revert default cross attention optimization to Doggettx
make --disable-opt-split-attention command line option work again
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@ -62,7 +62,7 @@ parser.add_argument("--opt-split-attention-invokeai", action='store_true', help=
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parser.add_argument("--opt-split-attention-v1", action='store_true', help="prefer older version of split attention optimization for automatic choice of optimization")
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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.*")
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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.*")
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parser.add_argument("--disable-opt-split-attention", action='store_true', help="does not do anything")
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parser.add_argument("--disable-opt-split-attention", action='store_true', help="prefer no cross-attention layer optimization for automatic choice of optimization")
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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")
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parser.add_argument("--use-cpu", nargs='+', help="use CPU as torch device for specified modules", default=[], type=str.lower)
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parser.add_argument("--listen", action='store_true', help="launch gradio with 0.0.0.0 as server name, allowing to respond to network requests")
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@ -68,6 +68,8 @@ def apply_optimizations():
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if selection == "None":
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matching_optimizer = None
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elif selection == "Automatic" and shared.cmd_opts.disable_opt_split_attention:
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matching_optimizer = None
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elif matching_optimizer is None:
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matching_optimizer = optimizers[0]
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@ -59,7 +59,7 @@ class SdOptimizationSdpNoMem(SdOptimization):
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name = "sdp-no-mem"
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label = "scaled dot product without memory efficient attention"
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cmd_opt = "opt_sdp_no_mem_attention"
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priority = 90
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priority = 80
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def is_available(self):
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return hasattr(torch.nn.functional, "scaled_dot_product_attention") and callable(torch.nn.functional.scaled_dot_product_attention)
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@ -73,7 +73,7 @@ class SdOptimizationSdp(SdOptimizationSdpNoMem):
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name = "sdp"
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label = "scaled dot product"
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cmd_opt = "opt_sdp_attention"
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priority = 80
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priority = 70
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def apply(self):
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ldm.modules.attention.CrossAttention.forward = scaled_dot_product_attention_forward
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@ -116,7 +116,7 @@ class SdOptimizationInvokeAI(SdOptimization):
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class SdOptimizationDoggettx(SdOptimization):
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name = "Doggettx"
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cmd_opt = "opt_split_attention"
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priority = 20
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priority = 90
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def apply(self):
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ldm.modules.attention.CrossAttention.forward = split_cross_attention_forward
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