Update app.py

app.py

@@ -316,12 +316,6 @@ def scheduler_swap_callback(pipeline, step_index, timestep, callback_kwargs):
         #pipe.scheduler.set_timesteps(num_inference_steps*.70)
       #  print(f"-- setting step {pipeline.num_timesteps * 0.9} --")
       #  pipeline.scheduler._step_index = pipeline.num_timesteps * 0.9
-    if step_index == int(pipeline.num_timesteps * self.config.cutoff_step_ratio):
-            prompt_embeds = callback_kwargs["prompt_embeds"]
-            prompt_embeds = prompt_embeds.chunk(2)[-1]
-                # update guidance_scale and prompt_embeds
-            pipeline._guidance_scale = 0.0
-            callback_kwargs["prompt_embeds"] = prompt_embeds
     return callback_kwargs
 
 def upload_to_ftp(filename):
@@ -365,7 +359,6 @@ def generate_30(
     height: int = 768,
     guidance_scale: float = 4,
     num_inference_steps: int = 125,
-    guidance_cutoff: float = 1.0,
     use_resolution_binning: bool = True, 
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -381,8 +374,7 @@ def generate_30(
         "num_inference_steps": num_inference_steps,
         "generator": generator,
         "output_type": "pil",
-        "callback_on_step_end": pyx.scheduler_swap_callback(cutoff_step_ratio=guidance_cutoff),
-        "callback_on_step_end_tensor_inputs": ['prompt_embeds']
+        "callback_on_step_end": pyx.scheduler_swap_callback,
     }
     if use_resolution_binning:
         options["use_resolution_binning"] = True
@@ -420,7 +412,6 @@ def generate_60(
     height: int = 768,
     guidance_scale: float = 4,
     num_inference_steps: int = 125,
-    guidance_cutoff: float = 1.0,
     use_resolution_binning: bool = True, 
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -436,8 +427,7 @@ def generate_60(
         "num_inference_steps": num_inference_steps,
         "generator": generator,
         "output_type": "pil",
-        "callback_on_step_end": pyx.scheduler_swap_callback(cutoff_step_ratio=guidance_cutoff),
-        "callback_on_step_end_tensor_inputs": ['prompt_embeds']
+        "callback_on_step_end": pyx.scheduler_swap_callback,
     }
     if use_resolution_binning:
         options["use_resolution_binning"] = True
@@ -465,7 +455,6 @@ def generate_90(
     height: int = 768,
     guidance_scale: float = 4,
     num_inference_steps: int = 125,
-    guidance_cutoff: float = 1.0,
     use_resolution_binning: bool = True, 
     progress=gr.Progress(track_tqdm=True)  # Add progress as a keyword argument
 ):
@@ -481,8 +470,7 @@ def generate_90(
         "num_inference_steps": num_inference_steps,
         "generator": generator,
         "output_type": "pil",
-        "callback_on_step_end": pyx.scheduler_swap_callback(cutoff_step_ratio=guidance_cutoff),
-        "callback_on_step_end_tensor_inputs": ['prompt_embeds']
+        "callback_on_step_end": pyx.scheduler_swap_callback,
     }
     if use_resolution_binning:
         options["use_resolution_binning"] = True
@@ -587,13 +575,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
                 step=0.1,
                 value=3.8,
             )
-            guidance_cutoff = gr.Slider(
-                label="Guidance Scale Cutoff",
-                minimum=0.01,
-                maximum=1.0,
-                step=0.01,
-                value=1.0,
-            )
             num_inference_steps = gr.Slider(
                 label="Number of inference steps",
                 minimum=10,
@@ -629,7 +610,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             width,
             height,
             guidance_scale,
-            guidance_cutoff,
             num_inference_steps,
         ],
         outputs=[result],
@@ -649,7 +629,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             width,
             height,
             guidance_scale,
-            guidance_cutoff,
             num_inference_steps,
         ],
         outputs=[result],
@@ -669,7 +648,6 @@ with gr.Blocks(theme=gr.themes.Origin(),css=css) as demo:
             width,
             height,
             guidance_scale,
-            guidance_cutoff,
             num_inference_steps,
         ],
         outputs=[result],