revert default cross attention optimization to Doggettx

make --disable-opt-split-attention command line option work again

3 files changed, 6 insertions, 4 deletions

diff --git a/modules/cmd_args.py b/modules/cmd_args.py
index 3eeb84d5..71a21b1a 100644
--- a/modules/cmd_args.py
+++ b/modules/cmd_args.py
@@ -62,7 +62,7 @@ parser.add_argument("--opt-split-attention-invokeai", action='store_true', help=
 parser.add_argument("--opt-split-attention-v1", action='store_true', help="prefer older version of split attention optimization for automatic choice of optimization")

 parser.add_argument("--opt-sdp-attention", action='store_true', help="prefer scaled dot product cross-attention layer optimization for automatic choice of optimization; requires PyTorch 2.*")

 parser.add_argument("--opt-sdp-no-mem-attention", action='store_true', help="prefer scaled dot product cross-attention layer optimization without memory efficient attention for automatic choice of optimization, makes image generation deterministic; requires PyTorch 2.*")

-parser.add_argument("--disable-opt-split-attention", action='store_true', help="does not do anything")

+parser.add_argument("--disable-opt-split-attention", action='store_true', help="prefer no cross-attention layer optimization for automatic choice of optimization")

 parser.add_argument("--disable-nan-check", action='store_true', help="do not check if produced images/latent spaces have nans; useful for running without a checkpoint in CI")

 parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower)

 parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")

diff --git a/modules/sd_hijack.py b/modules/sd_hijack.py
index f93df0a6..221771da 100644
--- a/modules/sd_hijack.py
+++ b/modules/sd_hijack.py
@@ -68,6 +68,8 @@ def apply_optimizations():
 

     if selection == "None":

         matching_optimizer = None

+    elif selection == "Automatic" and shared.cmd_opts.disable_opt_split_attention:

+        matching_optimizer = None

     elif matching_optimizer is None:

         matching_optimizer = optimizers[0]

 

diff --git a/modules/sd_hijack_optimizations.py b/modules/sd_hijack_optimizations.py
index 2ec0b049..80e48a42 100644
--- a/modules/sd_hijack_optimizations.py
+++ b/modules/sd_hijack_optimizations.py
@@ -59,7 +59,7 @@ class SdOptimizationSdpNoMem(SdOptimization):
     name = "sdp-no-mem"

     label = "scaled dot product without memory efficient attention"

     cmd_opt = "opt_sdp_no_mem_attention"

-    priority = 90

+    priority = 80

 

     def is_available(self):

         return hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention)

@@ -73,7 +73,7 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem):
     name = "sdp"

     label = "scaled dot product"

     cmd_opt = "opt_sdp_attention"

-    priority = 80

+    priority = 70

 

     def apply(self):

         ldm.modules.attention.CrossAttention.forward = scaled_dot_product_attention_forward

@@ -116,7 +116,7 @@ class SdOptimizationInvokeAI(SdOptimization):
 class SdOptimizationDoggettx(SdOptimization):

     name = "Doggettx"

     cmd_opt = "opt_split_attention"

-    priority = 20

+    priority = 90

 

     def apply(self):

         ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward