fix the problem with infinite prompts where empty cond would be calculated incorrectly

modules/models/sd3/sd3_cond.py

@@ -177,6 +177,7 @@ class SD3Cond(torch.nn.Module):
         self.weights_loaded = False
 
     def forward(self, prompts: list[str]):
+        with devices.without_autocast():
             lg_out, vector_out = self.model_lg(prompts)
 
             token_count = lg_out.shape[1]

modules/models/sd3/sd3_model.py

@@ -47,7 +47,6 @@ class SD3Inferencer(torch.nn.Module):
         return contextlib.nullcontext()
 
     def get_learned_conditioning(self, batch: list[str]):
-        with devices.without_autocast():
         return self.cond_stage_model(batch)
 
     def apply_model(self, x, t, cond):

modules/sd_models.py

@@ -718,9 +718,8 @@ def get_empty_cond(sd_model):
     p = processing.StableDiffusionProcessingTxt2Img()
     extra_networks.activate(p, {})
 
-    if hasattr(sd_model, 'conditioner'):
+    if hasattr(sd_model, 'get_learned_conditioning'):
         d = sd_model.get_learned_conditioning([""])
-        return d['crossattn']
     else:
         d = sd_model.cond_stage_model([""])