Update worker_runpod.py
Browse files- worker_runpod.py +13 -1
worker_runpod.py
CHANGED
@@ -17,13 +17,25 @@ from cogvideox.models.autoencoder_magvit import AutoencoderKLCogVideoX
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from cogvideox.pipeline.pipeline_cogvideox import CogVideoX_Fun_Pipeline
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from cogvideox.pipeline.pipeline_cogvideox_inpaint import CogVideoX_Fun_Pipeline_Inpaint
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from cogvideox.utils.lora_utils import merge_lora, unmerge_lora
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from cogvideox.utils.utils import get_image_to_video_latent, save_videos_grid
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from huggingface_hub import HfApi, HfFolder
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tokenxf = os.getenv("HF_API_TOKEN")
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# Low GPU memory mode
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low_gpu_memory_mode = False
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lora_path = "/content/shirtlift.safetensors"
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def download_image(url, download_dir="asset"):
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# Ensure the download directory exists
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if not os.path.exists(download_dir):
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from cogvideox.pipeline.pipeline_cogvideox import CogVideoX_Fun_Pipeline
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from cogvideox.pipeline.pipeline_cogvideox_inpaint import CogVideoX_Fun_Pipeline_Inpaint
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from cogvideox.utils.lora_utils import merge_lora, unmerge_lora
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from cogvideox.utils.utils import get_image_to_video_latent, save_videos_grid
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from cogvideox.data.bucket_sampler import ASPECT_RATIO_512, get_closest_ratio
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from huggingface_hub import HfApi, HfFolder
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tokenxf = os.getenv("HF_API_TOKEN")
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# Low GPU memory mode
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low_gpu_memory_mode = False
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lora_path = "/content/shirtlift.safetensors"
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def to_pil(image):
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if isinstance(image, Image.Image):
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return image
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if isinstance(image, torch.Tensor):
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return tensor2pil(image)
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if isinstance(image, np.ndarray):
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return numpy2pil(image)
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raise ValueError(f"Cannot convert {type(image)} to PIL.Image")
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def download_image(url, download_dir="asset"):
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# Ensure the download directory exists
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if not os.path.exists(download_dir):
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