clear

app.py

@@ -203,7 +203,6 @@ def generate(
 ) -> np.ndarray:
     global pipeline
     change_model_fn(model_name)
-    print(type(image))
     if isinstance(pipeline, FluxConceptrolPipeline):
         images = pipeline(
             prompt=prompt,
@@ -370,7 +369,6 @@ with gr.Blocks(css="style.css") as demo:
     #     inputs=gr.Number(1, visible=False),
     #     outputs=generate_button,
     # )
-    print(type(image_prompt))
     inputs = [
         prompt,
         textual_concept,

omini_control/flux_conceptrol_pipeline.py

@@ -194,8 +194,6 @@ class FluxConceptrolPipeline(FluxPipeline):
         else:
             batch_size = prompt_embeds.shape[0]
 
-        print(batch_size)
-
         device = self._execution_device
 
         lora_scale = (
@@ -292,10 +290,6 @@ class FluxConceptrolPipeline(FluxPipeline):
                     guidance = guidance.expand(latents.shape[0])
                 else:
                     guidance = None
-                print("condition_latents.shape:", condition_latents.shape)
-                print("latent.shape:", latents.shape)
-                print("prompt_embeds.shape", prompt_embeds.shape)
-                print("condition_ids.shape", condition_ids.shape)
                 noise_pred = tranformer_forward(
                     self.transformer,
                     model_config=model_config,