Support disabling conv via conv dim = 0

Author: 67372a

networks/dylora.py

@@ -217,11 +217,15 @@ def create_network(
     unit = kwargs.get("unit", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        assert conv_dim == network_dim, "conv_dim must be same as network_dim"
-        if conv_alpha is None:
-            conv_alpha = 1.0
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
         else:
-            conv_alpha = float(conv_alpha)
+            assert conv_dim == network_dim, "conv_dim must be same as network_dim"
+            if conv_alpha is None:
+                conv_alpha = 1.0
+            else:
+                conv_alpha = float(conv_alpha)
 
     if unit is not None:
         unit = int(unit)

networks/loha.py

@@ -455,7 +455,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_lora_dim is not None:
         conv_lora_dim = int(conv_lora_dim)
-        if conv_alpha is None:
+        if conv_lora_dim == 0:
+            conv_lora_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/lokr.py

@@ -449,7 +449,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_lora_dim is not None:
         conv_lora_dim = int(conv_lora_dim)
-        if conv_alpha is None:
+        if conv_lora_dim == 0:
+            conv_lora_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/lora.py

@@ -458,7 +458,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)
@@ -958,7 +961,7 @@ def __init__(
             logger.info(
                 f"neuron dropout: p={self.dropout}, rank dropout: p={self.rank_dropout}, module dropout: p={self.module_dropout}"
             )
-            if self.conv_lora_dim is not None:
+            if self.conv_lora_dim is not None and self.conv_lora_dim != 0:
                 logger.info(
                     f"apply LoRA to Conv2d with kernel size (3,3). dim (rank): {self.conv_lora_dim}, alpha: {self.conv_alpha}"
                 )
@@ -1061,7 +1064,7 @@ def create_modules(
 
         # extend U-Net target modules if conv2d 3x3 is enabled, or load from weights
         target_modules = LoRANetwork.UNET_TARGET_REPLACE_MODULE
-        if modules_dim is not None or self.conv_lora_dim is not None or conv_block_dims is not None:
+        if modules_dim is not None or (self.conv_lora_dim is not None and self.conv_lora_dim != 0) or conv_block_dims is not None:
             target_modules += LoRANetwork.UNET_TARGET_REPLACE_MODULE_CONV2D_3X3
 
         self.unet_loras, skipped_un = create_modules(True, None, unet, target_modules)

networks/lora_fa.py

@@ -463,7 +463,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)
@@ -834,7 +837,7 @@ def __init__(
         else:
             logger.info(f"create LoRA network. base dim (rank): {lora_dim}, alpha: {alpha}")
             logger.info(f"neuron dropout: p={self.dropout}, rank dropout: p={self.rank_dropout}, module dropout: p={self.module_dropout}")
-            if self.conv_lora_dim is not None:
+            if self.conv_lora_dim is not None and self.conv_lora_dim != 0:
                 logger.info(f"apply LoRA to Conv2d with kernel size (3,3). dim (rank): {self.conv_lora_dim}, alpha: {self.conv_alpha}")
 
         # create module instances
@@ -934,7 +937,7 @@ def create_modules(
 
         # extend U-Net target modules if conv2d 3x3 is enabled, or load from weights
         target_modules = LoRANetwork.UNET_TARGET_REPLACE_MODULE
-        if modules_dim is not None or self.conv_lora_dim is not None or conv_block_dims is not None:
+        if modules_dim is not None or (self.conv_lora_dim is not None and self.conv_lora_dim != 0) or conv_block_dims is not None:
             target_modules += LoRANetwork.UNET_TARGET_REPLACE_MODULE_CONV2D_3X3
 
         self.unet_loras, skipped_un = create_modules(True, None, unet, target_modules)

networks/lora_flux.py

@@ -481,7 +481,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/lora_hunyuan_image.py

@@ -55,7 +55,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/lora_lumina.py

@@ -334,7 +334,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/lora_sd3.py

@@ -50,7 +50,10 @@ def create_network(
     conv_alpha = kwargs.get("conv_alpha", None)
     if conv_dim is not None:
         conv_dim = int(conv_dim)
-        if conv_alpha is None:
+        if conv_dim == 0:
+            conv_dim = None
+            conv_alpha = None
+        elif conv_alpha is None:
             conv_alpha = 1.0
         else:
             conv_alpha = float(conv_alpha)

networks/network_base.py

@@ -261,7 +261,7 @@ def create_modules(
 
         # Create modules for UNet/DiT
         target_modules = list(arch_config.unet_target_modules)
-        if modules_dim is not None or conv_lora_dim is not None:
+        if modules_dim is not None or (conv_lora_dim is not None and conv_lora_dim != 0):
             target_modules.extend(arch_config.unet_conv_target_modules)
         if train_llm_adapter and arch_config.adapter_target_modules:
             target_modules.extend(arch_config.adapter_target_modules)