Update app.py

app.py

@@ -241,7 +241,7 @@ def randomize_seed_fn(seed: int, randomize_seed: bool) -> int:
         seed = random.randint(0, MAX_SEED)
     return seed
 
-def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
+def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise):
     filename= f'tst_A_{timestamp}.txt'
     with open(filename, "w") as f:
         f.write(f"Realvis 5.0 (Tester A) \n")
@@ -249,6 +249,7 @@ def uploadNote(prompt,num_inference_steps,guidance_scale,timestamp):
         f.write(f"Prompt: {prompt} \n")
         f.write(f"Steps: {num_inference_steps} \n")
         f.write(f"Guidance Scale: {guidance_scale} \n")
+        f.write(f"Denoise Strength: {denoise} \n")
         f.write(f"SPACE SETUP: \n")
         f.write(f"Use Model Dtype: no \n")
         f.write(f"Model Scheduler: Euler_a all_custom before cuda \n")
@@ -278,6 +279,7 @@ def generate_30(
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
     
 ):
+    print(f'debug: num_images: {num_images} denoise: {denoise}')
     torch.backends.cudnn.benchmark = False
     torch.cuda.empty_cache()
     gc.collect()
@@ -304,7 +306,7 @@ def generate_30(
     images = []
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
+    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
         batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
@@ -371,7 +373,7 @@ def generate_60(
     images = []
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
+    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
         batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]
@@ -438,7 +440,7 @@ def generate_90(
     images = []
     pipe.scheduler.set_timesteps(num_inference_steps,device)
     timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
-    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp)
+    uploadNote(prompt,num_inference_steps,guidance_scale,timestamp,denoise)
     for i in range(0, num_images, BATCH_SIZE):
         batch_options = options.copy()
         batch_options["prompt"] = options["prompt"][i:i+BATCH_SIZE]