Update worker_runpod.py

worker_runpod.py

@@ -110,6 +110,8 @@ else:
 def generate(input):
     values = input["input"]
     prompt = values["prompt"]
+    print("starting Generate function")
+    print(prompt)
     negative_prompt = values.get("negative_prompt", "blurry, blurred, blurry face")
     guidance_scale = values.get("guidance_scale", 6.0)
     seed = values.get("seed", 42)
@@ -123,10 +125,12 @@ def generate(input):
     partial_video_length = values.get("partial_video_length", None)
     overlap_video_length = values.get("overlap_video_length", 4)
     validation_image_start = values.get("validation_image_start", "asset/1.png")
+    print(validation_image_start)
     downloaded_image_path = download_image(validation_image_start)
     validation_image_end = values.get("validation_image_end", None)
     
     generator = torch.Generator(device="cuda").manual_seed(seed)
+    print("Generator started")
     if lora_path is not None:
         pipeline = merge_lora(pipeline, lora_path, lora_weight)
     
@@ -136,6 +140,8 @@ def generate(input):
     closest_size, closest_ratio = get_closest_ratio(original_height, original_width, ratios=aspect_ratio_sample_size)
     height, width = [int(x / 16) * 16 for x in closest_size]
     sample_size = [height, width]
+    print("Getting closest ratio")
+    print(closest_ratio)
     video_length = int((video_length - 1) // vae.config.temporal_compression_ratio * vae.config.temporal_compression_ratio) + 1 if video_length != 1 else 1
     input_video, input_video_mask, clip_image = get_image_to_video_latent(downloaded_image_path, validation_image_end, video_length=video_length, sample_size=sample_size)
         
@@ -150,7 +156,7 @@ def generate(input):
     video_path = os.path.join(save_path, f"{prefix}.mp4")
     save_videos_grid(sample, video_path, fps=fps)
 
-
+    print("Video saved to grid, uploading to huggingface")
     hf_api = HfApi()
     repo_id = "meepmoo/h4h4jejdf"  # Set your HF repo
     hf_api.upload_file(
@@ -161,7 +167,7 @@ def generate(input):
        repo_type="model"
     )
 
-    
+    print("Video uploaded to huggingface returing output")
     result_url = f"https://huggingface.co/{repo_id}/blob/main/{prefix}.mp4"
     result_url = ""
     job_id = values.get("job_id", "default-job-id")  # For RunPod job tracking