wehub-resource-sync
177 lines
5.9 KiB
Python
177 lines
5.9 KiB
Python
from __future__ import annotations
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import argparse
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import os
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import threading
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from pathlib import Path
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REPO_ROOT = Path(__file__).resolve().parents[2]
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GRADIO_TMP_ROOT = Path(os.getenv("LANCE_GRADIO_TMP_ROOT", "/tmp/lance_gradio")).expanduser()
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TMP_INPUT_DIR = GRADIO_TMP_ROOT / "inputs"
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RESULTS_ROOT = GRADIO_TMP_ROOT / "results"
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PREVIEW_VIDEO_DIR = GRADIO_TMP_ROOT / "preview_videos"
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GLOBAL_RECORDS_FILE = GRADIO_TMP_ROOT / "generation_records.jsonl"
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RUN_RECORD_FILENAME = "generation_record.json"
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PROMPT_JSON_FILENAME = "prompt.json"
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LOCAL_MODEL_BASE_DIR = Path("downloads")
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DEFAULT_MODEL_VARIANT = "video"
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MODEL_VARIANT_VIDEO = "video"
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MODEL_VARIANT_IMAGE = "image"
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MODEL_VARIANT_TO_DIR = {
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MODEL_VARIANT_VIDEO: "Lance_3B_Video",
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MODEL_VARIANT_IMAGE: "Lance_3B",
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}
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DEFAULT_VIT_TYPE = "qwen_2_5_vl_original"
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DEFAULT_TASK = "t2v"
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DEFAULT_TIMESTEPS = 30
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DEFAULT_TIMESTEP_SHIFT = 3.5
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DEFAULT_CFG_TEXT_SCALE = 4.0
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DEFAULT_RESOLUTION = "video_480p"
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DEFAULT_VIDEO_EDIT_RESOLUTION = "video_480p"
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DEFAULT_IMAGE_RESOLUTION = "image_768res"
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DEFAULT_BASIC_SEED = 42
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DEFAULT_HEIGHT = 352
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DEFAULT_WIDTH = 640
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DEFAULT_T2V_DURATION_SECONDS = 8
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DEFAULT_I2V_DURATION_SECONDS = 5
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DEFAULT_VIDEO_DURATION_SECONDS = DEFAULT_T2V_DURATION_SECONDS
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MAX_VIDEO_DURATION_SECONDS = 10
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MAX_VIDEO_NUM_FRAMES = 12 * MAX_VIDEO_DURATION_SECONDS + 1
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DEFAULT_NUM_FRAMES = 12 * DEFAULT_VIDEO_DURATION_SECONDS + 1
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DEFAULT_VIDEO_ASPECT_RATIO = "16:9"
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DEFAULT_IMAGE_ASPECT_RATIO = "1:1"
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ASPECT_RATIO_CHOICES = ["21:9", "16:9", "3:2", "4:3", "1:1", "3:4", "2:3", "9:16"]
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VIDEO_360P_ASPECT_RATIO_TO_SIZE = {
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"21:9": (672, 288),
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"16:9": (640, 352),
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"3:2": (528, 352),
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"4:3": (560, 416),
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"1:1": (480, 480),
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"3:4": (416, 560),
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"2:3": (352, 528),
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"9:16": (352, 640),
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}
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VIDEO_480P_ASPECT_RATIO_TO_SIZE = {
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"21:9": (976, 416),
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"16:9": (848, 480),
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"3:2": (784, 528),
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"4:3": (736, 560),
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"1:1": (640, 640),
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"3:4": (560, 736),
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"2:3": (528, 784),
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"9:16": (480, 848),
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}
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VIDEO_RESOLUTION_TO_SIZE_MAP = {
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"video_360p": VIDEO_360P_ASPECT_RATIO_TO_SIZE,
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"video_480p": VIDEO_480P_ASPECT_RATIO_TO_SIZE,
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}
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IMAGE_ASPECT_RATIO_TO_SIZE = {
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"21:9": (1168, 496),
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"16:9": (1024, 576),
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"3:2": (944, 624),
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"4:3": (880, 672),
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"1:1": (768, 768),
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"3:4": (672, 880),
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"2:3": (624, 944),
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"9:16": (576, 1024),
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}
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DEFAULT_GPUS = "0"
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DEFAULT_QUEUE_SIZE = 32
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USE_KVCACHE = True
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TEXT_TEMPLATE = True
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RECORD_WRITE_LOCK = threading.Lock()
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LANCE_HOMEPAGE_URL = "https://lance-project.github.io/"
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LANCE_PAPER_URL = "http://arxiv.org/abs/2605.18678"
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LANCE_HUGGING_FACE_URL = "https://huggingface.co/bytedance-research/Lance"
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LANCE_GITHUB_URL = "https://github.com/bytedance/Lance"
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LANCE_LOGO_PATH = REPO_ROOT / "assets" / "logo" / "lance-logo.png"
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TASK_T2V = "t2v"
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TASK_T2I = "t2i"
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TASK_I2V = "i2v"
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TASK_V2T = "v2t"
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TASK_X2T = "x2t"
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TASK_X2T_VIDEO = "x2t_video"
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TASK_X2T_IMAGE = "x2t_image"
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TASK_IMAGE_EDIT = "image_edit"
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TASK_VIDEO_EDIT = "video_edit"
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TASK_LABEL_VIDEO_GENERATION = "Text-to-Video"
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TASK_LABEL_IMAGE_TO_VIDEO = "Image-to-Video"
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TASK_LABEL_VIDEO_EDIT = "Video Edit"
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TASK_LABEL_VIDEO_UNDERSTANDING = "Video Understanding"
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TASK_LABEL_IMAGE_GENERATION = "Text-to-Image"
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TASK_LABEL_IMAGE_EDIT = "Image Edit"
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TASK_LABEL_IMAGE_UNDERSTANDING = "Image Understanding"
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TASK_CHOICES = [
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TASK_LABEL_VIDEO_GENERATION,
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TASK_LABEL_IMAGE_TO_VIDEO,
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TASK_LABEL_VIDEO_EDIT,
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TASK_LABEL_VIDEO_UNDERSTANDING,
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TASK_LABEL_IMAGE_GENERATION,
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TASK_LABEL_IMAGE_EDIT,
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TASK_LABEL_IMAGE_UNDERSTANDING,
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]
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TASK_LABEL_TO_INTERNAL = {
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TASK_LABEL_VIDEO_GENERATION: TASK_T2V,
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TASK_LABEL_IMAGE_TO_VIDEO: TASK_I2V,
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TASK_LABEL_VIDEO_EDIT: TASK_VIDEO_EDIT,
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TASK_LABEL_VIDEO_UNDERSTANDING: TASK_X2T_VIDEO,
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TASK_LABEL_IMAGE_GENERATION: TASK_T2I,
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TASK_LABEL_IMAGE_EDIT: TASK_IMAGE_EDIT,
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TASK_LABEL_IMAGE_UNDERSTANDING: TASK_X2T_IMAGE,
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TASK_T2V: TASK_T2V,
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TASK_VIDEO_EDIT: TASK_VIDEO_EDIT,
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TASK_V2T: TASK_X2T_VIDEO,
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TASK_X2T: TASK_X2T_VIDEO,
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TASK_X2T_VIDEO: TASK_X2T_VIDEO,
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TASK_T2I: TASK_T2I,
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TASK_I2V: TASK_I2V,
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TASK_IMAGE_EDIT: TASK_IMAGE_EDIT,
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TASK_X2T_IMAGE: TASK_X2T_IMAGE,
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}
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GENERATION_TASKS = {TASK_T2V, TASK_T2I, TASK_I2V, TASK_IMAGE_EDIT, TASK_VIDEO_EDIT}
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UNDERSTANDING_TASKS = {TASK_X2T_VIDEO, TASK_X2T_IMAGE}
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IMAGE_TASKS = {TASK_T2I, TASK_IMAGE_EDIT, TASK_X2T_IMAGE}
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VIDEO_TASKS = {TASK_T2V, TASK_I2V, TASK_VIDEO_EDIT, TASK_X2T_VIDEO}
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EDIT_TASKS = {TASK_IMAGE_EDIT, TASK_VIDEO_EDIT}
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VIDEO_RESOLUTION_CHOICES = [DEFAULT_RESOLUTION]
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VIDEO_EDIT_RESOLUTION_CHOICES = [DEFAULT_VIDEO_EDIT_RESOLUTION]
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IMAGE_RESOLUTION_CHOICES = [DEFAULT_IMAGE_RESOLUTION]
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VIDEO_RESOLUTION_DISPLAY_CHOICES = [("360p", "video_360p"), ("480p", "video_480p")]
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V2T_QA_SYSTEM_PROMPT = "View the video attentively and provide a suitable answer to the posed question."
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I2T_QA_SYSTEM_PROMPT = "View the image attentively and provide a suitable answer to the posed question."
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def parse_args() -> argparse.Namespace:
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parser = argparse.ArgumentParser(description="Lance multimodal Gradio")
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parser.add_argument("--server-name", default=os.getenv("GRADIO_SERVER_NAME", "127.0.0.1"))
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parser.add_argument("--server-port", type=int, default=int(os.getenv("GRADIO_SERVER_PORT", "7860")))
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parser.add_argument(
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"--gpus",
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default=os.getenv("LANCE_GPUS", DEFAULT_GPUS),
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help="Comma-separated GPU list, for example: 0,1,2,3,4,5,6",
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)
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parser.add_argument(
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"--queue-size",
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type=int,
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default=int(os.getenv("LANCE_QUEUE_SIZE", str(DEFAULT_QUEUE_SIZE))),
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help="Maximum number of queued Gradio requests.",
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)
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return parser.parse_args()
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def parse_gpu_ids(gpu_string: str) -> list[int]:
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gpu_ids: list[int] = []
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for item in gpu_string.split(","):
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item = item.strip()
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if not item:
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continue
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gpu_ids.append(int(item))
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if not gpu_ids:
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raise ValueError("No valid GPU IDs were parsed.")
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return gpu_ids
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