SDXL support

1 files changed, 23 insertions, 4 deletions

diff --git a/modules/sd_models_xl.py b/modules/sd_models_xl.py
index d43b8868..e8e270c3 100644
--- a/modules/sd_models_xl.py
+++ b/modules/sd_models_xl.py
@@ -1,18 +1,30 @@
 from __future__ import annotations

 

+import sys

+

 import torch

 

 import sgm.models.diffusion

 import sgm.modules.diffusionmodules.denoiser_scaling

 import sgm.modules.diffusionmodules.discretizer

-from modules import devices

+from modules import devices, shared, prompt_parser

 

 

-def get_learned_conditioning(self: sgm.models.diffusion.DiffusionEngine, batch: list[str]):

+def get_learned_conditioning(self: sgm.models.diffusion.DiffusionEngine, batch: prompt_parser.SdConditioning | list[str]):

     for embedder in self.conditioner.embedders:

         embedder.ucg_rate = 0.0

 

-    c = self.conditioner({'txt': batch})

+    width = getattr(self, 'target_width', 1024)

+    height = getattr(self, 'target_height', 1024)

+

+    sdxl_conds = {

+        "txt": batch,

+        "original_size_as_tuple": torch.tensor([height, width]).repeat(len(batch), 1).to(devices.device, devices.dtype),

+        "crop_coords_top_left": torch.tensor([shared.opts.sdxl_crop_top, shared.opts.sdxl_crop_left]).repeat(len(batch), 1).to(devices.device, devices.dtype),

+        "target_size_as_tuple": torch.tensor([height, width]).repeat(len(batch), 1).to(devices.device, devices.dtype),

+    }

+

+    c = self.conditioner(sdxl_conds)

 

     return c

 

@@ -26,7 +38,7 @@ def extend_sdxl(model):
     model.model.diffusion_model.dtype = dtype

     model.model.conditioning_key = 'crossattn'

 

-    model.cond_stage_model = [x for x in model.conditioner.embedders if type(x).__name__ == 'FrozenOpenCLIPEmbedder'][0]

+    model.cond_stage_model = [x for x in model.conditioner.embedders if 'CLIPEmbedder' in type(x).__name__][0]

     model.cond_stage_key = model.cond_stage_model.input_key

 

     model.parameterization = "v" if isinstance(model.denoiser.scaling, sgm.modules.diffusionmodules.denoiser_scaling.VScaling) else "eps"

@@ -34,7 +46,14 @@ def extend_sdxl(model):
     discretization = sgm.modules.diffusionmodules.discretizer.LegacyDDPMDiscretization()

     model.alphas_cumprod = torch.asarray(discretization.alphas_cumprod, device=devices.device, dtype=dtype)

 

+    model.is_xl = True

+

 

 sgm.models.diffusion.DiffusionEngine.get_learned_conditioning = get_learned_conditioning

 sgm.models.diffusion.DiffusionEngine.apply_model = apply_model

 

+sgm.modules.attention.print = lambda *args: None

+sgm.modules.diffusionmodules.model.print = lambda *args: None

+sgm.modules.diffusionmodules.openaimodel.print = lambda *args: None

+sgm.modules.encoders.modules.print = lambda *args: None

+