Apply suggestions from code review

Co-authored-by: Aarni Koskela <akx@iki.fi>

modules/sd_hijack_optimizations.py

@@ -19,10 +19,10 @@ diffusionmodules_model_AttnBlock_forward = ldm.modules.diffusionmodules.model.At
 
 
 class SdOptimization:
-    def __init__(self, name, label=None, cmd_opt=None):
-        self.name = name
-        self.label = label
-        self.cmd_opt = cmd_opt
+    name: str = None
+    label: str | None = None
+    cmd_opt: str | None = None
+    priority: int = 0
 
     def title(self):
         if self.label is None:
@@ -33,9 +33,6 @@ class SdOptimization:
     def is_available(self):
         return True
 
-    def priority(self):
-        return 0
-
     def apply(self):
         pass
 
@@ -45,41 +42,37 @@ class SdOptimization:
 
 
 class SdOptimizationXformers(SdOptimization):
-    def __init__(self):
-        super().__init__("xformers", cmd_opt="xformers")
+    name = "xformers"
+    cmd_opt = "xformers"
+    priority = 100
 
     def is_available(self):
         return shared.cmd_opts.force_enable_xformers or (shared.xformers_available and torch.version.cuda and (6, 0) <= torch.cuda.get_device_capability(shared.device) <= (9, 0))
 
-    def priority(self):
-        return 100
-
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = xformers_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = xformers_attnblock_forward
 
 
 class SdOptimizationSdpNoMem(SdOptimization):
-    def __init__(self, name="sdp-no-mem", label="scaled dot product without memory efficient attention", cmd_opt="opt_sdp_no_mem_attention"):
-        super().__init__(name, label, cmd_opt)
+    name = "sdp-no-mem"
+    label = "scaled dot product without memory efficient attention"
+    cmd_opt = "opt_sdp_no_mem_attention"
+    priority = 90
 
     def is_available(self):
         return hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention)
 
-    def priority(self):
-        return 90
-
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = scaled_dot_product_no_mem_attention_forward
         ldm.modules.diffusionmodules.model.AttnBlock.forward = sdp_no_mem_attnblock_forward
 
 
 class SdOptimizationSdp(SdOptimizationSdpNoMem):
-    def __init__(self):
-        super().__init__("sdp", "scaled dot product", cmd_opt="opt_sdp_attention")
-
-    def priority(self):
-        return 80
+    name = "sdp"
+    label = "scaled dot product"
+    cmd_opt = "opt_sdp_attention"
+    priority = 80
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = scaled_dot_product_attention_forward
@@ -87,11 +80,9 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem):
 
 
 class SdOptimizationSubQuad(SdOptimization):
-    def __init__(self):
-        super().__init__("sub-quadratic", cmd_opt="opt_sub_quad_attention")
-
-    def priority(self):
-        return 10
+    name = "sub-quadratic"
+    cmd_opt = "opt_sub_quad_attention"
+    priority = 10
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = sub_quad_attention_forward
@@ -99,20 +90,21 @@ class SdOptimizationSubQuad(SdOptimization):
 
 
 class SdOptimizationV1(SdOptimization):
-    def __init__(self):
-        super().__init__("V1", "original v1", cmd_opt="opt_split_attention_v1")
+    name = "V1"
+    label = "original v1"
+    cmd_opt = "opt_split_attention_v1"
+    priority = 10
 
-    def priority(self):
-        return 10
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward_v1
 
 
 class SdOptimizationInvokeAI(SdOptimization):
-    def __init__(self):
-        super().__init__("InvokeAI", cmd_opt="opt_split_attention_invokeai")
+    name = "InvokeAI"
+    cmd_opt = "opt_split_attention_invokeai"
 
+    @property
     def priority(self):
         return 1000 if not torch.cuda.is_available() else 10
 
@@ -121,11 +113,9 @@ class SdOptimizationInvokeAI(SdOptimization):
 
 
 class SdOptimizationDoggettx(SdOptimization):
-    def __init__(self):
-        super().__init__("Doggettx", cmd_opt="opt_split_attention")
-
-    def priority(self):
-        return 20
+    name = "Doggettx"
+    cmd_opt = "opt_split_attention"
+    priority = 20
 
     def apply(self):
         ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward