Update app.py

app.py

@@ -94,6 +94,8 @@ class ModelWrapper:
         
         for constant in all_timesteps:
             current_timesteps = torch.ones(len(prompt_embed), device="cuda", dtype=torch.long) * constant
+            print(type(current_timesteps))
+            print(type(noise))
             eval_images = self.model(noise, current_timesteps, prompt_embed, added_cond_kwargs=unet_added_conditions).sample
             print(type(eval_images))
 
@@ -158,7 +160,7 @@ def get_x0_from_noise(sample, model_output, alphas_cumprod, timestep):
     return pred_original_sample
 
 class SDXLTextEncoder(torch.nn.Module):
-    def __init__(self, model_id, revision, accelerator, dtype=torch.float16):
+    def __init__(self, model_id, revision, accelerator, dtype=torch.float32):
         super().__init__()
 
         self.text_encoder_one = CLIPTextModel.from_pretrained(model_id, subfolder="text_encoder", revision=revision).to(0).to(dtype=dtype)