
     decompose_both,
     train_on_input,
     conv_dim,
@@ -280,15 +287,22 @@ def open_configuration(
     caption_dropout_rate,
     optimizer,
     optimizer_args,
-    lr_scheduler_args,max_grad_norm,
+    lr_scheduler_args,
+    max_grad_norm,
     noise_offset_type,
     noise_offset,
     adaptive_noise_scale,
     multires_noise_iterations,
     multires_noise_discount,
     LoRA_type,
     factor,
-    use_cp,use_tucker,use_scalar,rank_dropout_scale,constrain,rescaled,train_norm,
+    use_cp,
+    use_tucker,
+    use_scalar,
+    rank_dropout_scale,
+    constrain,
+    rescaled,
+    train_norm,
     decompose_both,
     train_on_input,
     conv_dim,
@@ -378,7 +392,18 @@ def open_configuration(
             values.append(json_value if json_value is not None else value)
 
     # This next section is about making the LoCon parameters visible if LoRA_type = 'Standard'
-    if my_data.get("LoRA_type", "Standard") == "LoCon":
+    if my_data.get("LoRA_type", "Standard") in {
+        "LoCon",
+        "Kohya DyLoRA",
+        "Kohya LoCon",
+        "LoRA-FA",
+        "LyCORIS/Diag-OFT",
+        "LyCORIS/DyLoRA",
+        "LyCORIS/LoHa",
+        "LyCORIS/LoKr",
+        "LyCORIS/LoCon",
+        "LyCORIS/GLoRA",
+    }:
         values.append(gr.Row.update(visible=True))
     else:
         values.append(gr.Row.update(visible=False))
@@ -455,15 +480,22 @@ def train_model(
     caption_dropout_rate,
     optimizer,
     optimizer_args,
-    lr_scheduler_args,max_grad_norm,
+    lr_scheduler_args,
+    max_grad_norm,
     noise_offset_type,
     noise_offset,
     adaptive_noise_scale,
     multires_noise_iterations,
     multires_noise_discount,
     LoRA_type,
     factor,
-    use_cp,use_tucker,use_scalar,rank_dropout_scale,constrain,rescaled,train_norm,
+    use_cp,
+    use_tucker,
+    use_scalar,
+    rank_dropout_scale,
+    constrain,
+    rescaled,
+    train_norm,
     decompose_both,
     train_on_input,
     conv_dim,
@@ -825,9 +857,7 @@ def train_model(
             )
             return
         run_cmd += f" --network_module=lycoris.kohya"
-        run_cmd += (
-            f' --network_args "preset={LyCORIS_preset}" "rank_dropout={rank_dropout}" "module_dropout={module_dropout}" "use_tucker={use_tucker}" "use_scalar={use_scalar}" "rank_dropout_scale={rank_dropout_scale}" "algo=full" "train_norm={train_norm}"'
-        )
+        run_cmd += f' --network_args "preset={LyCORIS_preset}" "rank_dropout={rank_dropout}" "module_dropout={module_dropout}" "use_tucker={use_tucker}" "use_scalar={use_scalar}" "rank_dropout_scale={rank_dropout_scale}" "algo=full" "train_norm={train_norm}"'
         # This is a hack to fix a train_network LoHA logic issue
         if not network_dropout > 0.0:
             run_cmd += f' --network_dropout="{network_dropout}"'
@@ -1504,18 +1534,28 @@ def update_LoRA_settings(
                                 "gr_type": gr.Slider,
                                 "update_params": {
                                     "maximum": 100000
-                                    if LoRA_type in {"LyCORIS/LoHa", "LyCORIS/LoKr", "LyCORIS/Diag-OFT"}
+                                    if LoRA_type
+                                    in {
+                                        "LyCORIS/LoHa",
+                                        "LyCORIS/LoKr",
+                                        "LyCORIS/Diag-OFT",
+                                    }
                                     else 512,
-                                    "value": 512, # if conv_dim > 512 else conv_dim,
+                                    "value": conv_dim,  # if conv_dim > 512 else conv_dim,
                                 },
                             },
                             "network_dim": {
                                 "gr_type": gr.Slider,
                                 "update_params": {
                                     "maximum": 100000
-                                    if LoRA_type in {"LyCORIS/LoHa", "LyCORIS/LoKr", "LyCORIS/Diag-OFT"}
+                                    if LoRA_type
+                                    in {
+                                        "LyCORIS/LoHa",
+                                        "LyCORIS/LoKr",
+                                        "LyCORIS/Diag-OFT",
+                                    }
                                     else 512,
-                                    "value": 512, # if network_dim > 512 else network_dim,
+                                    "value": network_dim,  # if network_dim > 512 else network_dim,
                                 },
                             },
                             "use_cp": {
@@ -1790,7 +1830,13 @@ def update_LoRA_settings(
                     factor,
                     conv_dim,
                     network_dim,
-                    use_cp,use_tucker,use_scalar,rank_dropout_scale,constrain,rescaled,train_norm,
+                    use_cp,
+                    use_tucker,
+                    use_scalar,
+                    rank_dropout_scale,
+                    constrain,
+                    rescaled,
+                    train_norm,
                     decompose_both,
                     train_on_input,
                     scale_weight_norms,
@@ -1913,7 +1959,13 @@ def update_LoRA_settings(
             advanced_training.multires_noise_discount,
             LoRA_type,
             factor,
-            use_cp,use_tucker,use_scalar,rank_dropout_scale,constrain,rescaled,train_norm,
+            use_cp,
+            use_tucker,
+            use_scalar,
+            rank_dropout_scale,
+            constrain,
+            rescaled,
+            train_norm,
             decompose_both,
             train_on_input,
             conv_dim,