1881 lines
313 KiB
Plaintext
1881 lines
313 KiB
Plaintext
2026-06-13 19:58:07.678[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/ahserver/configuredServer.py:40]client_max_size=1024000000
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reuse_port= True
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<bound method LongTasks.run of <__main__.Wan22Tasks object at 0x7fd10e1e6e00>> is a coroutine
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2026-06-13 19:58:07.680[webapp][debug][/data/ymq/wan22-service/ah.py:32]longtasks worker started, GPU: 3
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======== Running on http://0.0.0.0:8079 ========
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(Press CTRL+C to quit)
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2026-06-13 19:58:07.781[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-13 19:58:07.782[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:131][worker 0] start
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2026-06-13 20:02:40.997[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=0g-viJnViW4v5AVaqQFCZ
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2026-06-13 20:02:40.998[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': '949ddbbf0fa5', 'prompt': 'Concurrent test task 3 - mountain landscape with flowing river', 'image': None, 'size': '832*480', 'frame_num': 33, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781352160.9958723, 'task_id': '0g-viJnViW4v5AVaqQFCZ'}
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2026-06-13 20:02:40.998[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:02:41.002[webapp][debug][/data/ymq/wan22-service/workers/generate.py:29]Loading Wan22 engine (first call, may take 30-60s)...
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Loading checkpoint shards: 100%|██████████| 3/3 [00:00<00:00, 11.59it/s]
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2026-06-13 20:03:58.617[webapp][debug][/data/ymq/wan22-service/workers/generate.py:49]Wan22 engine loaded, GPU: 3
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33%|███▎ | 10/30 [00:09<00:18, 1.10it/s]2026-06-13 20:04:25.429[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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/data/ymq/wan22-service/repo/wan/modules/vae2_2.py:1042: FutureWarning: `torch.cuda.amp.autocast(args...)` is deprecated. Please use `torch.amp.autocast('cuda', args...)` instead.
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with amp.autocast(dtype=self.dtype):
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2026-06-13 20:05:06.011[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/949ddbbf0fa5.mp4 (2482335 bytes)
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2026-06-13 20:05:06.013[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished 0g-viJnViW4v5AVaqQFCZ
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2026-06-13 20:09:25.432[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:14:01.008[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=Vp_8yhI9S23n7aDAIjfvw
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2026-06-13 20:14:01.009[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'scene_01', 'prompt': "An absurdly over-engineered quality control center where every musical note is inspected by robotic arms with magnifying glasses. A giant assembly line conveyor belt carries glowing musical notes through 700 scanning stations. Holographic stamps reading 'APPROVED' flash repeatedly. Workers in hazmat suits carefully examine each syllable under microscopes. The camera tracks sideways along the infinite assembly line. Color palette: sterile white mixed with neon green verification lights and red rejection warnings. Satirical industrial aesthetic with exaggerated bureaucratic imagery.", 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781352841.0077553, 'task_id': 'Vp_8yhI9S23n7aDAIjfvw'}
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2026-06-13 20:14:01.009[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:14:25.437[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:16:55.800[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/scene_01.mp4 (6944068 bytes)
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2026-06-13 20:16:55.805[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished Vp_8yhI9S23n7aDAIjfvw
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2026-06-13 20:16:55.805[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=xYgL-foX5FzQXpHbqTk-_
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2026-06-13 20:16:55.806[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'scene_06', 'prompt': "A propaganda ministry control room where officials manipulate reality displays. Giant screens show statistics being 'optimized' - bars growing impossibly tall, pie charts distorting. Workers adjust 'narrative dials' on a massive control panel labeled 'PROMOTION CALIBRATION'. A conveyor belt feeds revised press releases. When data looks insufficient, a button labeled 'UPGRADE NARRATIVE' is pressed and everything glows brighter. The camera dollies through layers of increasingly absurd propaganda machinery. Deep red and gold authoritarian color palette with glitching digital artifacts. Totalitarian kitsch meets cyberpunk.", 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781352841.0551424, 'task_id': 'xYgL-foX5FzQXpHbqTk-_'}
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2026-06-13 20:16:55.806[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:19:25.440[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:19:51.192[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/scene_06.mp4 (10036698 bytes)
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2026-06-13 20:19:51.194[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished xYgL-foX5FzQXpHbqTk-_
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2026-06-13 20:20:44.344[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=y2XIm99stQu4hazA3N9Sr
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2026-06-13 20:20:44.344[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s02', 'prompt': 'A golden stamp reading TOP SECRET slams onto a futuristic document. Camera pulls back to reveal an enormous vault filled with classified projects. Volumetric fog, dramatic rim lighting.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.3430252, 'task_id': 'y2XIm99stQu4hazA3N9Sr'}
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2026-06-13 20:20:44.345[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:23:37.483[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s02.mp4 (5902251 bytes)
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2026-06-13 20:23:37.483[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished y2XIm99stQu4hazA3N9Sr
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2026-06-13 20:23:37.484[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=NS7Me0mSueAZeeuA-ORsQ
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2026-06-13 20:23:37.484[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s27', 'prompt': 'People on streets worldwide staring at screens with glazed hypnotized eyes while a giant holographic face smiles benevolently above the city. Purple neon and cosmic gold palette.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.544177, 'task_id': 'NS7Me0mSueAZeeuA-ORsQ'}
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2026-06-13 20:23:37.485[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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23%|██▎ | 7/30 [00:26<01:27, 3.80s/it]2026-06-13 20:24:25.447[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:26:27.188[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s27.mp4 (9818124 bytes)
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2026-06-13 20:26:27.190[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished NS7Me0mSueAZeeuA-ORsQ
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2026-06-13 20:26:27.190[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s27
|
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2026-06-13 20:26:27.191[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s27', 'prompt': 'People on streets worldwide staring at screens with glazed hypnotized eyes while a giant holographic face smiles benevolently above the city. Purple neon and cosmic gold palette.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6094542, 'task_id': 'mtv_s27'}
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2026-06-13 20:26:27.191[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:29:16.802[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s27.mp4 (9818124 bytes)
|
|
2026-06-13 20:29:16.803[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s27
|
|
2026-06-13 20:29:16.804[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s23
|
|
2026-06-13 20:29:16.804[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s23', 'prompt': 'A massive red button labeled upgrade narrative being pressed. Everything in the room glows brighter. Conveyor belt feeds revised press releases. Deep red and gold authoritarian palette.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6086533, 'task_id': 'mtv_s23'}
|
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2026-06-13 20:29:16.805[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-13 20:29:25.450[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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90%|█████████ | 27/30 [01:43<00:11, 3.84s/it]
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|
|
2026-06-13 20:32:07.013[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s23.mp4 (6108860 bytes)
|
|
2026-06-13 20:32:07.014[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s23
|
|
2026-06-13 20:32:07.015[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s19
|
|
2026-06-13 20:32:07.015[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s19', 'prompt': 'Historical music textbooks being shredded by machines and replaced with shiny new editions bearing the song title. Institutional green and cyberpunk purple tones.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6078622, 'task_id': 'mtv_s19'}
|
|
2026-06-13 20:32:07.016[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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100%|██████████| 30/30 [01:54<00:00, 3.83s/it]
|
|
2026-06-13 20:34:25.458[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 20:34:55.164[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s19.mp4 (6753208 bytes)
|
|
2026-06-13 20:34:55.167[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s19
|
|
2026-06-13 20:34:55.167[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s15
|
|
2026-06-13 20:34:55.168[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s15', 'prompt': 'Cyberpunk lawyers in glowing suits deploy from pods, marching in formation with briefcases emitting laser beams. Authoritarian corporate aesthetic, dark satire.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.607049, 'task_id': 'mtv_s15'}
|
|
2026-06-13 20:34:55.168[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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83%|████████▎ | 25/30 [01:35<00:19, 3.84s/it]
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|
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90%|█████████ | 27/30 [01:43<00:11, 3.84s/it]
|
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|
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97%|█████████▋| 29/30 [01:50<00:03, 3.84s/it]
|
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|
|
2026-06-13 20:37:43.987[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s15.mp4 (5756094 bytes)
|
|
2026-06-13 20:37:43.988[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s15
|
|
2026-06-13 20:37:43.989[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s12
|
|
2026-06-13 20:37:43.997[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s12', 'prompt': 'News anchors with shocked expressions reading teleprompters. Screens behind them showing charts going parabolic. Media frenzy, information overload, neon orange and red alert colors.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6064453, 'task_id': 'mtv_s12'}
|
|
2026-06-13 20:37:43.998[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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27%|██▋ | 8/30 [00:30<01:23, 3.81s/it]
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70%|███████ | 21/30 [01:20<00:34, 3.83s/it]2026-06-13 20:39:25.461[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:40:33.557[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s12.mp4 (5715933 bytes)
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2026-06-13 20:40:33.559[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s12
|
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2026-06-13 20:40:33.559[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s08
|
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2026-06-13 20:40:33.560[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s08', 'prompt': 'A golden museum entrance where song titles are carved into stone tablets. Visitors bow reverently. Cyberpunk cityscape visible through glass ceiling, bathed in electric pink and gold.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6056054, 'task_id': 'mtv_s08'}
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2026-06-13 20:40:33.560[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:43:23.842[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s08.mp4 (4390558 bytes)
|
|
2026-06-13 20:43:23.844[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s08
|
|
2026-06-13 20:43:23.844[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s04
|
|
2026-06-13 20:43:23.845[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s04', 'prompt': 'Workers in futuristic hazmat suits examining sound waves under holographic microscopes. Giant APPROVED stamps flash repeatedly. Exaggerated bureaucratic quality control center, satirical.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6048214, 'task_id': 'mtv_s04'}
|
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2026-06-13 20:43:23.845[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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37%|███▋ | 11/30 [00:41<01:12, 3.82s/it]2026-06-13 20:44:25.471[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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|
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2026-06-13 20:46:13.056[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s04.mp4 (7081656 bytes)
|
|
2026-06-13 20:46:13.058[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s04
|
|
2026-06-13 20:46:13.058[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=mtv_s00
|
|
2026-06-13 20:46:13.059[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s00', 'prompt': 'A lone figure in a dark underground cyberpunk lab, typing on a holographic keyboard. Rows of server racks pulse with neon blue light behind them. Camera slowly dollies forward. Moody, mysterious atmosphere.', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781353496.6039467, 'task_id': 'mtv_s00'}
|
|
2026-06-13 20:46:13.060[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:49:00.518[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s00.mp4 (7694351 bytes)
|
|
2026-06-13 20:49:00.519[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished mtv_s00
|
|
2026-06-13 20:49:00.520[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=XiTHUaiO3UfrzNhwBJEI7
|
|
2026-06-13 20:49:00.520[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s23', 'prompt': 'A massive red button labeled upgrade narrative being pressed. Everything in the room glows brighter. Conveyor belt feeds revised press releases. Deep red and gold authoritarian palette.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.509087, 'task_id': 'XiTHUaiO3UfrzNhwBJEI7'}
|
|
2026-06-13 20:49:00.521[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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|
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2026-06-13 20:51:51.147[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s23.mp4 (6108860 bytes)
|
|
2026-06-13 20:51:51.149[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished XiTHUaiO3UfrzNhwBJEI7
|
|
2026-06-13 20:51:51.150[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=ylPWc4qq9WkOYRNTKmPPB
|
|
2026-06-13 20:51:51.209[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s19', 'prompt': 'Historical music textbooks being shredded by machines and replaced with shiny new editions bearing the song title. Institutional green and cyberpunk purple tones.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.4805446, 'task_id': 'ylPWc4qq9WkOYRNTKmPPB'}
|
|
2026-06-13 20:51:51.209[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:54:25.586[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 20:54:38.381[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s19.mp4 (6753208 bytes)
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2026-06-13 20:54:38.383[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished ylPWc4qq9WkOYRNTKmPPB
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2026-06-13 20:54:38.383[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=DJ9kZnrHO8J4EKlyEzf_5
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2026-06-13 20:54:38.384[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s15', 'prompt': 'Cyberpunk lawyers in glowing suits deploy from pods, marching in formation with briefcases emitting laser beams. Authoritarian corporate aesthetic, dark satire.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.4481158, 'task_id': 'DJ9kZnrHO8J4EKlyEzf_5'}
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2026-06-13 20:54:38.385[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 20:57:26.611[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s15.mp4 (5756094 bytes)
|
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2026-06-13 20:57:26.613[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished DJ9kZnrHO8J4EKlyEzf_5
|
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2026-06-13 20:57:26.614[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=EJte6TJv-aViImIvVL1FG
|
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2026-06-13 20:57:26.615[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s11', 'prompt': 'Split screens showing social media trending topics exploding with fire emojis and comment floods. A panel of experts in oversized glasses pointing at whiteboards with complex formulas.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.4151943, 'task_id': 'EJte6TJv-aViImIvVL1FG'}
|
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2026-06-13 20:57:26.615[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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17%|█▋ | 5/30 [00:19<01:35, 3.80s/it]2026-06-13 20:58:07.783[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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83%|████████▎ | 25/30 [01:35<00:19, 3.84s/it]2026-06-13 20:59:25.664[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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87%|████████▋ | 26/30 [01:39<00:15, 3.84s/it]
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2026-06-13 21:00:16.053[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s11.mp4 (3725835 bytes)
|
|
2026-06-13 21:00:16.055[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished EJte6TJv-aViImIvVL1FG
|
|
2026-06-13 21:00:16.055[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=IAllnEvLJg2sATsG_Nqz-
|
|
2026-06-13 21:00:16.056[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'mtv_s07', 'prompt': 'Competing artists entries crumble to dust on a massive stage. A holographic crown descends from the ceiling onto an empty throne. Camera sweeps upward revealing endless hall of trophies.', 'image': None, 'size': '832*480', 'frame_num': 129, 'sample_steps': None, 'sample_guide_scale': None, 'base_seed': None}, 'status': 'PENDING', 'created_at': 1781353244.3789103, 'task_id': 'IAllnEvLJg2sATsG_Nqz-'}
|
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2026-06-13 21:00:16.057[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-13 21:03:04.926[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/mtv_s07.mp4 (11224785 bytes)
|
|
2026-06-13 21:03:04.928[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished IAllnEvLJg2sATsG_Nqz-
|
|
2026-06-13 21:04:25.669[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:09:25.672[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:14:25.673[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:19:25.678[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:24:25.681[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:29:25.683[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:34:25.683[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:39:25.687[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:44:25.690[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 21:49:25.692[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:54:25.697[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 21:58:07.783[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
|
|
2026-06-13 21:59:25.701[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:04:25.702[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:09:25.703[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:14:25.708[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:19:25.711[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:24:25.713[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:29:25.714[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:34:25.718[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:39:25.720[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:44:25.720[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:49:25.725[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 22:54:25.729[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-13 22:58:07.784[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
|
|
2026-06-13 22:59:25.731[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:04:25.731[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:09:25.735[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:14:25.737[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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2026-06-13 23:19:25.738[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:24:25.743[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:29:25.745[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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2026-06-13 23:34:25.746[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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2026-06-13 23:39:25.747[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-13 23:44:25.751[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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2026-06-13 23:49:25.754[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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2026-06-13 23:52:12.200[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s03
|
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2026-06-13 23:52:12.202[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s03', 'prompt': 'A teenage boy learning to play acoustic guitar on a wooden porch, warm indoor lighting, focused expression, coming of age', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781365932.2001543, 'task_id': 'dielv_s03'}
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2026-06-13 23:52:12.202[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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97%|█████████▋| 29/30 [01:50<00:03, 3.83s/it]2026-06-13 23:54:25.856[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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100%|██████████| 30/30 [01:54<00:00, 3.83s/it]
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2026-06-13 23:55:02.423[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s03.mp4 (4230230 bytes)
|
|
2026-06-13 23:55:02.425[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s03
|
|
2026-06-13 23:55:02.425[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s21
|
|
2026-06-13 23:55:02.426[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s21', 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, aerial drone shot, blue green water', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781366061.6871283, 'task_id': 'dielv_s21'}
|
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2026-06-13 23:55:02.426[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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100%|██████████| 30/30 [01:54<00:00, 3.83s/it]
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|
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2026-06-13 23:57:52.462[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s21.mp4 (11259881 bytes)
|
|
2026-06-13 23:57:52.464[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s21
|
|
2026-06-13 23:57:52.464[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s17
|
|
2026-06-13 23:57:52.465[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s17', 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature symphony, epic wide shot', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781366061.6863546, 'task_id': 'dielv_s17'}
|
|
2026-06-13 23:57:52.465[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-13 23:58:07.785[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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63%|██████▎ | 19/30 [01:12<00:42, 3.83s/it]2026-06-13 23:59:25.930[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
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67%|██████▋ | 20/30 [01:16<00:38, 3.83s/it]
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|
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2026-06-14 00:00:41.254[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s17.mp4 (9814141 bytes)
|
|
2026-06-14 00:00:41.257[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s17
|
|
2026-06-14 00:00:41.257[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s14
|
|
2026-06-14 00:00:41.258[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s14', 'prompt': 'Close-up of hands writing music notes on paper, pen moving steadily, warm desk lamp, creative flow, vintage paper texture', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781366061.6857574, 'task_id': 'dielv_s14'}
|
|
2026-06-14 00:00:41.259[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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|
|
2026-06-14 00:03:31.495[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s14.mp4 (3088185 bytes)
|
|
2026-06-14 00:03:31.497[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s14
|
|
2026-06-14 00:03:31.497[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s09
|
|
2026-06-14 00:03:31.498[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s09', 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, reflective mood, night scene', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781366061.6847923, 'task_id': 'dielv_s09'}
|
|
2026-06-14 00:03:31.498[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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30%|███ | 9/30 [00:34<01:20, 3.82s/it]2026-06-14 00:04:25.986[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:06:19.726[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s09.mp4 (6427469 bytes)
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2026-06-14 00:06:19.727[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s09
|
|
2026-06-14 00:06:19.728[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s06
|
|
2026-06-14 00:06:19.728[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s06', 'prompt': 'Close-up of guitar strings being played, fingers moving gracefully, warm stage lighting, musical passion, shallow depth of field', 'size': '832*480', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781366061.6841996, 'task_id': 'dielv_s06'}
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2026-06-14 00:06:19.729[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:09:08.976[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s06.mp4 (5484613 bytes)
|
|
2026-06-14 00:09:08.977[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s06
|
|
2026-06-14 00:09:08.978[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s02
|
|
2026-06-14 00:09:08.979[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s02', 'prompt': 'An old tree on a hilltop under moonlight, cicadas singing in the night, peaceful rural summer evening, soft blue tones', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6830482, 'finished_at': 1781366102.8508167, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s02', 'status': 'completed', 'video_url': '/idfile?path=dielv_s02.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s02.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 4427050, 'prompt': 'An old tree on a hilltop under moonlight, cicadas singing in the night, peaceful rural summer evenin', 'seed': 1574215179}, 'task_id': 'dielv_s02', 'started_at': 1781365932.201593}
|
|
2026-06-14 00:09:08.980[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:09:25.999[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:11:58.206[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s02.mp4 (3780188 bytes)
|
|
2026-06-14 00:11:58.207[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s02
|
|
2026-06-14 00:11:58.208[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s21
|
|
2026-06-14 00:11:58.209[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s21', 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, aerial drone shot, blue green water', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6871283, 'finished_at': 1781366272.4627793, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s21', 'status': 'completed', 'video_url': '/idfile?path=dielv_s21.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s21.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 11259881, 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, a', 'seed': 56748582}, 'task_id': 'dielv_s21', 'started_at': 1781366102.4260478}
|
|
2026-06-14 00:11:58.209[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:14:26.100[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-14 00:14:46.369[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s21.mp4 (11259881 bytes)
|
|
2026-06-14 00:14:46.371[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s21
|
|
2026-06-14 00:14:46.371[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s17
|
|
2026-06-14 00:14:46.372[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s17', 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature symphony, epic wide shot', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6863546, 'finished_at': 1781366441.2550292, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s17', 'status': 'completed', 'video_url': '/idfile?path=dielv_s17.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s17.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 9814141, 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature s', 'seed': 56748582}, 'task_id': 'dielv_s17', 'started_at': 1781366272.465407}
|
|
2026-06-14 00:14:46.373[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:17:36.643[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s17.mp4 (9814141 bytes)
|
|
2026-06-14 00:17:36.645[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s17
|
|
2026-06-14 00:17:36.645[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s13
|
|
2026-06-14 00:17:36.646[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s13', 'prompt': 'A middle-aged musician performing in a park, surrounded by trees, children listening, warm afternoon sunlight, simple joy', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6855578, 'finished_at': 1781366612.7144716, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s13', 'status': 'completed', 'video_url': '/idfile?path=dielv_s13.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s13.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 8107530, 'prompt': 'A middle-aged musician performing in a park, surrounded by trees, children listening, warm afternoon', 'seed': 1789236950}, 'task_id': 'dielv_s13', 'started_at': 1781366442.3059115}
|
|
2026-06-14 00:17:36.647[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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77%|███████▋ | 23/30 [01:28<00:26, 3.84s/it]2026-06-14 00:19:26.150[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:20:25.349[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s13.mp4 (11200309 bytes)
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2026-06-14 00:20:25.351[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s13
|
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2026-06-14 00:20:25.351[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s09
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2026-06-14 00:20:25.352[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s09', 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, reflective mood, night scene', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6847923, 'finished_at': 1781366779.7262733, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s09', 'status': 'completed', 'video_url': '/idfile?path=dielv_s09.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s09.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 6427469, 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, ref', 'seed': 56748582}, 'task_id': 'dielv_s09', 'started_at': 1781366611.4982686}
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2026-06-14 00:20:25.353[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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|
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2026-06-14 00:23:13.574[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s09.mp4 (6427469 bytes)
|
|
2026-06-14 00:23:13.576[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s09
|
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2026-06-14 00:23:13.577[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s05
|
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2026-06-14 00:23:13.578[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s05', 'prompt': 'A cozy bar with warm lighting, a young singer performing on a small stage, audience clapping along, intimate concert atmosphere', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6840105, 'finished_at': 1781366953.6976562, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s05', 'status': 'completed', 'video_url': '/idfile?path=dielv_s05.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s05.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 5507655, 'prompt': 'A cozy bar with warm lighting, a young singer performing on a small stage, audience clapping along, ', 'seed': 2087212057}, 'task_id': 'dielv_s05', 'started_at': 1781366782.0936668}
|
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2026-06-14 00:23:13.578[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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47%|████▋ | 14/30 [00:53<01:01, 3.83s/it]2026-06-14 00:24:26.222[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:26:01.447[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s05.mp4 (5437821 bytes)
|
|
2026-06-14 00:26:01.448[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s05
|
|
2026-06-14 00:26:01.449[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s01
|
|
2026-06-14 00:26:01.450[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s01', 'prompt': 'Close-up of ocean waves crashing on shore, seashells scattered on wet sand, summer afternoon, peaceful atmosphere', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6828666, 'finished_at': 1781367123.449019, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s01', 'status': 'completed', 'video_url': '/idfile?path=dielv_s01.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s01.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 6060675, 'prompt': 'Close-up of ocean waves crashing on shore, seashells scattered on wet sand, summer afternoon, peacef', 'seed': 1789236950}, 'task_id': 'dielv_s01', 'started_at': 1781366952.7524881}
|
|
2026-06-14 00:26:01.451[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:28:50.454[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s01.mp4 (9118882 bytes)
|
|
2026-06-14 00:28:50.456[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s01
|
|
2026-06-14 00:28:50.457[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s20
|
|
2026-06-14 00:28:50.458[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s20', 'prompt': 'A young child sitting next to the elderly musician on the beach, learning to play, generational passing of music, heartwarming', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6869352, 'finished_at': 1781367293.1864796, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s20', 'status': 'completed', 'video_url': '/idfile?path=dielv_s20.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s20.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 2668228, 'prompt': 'A young child sitting next to the elderly musician on the beach, learning to play, generational pass', 'seed': 1789236950}, 'task_id': 'dielv_s20', 'started_at': 1781367123.4519937}
|
|
2026-06-14 00:28:50.458[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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13%|█▎ | 4/30 [00:15<01:38, 3.80s/it]2026-06-14 00:29:26.260[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:31:37.792[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s20.mp4 (2948397 bytes)
|
|
2026-06-14 00:31:37.794[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s20
|
|
2026-06-14 00:31:37.794[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s16
|
|
2026-06-14 00:31:37.795[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s16', 'prompt': 'Moonlight reflecting on calm ocean surface, gentle ripples creating patterns, serene night scene, silver blue tones, meditative', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6861644, 'finished_at': 1781367464.3984025, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s16', 'status': 'completed', 'video_url': '/idfile?path=dielv_s16.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s16.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 4597770, 'prompt': 'Moonlight reflecting on calm ocean surface, gentle ripples creating patterns, serene night scene, si', 'seed': 1789236950}, 'task_id': 'dielv_s16', 'started_at': 1781367293.18933}
|
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2026-06-14 00:31:37.796[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:34:24.115[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s16.mp4 (4959999 bytes)
|
|
2026-06-14 00:34:24.116[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s16
|
|
2026-06-14 00:34:24.116[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s12
|
|
2026-06-14 00:34:24.117[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s12', 'prompt': 'Waves continuously hitting rocky shores, time-lapse style showing the repetitive rhythm of nature, powerful yet calming', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6853685, 'finished_at': 1781367634.8353448, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s12', 'status': 'completed', 'video_url': '/idfile?path=dielv_s12.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s12.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 7052668, 'prompt': 'Waves continuously hitting rocky shores, time-lapse style showing the repetitive rhythm of nature, p', 'seed': 1789236950}, 'task_id': 'dielv_s12', 'started_at': 1781367464.401356}
|
|
2026-06-14 00:34:24.118[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:34:26.263[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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|
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2026-06-14 00:37:10.323[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s12.mp4 (7594820 bytes)
|
|
2026-06-14 00:37:10.325[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s12
|
|
2026-06-14 00:37:10.326[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s08
|
|
2026-06-14 00:37:10.327[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s08', 'prompt': 'Beautiful sunset over the ocean, silhouette of a person standing on a pier, contemplative mood, orange and purple sky', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6845872, 'finished_at': 1781367803.4878805, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s08', 'status': 'completed', 'video_url': '/idfile?path=dielv_s08.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s08.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 1374010, 'prompt': 'Beautiful sunset over the ocean, silhouette of a person standing on a pier, contemplative mood, oran', 'seed': 2087212057}, 'task_id': 'dielv_s08', 'started_at': 1781367633.7020593}
|
|
2026-06-14 00:37:10.327[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:39:26.362[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
|
|
2026-06-14 00:39:58.115[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s08.mp4 (1730393 bytes)
|
|
2026-06-14 00:39:58.118[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s08
|
|
2026-06-14 00:39:58.118[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s04
|
|
2026-06-14 00:39:58.119[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s04', 'prompt': 'A young musician performing on a small street stage, strumming guitar, people walking by, urban evening golden hour', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6836863, 'finished_at': 1781367974.7463224, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s04', 'status': 'completed', 'video_url': '/idfile?path=dielv_s04.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s04.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 9898755, 'prompt': 'A young musician performing on a small street stage, strumming guitar, people walking by, urban even', 'seed': 2087212057}, 'task_id': 'dielv_s04', 'started_at': 1781367803.490727}
|
|
2026-06-14 00:39:58.120[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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|
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2026-06-14 00:42:47.797[webapp][debug][/data/ymq/wan22-service/workers/generate.py:114]Video generated: /data/ymq/wan22-outputs/dielv_s04.mp4 (9618652 bytes)
|
|
2026-06-14 00:42:47.799[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s04
|
|
2026-06-14 00:42:47.799[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s22
|
|
2026-06-14 00:42:47.800[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s22', 'prompt': 'Final shot: sunset beach with guitar leaning against driftwood, waves gently washing, musical legacy, peaceful ending, warm tones fading', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8583353, 'task_id': 'dielv_hd_s22'}
|
|
2026-06-14 00:42:47.800[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
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2026-06-14 00:43:08.141[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 1.99 GiB. GPU 0 has a total capacity of 23.52 GiB of which 1.69 GiB is free. Including non-PyTorch memory, this process has 21.82 GiB memory in use. Of the allocated memory 21.21 GiB is allocated by PyTorch, and 74.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 384, in t2v
|
|
noise_pred_cond = self.model(
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
|
|
return self._call_impl(*args, **kwargs)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
|
|
return forward_call(*args, **kwargs)
|
|
File "/data/ymq/wan22-service/repo/wan/modules/model.py", line 490, in forward
|
|
x = block(x, **kwargs)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1779, in _wrapped_call_impl
|
|
return self._call_impl(*args, **kwargs)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1790, in _call_impl
|
|
return forward_call(*args, **kwargs)
|
|
File "/data/ymq/wan22-service/repo/wan/modules/model.py", line 239, in forward
|
|
e = (self.modulation.unsqueeze(0) + e).chunk(6, dim=2)
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 1.99 GiB. GPU 0 has a total capacity of 23.52 GiB of which 1.69 GiB is free. Including non-PyTorch memory, this process has 21.82 GiB memory in use. Of the allocated memory 21.21 GiB is allocated by PyTorch, and 74.81 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:08.143[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s22
|
|
2026-06-14 00:43:08.143[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s21
|
|
2026-06-14 00:43:08.144[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s21', 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, aerial drone shot, blue green water', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8581762, 'task_id': 'dielv_hd_s21'}
|
|
2026-06-14 00:43:08.145[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.041[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.043[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s21
|
|
2026-06-14 00:43:10.043[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s19
|
|
2026-06-14 00:43:10.044[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s19', 'prompt': 'An elderly musician sitting on a beach chair playing guitar at sunrise, peaceful expression, lifetime of music, warm golden light', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8578477, 'task_id': 'dielv_hd_s19'}
|
|
2026-06-14 00:43:10.044[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.055[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.056[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s19
|
|
2026-06-14 00:43:10.056[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s18
|
|
2026-06-14 00:43:10.057[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s18', 'prompt': 'A lighthouse beam sweeping across dark ocean waters, rhythmic rotation, beacon in the night, metaphor for persistence', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8576858, 'task_id': 'dielv_hd_s18'}
|
|
2026-06-14 00:43:10.057[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.067[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.068[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s18
|
|
2026-06-14 00:43:10.068[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s17
|
|
2026-06-14 00:43:10.068[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s17', 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature symphony, epic wide shot', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.857527, 'task_id': 'dielv_hd_s17'}
|
|
2026-06-14 00:43:10.069[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.080[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.080[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s17
|
|
2026-06-14 00:43:10.081[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s16
|
|
2026-06-14 00:43:10.081[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s16', 'prompt': 'Moonlight reflecting on calm ocean surface, gentle ripples creating patterns, serene night scene, silver blue tones, meditative', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8573673, 'task_id': 'dielv_hd_s16'}
|
|
2026-06-14 00:43:10.082[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.091[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.092[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s16
|
|
2026-06-14 00:43:10.092[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s15
|
|
2026-06-14 00:43:10.093[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s15', 'prompt': 'A crowd of people singing together at an outdoor concert, everyone swaying to the same melody, unity in music, golden hour', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8572009, 'task_id': 'dielv_hd_s15'}
|
|
2026-06-14 00:43:10.093[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.103[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.104[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s15
|
|
2026-06-14 00:43:10.104[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s14
|
|
2026-06-14 00:43:10.105[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s14', 'prompt': 'Close-up of hands writing music notes on paper, pen moving steadily, warm desk lamp, creative flow, vintage paper texture', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8570404, 'task_id': 'dielv_hd_s14'}
|
|
2026-06-14 00:43:10.105[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.116[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.116[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s14
|
|
2026-06-14 00:43:10.117[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s13
|
|
2026-06-14 00:43:10.117[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s13', 'prompt': 'A middle-aged musician performing in a park, surrounded by trees, children listening, warm afternoon sunlight, simple joy', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8568761, 'task_id': 'dielv_hd_s13'}
|
|
2026-06-14 00:43:10.118[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.127[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.128[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s13
|
|
2026-06-14 00:43:10.128[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s12
|
|
2026-06-14 00:43:10.129[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s12', 'prompt': 'Waves continuously hitting rocky shores, time-lapse style showing the repetitive rhythm of nature, powerful yet calming', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8567135, 'task_id': 'dielv_hd_s12'}
|
|
2026-06-14 00:43:10.129[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.139[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.140[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s12
|
|
2026-06-14 00:43:10.140[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s11
|
|
2026-06-14 00:43:10.140[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s11', 'prompt': 'The same musician sitting quietly by a window with an acoustic guitar, simple and peaceful, natural daylight, returning to roots', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8565538, 'task_id': 'dielv_hd_s11'}
|
|
2026-06-14 00:43:10.141[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.151[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.152[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s11
|
|
2026-06-14 00:43:10.153[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s10
|
|
2026-06-14 00:43:10.153[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s10', 'prompt': 'A modern music studio with synthesizers and screens, a musician experimenting with new sounds, blue LED lighting, creative exploration', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8563745, 'task_id': 'dielv_hd_s10'}
|
|
2026-06-14 00:43:10.153[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.163[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.164[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s10
|
|
2026-06-14 00:43:10.164[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s09
|
|
2026-06-14 00:43:10.165[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s09', 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, reflective mood, night scene', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8562067, 'task_id': 'dielv_hd_s09'}
|
|
2026-06-14 00:43:10.165[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.175[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.176[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s09
|
|
2026-06-14 00:43:10.176[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s08
|
|
2026-06-14 00:43:10.177[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s08', 'prompt': 'Beautiful sunset over the ocean, silhouette of a person standing on a pier, contemplative mood, orange and purple sky', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8560233, 'task_id': 'dielv_hd_s08'}
|
|
2026-06-14 00:43:10.177[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.187[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.188[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s08
|
|
2026-06-14 00:43:10.188[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s07
|
|
2026-06-14 00:43:10.189[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s07', 'prompt': 'Musical notes and sound waves visualized as colorful light trails flowing through a concert hall, abstract artistic visualization', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.855862, 'task_id': 'dielv_hd_s07'}
|
|
2026-06-14 00:43:10.189[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.199[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.200[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s07
|
|
2026-06-14 00:43:10.200[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s06
|
|
2026-06-14 00:43:10.201[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s06', 'prompt': 'Close-up of guitar strings being played, fingers moving gracefully, warm stage lighting, musical passion, shallow depth of field', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8557, 'task_id': 'dielv_hd_s06'}
|
|
2026-06-14 00:43:10.201[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.211[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.212[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s06
|
|
2026-06-14 00:43:10.212[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s05
|
|
2026-06-14 00:43:10.213[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s05', 'prompt': 'A cozy bar with warm lighting, a young singer performing on a small stage, audience clapping along, intimate concert atmosphere', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8555326, 'task_id': 'dielv_hd_s05'}
|
|
2026-06-14 00:43:10.213[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.223[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.224[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s05
|
|
2026-06-14 00:43:10.224[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s04
|
|
2026-06-14 00:43:10.225[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s04', 'prompt': 'A young musician performing on a small street stage, strumming guitar, people walking by, urban evening golden hour', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.855363, 'task_id': 'dielv_hd_s04'}
|
|
2026-06-14 00:43:10.225[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.235[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.236[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s04
|
|
2026-06-14 00:43:10.236[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s03
|
|
2026-06-14 00:43:10.237[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s03', 'prompt': 'A teenage boy learning to play acoustic guitar on a wooden porch, warm indoor lighting, focused expression, coming of age', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8551948, 'task_id': 'dielv_hd_s03'}
|
|
2026-06-14 00:43:10.237[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.247[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.248[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s03
|
|
2026-06-14 00:43:10.248[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s02
|
|
2026-06-14 00:43:10.248[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s02', 'prompt': 'An old tree on a hilltop under moonlight, cicadas singing in the night, peaceful rural summer evening, soft blue tones', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.8550203, 'task_id': 'dielv_hd_s02'}
|
|
2026-06-14 00:43:10.249[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.259[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.260[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s02
|
|
2026-06-14 00:43:10.260[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s01
|
|
2026-06-14 00:43:10.260[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s01', 'prompt': 'Close-up of ocean waves crashing on shore, seashells scattered on wet sand, summer afternoon, peaceful atmosphere', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.85481, 'task_id': 'dielv_hd_s01'}
|
|
2026-06-14 00:43:10.261[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.271[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.272[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s01
|
|
2026-06-14 00:43:10.272[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_hd_s00
|
|
2026-06-14 00:43:10.273[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_hd_s00', 'prompt': 'A young child standing on a sandy beach at sunset, listening to ocean waves, warm golden light, cinematic wide shot', 'size': '1280*704', 'frame_num': 129}, 'status': 'PENDING', 'created_at': 1781368938.84919, 'task_id': 'dielv_hd_s00'}
|
|
2026-06-14 00:43:10.273[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.283[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.284[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_hd_s00
|
|
2026-06-14 00:43:10.284[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s00
|
|
2026-06-14 00:43:10.285[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s00', 'prompt': 'A young child standing on a sandy beach at sunset, listening to ocean waves, warm golden light, cinematic wide shot', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.677895, 'finished_at': 1781368145.7620416, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s00', 'status': 'completed', 'video_url': '/idfile?path=dielv_s00.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s00.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 5043407, 'prompt': 'A young child standing on a sandy beach at sunset, listening to ocean waves, warm golden light, cine', 'seed': 2087212057}, 'task_id': 'dielv_s00', 'started_at': 1781367974.7489202}
|
|
2026-06-14 00:43:10.285[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.295[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.296[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s00
|
|
2026-06-14 00:43:10.296[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s22
|
|
2026-06-14 00:43:10.297[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s22', 'prompt': 'Final shot: sunset beach with guitar leaning against driftwood, waves gently washing, musical legacy, peaceful ending, warm tones fading', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6873186, 'finished_at': 1781368145.763598, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s22', 'status': 'completed', 'video_url': '/idfile?path=dielv_s22.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s22.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 4991745, 'prompt': 'Final shot: sunset beach with guitar leaning against driftwood, waves gently washing, musical legacy', 'seed': 1789236950}, 'task_id': 'dielv_s22', 'started_at': 1781367975.2647176}
|
|
2026-06-14 00:43:10.297[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.307[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.308[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s22
|
|
2026-06-14 00:43:10.308[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s21
|
|
2026-06-14 00:43:10.309[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s21', 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, aerial drone shot, blue green water', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6871283, 'finished_at': 1781368153.2746918, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s21', 'status': 'completed', 'video_url': '/idfile?path=dielv_s21.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s21.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 8247910, 'prompt': 'Ocean waves forming perfect spiraling patterns when viewed from above, nature mathematical beauty, a', 'seed': 1574215179}, 'task_id': 'dielv_s21', 'started_at': 1781367982.3373256}
|
|
2026-06-14 00:43:10.309[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.319[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.320[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s21
|
|
2026-06-14 00:43:10.320[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s20
|
|
2026-06-14 00:43:10.321[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s20', 'prompt': 'A young child sitting next to the elderly musician on the beach, learning to play, generational passing of music, heartwarming', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6869352, 'finished_at': 1781368297.7926195, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s20', 'status': 'completed', 'video_url': '/idfile?path=dielv_s20.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s20.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 2948397, 'prompt': 'A young child sitting next to the elderly musician on the beach, learning to play, generational pass', 'seed': 56748582}, 'task_id': 'dielv_s20', 'started_at': 1781368130.458442}
|
|
2026-06-14 00:43:10.321[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.331[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.332[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s20
|
|
2026-06-14 00:43:10.332[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s19
|
|
2026-06-14 00:43:10.333[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s19', 'prompt': 'An elderly musician sitting on a beach chair playing guitar at sunrise, peaceful expression, lifetime of music, warm golden light', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6867406, 'finished_at': 1781368317.0752552, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s19', 'status': 'completed', 'video_url': '/idfile?path=dielv_s19.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s19.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 3253145, 'prompt': 'An elderly musician sitting on a beach chair playing guitar at sunrise, peaceful expression, lifetim', 'seed': 2087212057}, 'task_id': 'dielv_s19', 'started_at': 1781368145.7649589}
|
|
2026-06-14 00:43:10.333[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.343[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.344[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s19
|
|
2026-06-14 00:43:10.344[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s18
|
|
2026-06-14 00:43:10.345[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s18', 'prompt': 'A lighthouse beam sweeping across dark ocean waters, rhythmic rotation, beacon in the night, metaphor for persistence', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.686545, 'finished_at': 1781368313.7690911, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s18', 'status': 'completed', 'video_url': '/idfile?path=dielv_s18.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s18.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 3594139, 'prompt': 'A lighthouse beam sweeping across dark ocean waters, rhythmic rotation, beacon in the night, metapho', 'seed': 1789236950}, 'task_id': 'dielv_s18', 'started_at': 1781368145.7664058}
|
|
2026-06-14 00:43:10.345[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.355[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.356[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s18
|
|
2026-06-14 00:43:10.356[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s17
|
|
2026-06-14 00:43:10.357[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s17', 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature symphony, epic wide shot', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6863546, 'finished_at': 1781368323.642458, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s17', 'status': 'completed', 'video_url': '/idfile?path=dielv_s17.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s17.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 6598791, 'prompt': 'Wind blowing through tall grass and trees on a coastal cliff, clouds moving across the sky, nature s', 'seed': 1574215179}, 'task_id': 'dielv_s17', 'started_at': 1781368153.277429}
|
|
2026-06-14 00:43:10.357[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.367[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.368[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s17
|
|
2026-06-14 00:43:10.368[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s16
|
|
2026-06-14 00:43:10.369[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s16', 'prompt': 'Moonlight reflecting on calm ocean surface, gentle ripples creating patterns, serene night scene, silver blue tones, meditative', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6861644, 'finished_at': 1781368464.1157703, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s16', 'status': 'completed', 'video_url': '/idfile?path=dielv_s16.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s16.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 4959999, 'prompt': 'Moonlight reflecting on calm ocean surface, gentle ripples creating patterns, serene night scene, si', 'seed': 56748582}, 'task_id': 'dielv_s16', 'started_at': 1781368297.7955174}
|
|
2026-06-14 00:43:10.369[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.379[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.380[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s16
|
|
2026-06-14 00:43:10.380[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s15
|
|
2026-06-14 00:43:10.381[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s15', 'prompt': 'A crowd of people singing together at an outdoor concert, everyone swaying to the same melody, unity in music, golden hour', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.685966, 'finished_at': 1781368481.3264537, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s15', 'status': 'completed', 'video_url': '/idfile?path=dielv_s15.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s15.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 7683800, 'prompt': 'A crowd of people singing together at an outdoor concert, everyone swaying to the same melody, unity', 'seed': 1789236950}, 'task_id': 'dielv_s15', 'started_at': 1781368313.7721217}
|
|
2026-06-14 00:43:10.381[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.391[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.392[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s15
|
|
2026-06-14 00:43:10.392[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s14
|
|
2026-06-14 00:43:10.393[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s14', 'prompt': 'Close-up of hands writing music notes on paper, pen moving steadily, warm desk lamp, creative flow, vintage paper texture', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6857574, 'finished_at': 1781368488.1934762, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s14', 'status': 'completed', 'video_url': '/idfile?path=dielv_s14.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s14.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 2348892, 'prompt': 'Close-up of hands writing music notes on paper, pen moving steadily, warm desk lamp, creative flow, ', 'seed': 2087212057}, 'task_id': 'dielv_s14', 'started_at': 1781368317.0779226}
|
|
2026-06-14 00:43:10.394[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.403[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.404[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s14
|
|
2026-06-14 00:43:10.404[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s13
|
|
2026-06-14 00:43:10.405[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s13', 'prompt': 'A middle-aged musician performing in a park, surrounded by trees, children listening, warm afternoon sunlight, simple joy', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6855578, 'finished_at': 1781368494.8031945, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s13', 'status': 'completed', 'video_url': '/idfile?path=dielv_s13.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s13.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 7526481, 'prompt': 'A middle-aged musician performing in a park, surrounded by trees, children listening, warm afternoon', 'seed': 1574215179}, 'task_id': 'dielv_s13', 'started_at': 1781368323.6455007}
|
|
2026-06-14 00:43:10.405[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.415[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.416[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s13
|
|
2026-06-14 00:43:10.416[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s12
|
|
2026-06-14 00:43:10.417[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s12', 'prompt': 'Waves continuously hitting rocky shores, time-lapse style showing the repetitive rhythm of nature, powerful yet calming', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6853685, 'finished_at': 1781368630.3239963, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s12', 'status': 'completed', 'video_url': '/idfile?path=dielv_s12.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s12.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 7594820, 'prompt': 'Waves continuously hitting rocky shores, time-lapse style showing the repetitive rhythm of nature, p', 'seed': 56748582}, 'task_id': 'dielv_s12', 'started_at': 1781368464.1177084}
|
|
2026-06-14 00:43:10.417[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.427[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.428[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s12
|
|
2026-06-14 00:43:10.428[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s11
|
|
2026-06-14 00:43:10.429[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s11', 'prompt': 'The same musician sitting quietly by a window with an acoustic guitar, simple and peaceful, natural daylight, returning to roots', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6851797, 'finished_at': 1781368650.994856, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s11', 'status': 'completed', 'video_url': '/idfile?path=dielv_s11.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s11.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 1687544, 'prompt': 'The same musician sitting quietly by a window with an acoustic guitar, simple and peaceful, natural ', 'seed': 1789236950}, 'task_id': 'dielv_s11', 'started_at': 1781368481.3292315}
|
|
2026-06-14 00:43:10.429[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.439[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.440[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s11
|
|
2026-06-14 00:43:10.440[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s10
|
|
2026-06-14 00:43:10.441[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s10', 'prompt': 'A modern music studio with synthesizers and screens, a musician experimenting with new sounds, blue LED lighting, creative exploration', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.684984, 'finished_at': 1781368659.4676297, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s10', 'status': 'completed', 'video_url': '/idfile?path=dielv_s10.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s10.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 5248297, 'prompt': 'A modern music studio with synthesizers and screens, a musician experimenting with new sounds, blue ', 'seed': 2087212057}, 'task_id': 'dielv_s10', 'started_at': 1781368488.1960354}
|
|
2026-06-14 00:43:10.441[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.451[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.452[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s10
|
|
2026-06-14 00:43:10.452[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s09
|
|
2026-06-14 00:43:10.453[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s09', 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, reflective mood, night scene', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6847923, 'finished_at': 1781368665.592558, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s09', 'status': 'completed', 'video_url': '/idfile?path=dielv_s09.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s09.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 5499070, 'prompt': 'An adult musician walking through a busy city street with neon signs, searching for inspiration, ref', 'seed': 1574215179}, 'task_id': 'dielv_s09', 'started_at': 1781368494.8068867}
|
|
2026-06-14 00:43:10.453[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.463[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.464[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s09
|
|
2026-06-14 00:43:10.464[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s08
|
|
2026-06-14 00:43:10.465[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s08', 'prompt': 'Beautiful sunset over the ocean, silhouette of a person standing on a pier, contemplative mood, orange and purple sky', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6845872, 'finished_at': 1781368798.115873, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s08', 'status': 'completed', 'video_url': '/idfile?path=dielv_s08.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s08.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 1730393, 'prompt': 'Beautiful sunset over the ocean, silhouette of a person standing on a pier, contemplative mood, oran', 'seed': 56748582}, 'task_id': 'dielv_s08', 'started_at': 1781368630.327041}
|
|
2026-06-14 00:43:10.465[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.475[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.476[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s08
|
|
2026-06-14 00:43:10.476[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s07
|
|
2026-06-14 00:43:10.477[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s07', 'prompt': 'Musical notes and sound waves visualized as colorful light trails flowing through a concert hall, abstract artistic visualization', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6843948, 'finished_at': 1781368819.3826573, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s07', 'status': 'completed', 'video_url': '/idfile?path=dielv_s07.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s07.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 8004551, 'prompt': 'Musical notes and sound waves visualized as colorful light trails flowing through a concert hall, ab', 'seed': 1789236950}, 'task_id': 'dielv_s07', 'started_at': 1781368650.9977145}
|
|
2026-06-14 00:43:10.477[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.487[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.488[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s07
|
|
2026-06-14 00:43:10.488[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s06
|
|
2026-06-14 00:43:10.489[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s06', 'prompt': 'Close-up of guitar strings being played, fingers moving gracefully, warm stage lighting, musical passion, shallow depth of field', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6841996, 'finished_at': 1781368830.647741, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s06', 'status': 'completed', 'video_url': '/idfile?path=dielv_s06.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s06.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 4551493, 'prompt': 'Close-up of guitar strings being played, fingers moving gracefully, warm stage lighting, musical pas', 'seed': 2087212057}, 'task_id': 'dielv_s06', 'started_at': 1781368659.470447}
|
|
2026-06-14 00:43:10.489[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.499[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
|
|
2026-06-14 00:43:10.500[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s06
|
|
2026-06-14 00:43:10.500[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s05
|
|
2026-06-14 00:43:10.501[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s05', 'prompt': 'A cozy bar with warm lighting, a young singer performing on a small stage, audience clapping along, intimate concert atmosphere', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6840105, 'finished_at': 1781368836.7919676, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s05', 'status': 'completed', 'video_url': '/idfile?path=dielv_s05.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s05.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 5180729, 'prompt': 'A cozy bar with warm lighting, a young singer performing on a small stage, audience clapping along, ', 'seed': 1574215179}, 'task_id': 'dielv_s05', 'started_at': 1781368665.59576}
|
|
2026-06-14 00:43:10.501[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
|
|
2026-06-14 00:43:10.511[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
|
|
Traceback (most recent call last):
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
|
|
result = await loop.run_in_executor(None, _infer)
|
|
File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
|
|
result = self.fn(*self.args, **self.kwargs)
|
|
File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
|
|
return engine.generate(
|
|
File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
|
|
video = self.pipeline.generate(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
|
|
return self.t2v(
|
|
File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
|
|
self.text_encoder.model.to(self.device)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
|
|
return self._apply(convert)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
|
|
module._apply(fn)
|
|
[Previous line repeated 2 more times]
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
|
|
param_applied = fn(param)
|
|
File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
|
|
return t.to(
|
|
torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
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2026-06-14 00:43:10.512[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s05
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2026-06-14 00:43:10.512[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:144]get task_id=dielv_s04
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2026-06-14 00:43:10.513[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:148]task={'payload': {'task_type': 'generate_video', 'task_id': 'dielv_s04', 'prompt': 'A young musician performing on a small street stage, strumming guitar, people walking by, urban evening golden hour', 'size': '832*480', 'frame_num': 129}, 'created_at': 1781366061.6836863, 'finished_at': 1781368967.7975943, 'status': 'SUCCEEDED', 'result': {'task_id': 'dielv_s04', 'status': 'completed', 'video_url': '/idfile?path=dielv_s04.mp4', 'video_path': '/data/ymq/wan22-outputs/dielv_s04.mp4', 'size': '832*480', 'frame_num': 129, 'file_size': 9618652, 'prompt': 'A young musician performing on a small street stage, strumming guitar, people walking by, urban even', 'seed': 56748582}, 'task_id': 'dielv_s04', 'started_at': 1781368798.1197057}
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2026-06-14 00:43:10.513[webapp][debug][/data/ymq/wan22-service/ah.py:20]Wan22Tasks processing: type=generate_video
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2026-06-14 00:43:10.523[webapp][exception][/data/ymq/wan22-service/workers/generate.py:129]Generation error: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
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Traceback (most recent call last):
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File "/data/ymq/wan22-service/workers/generate.py", line 104, in run_generate
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result = await loop.run_in_executor(None, _infer)
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File "/usr/lib/python3.10/concurrent/futures/thread.py", line 58, in run
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result = self.fn(*self.args, **self.kwargs)
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File "/data/ymq/wan22-service/workers/generate.py", line 93, in _infer
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return engine.generate(
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File "/data/ymq/wan22-service/workers/wan22_wrapper.py", line 190, in generate
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video = self.pipeline.generate(
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File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 229, in generate
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return self.t2v(
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File "/data/ymq/wan22-service/repo/wan/textimage2video.py", line 302, in t2v
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self.text_encoder.model.to(self.device)
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1384, in to
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return self._apply(convert)
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
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module._apply(fn)
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
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module._apply(fn)
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 934, in _apply
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module._apply(fn)
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[Previous line repeated 2 more times]
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 965, in _apply
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param_applied = fn(param)
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File "/data/ymq/wan22-service/py3/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1370, in convert
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return t.to(
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torch.OutOfMemoryError: CUDA out of memory. Tried to allocate 80.00 MiB. GPU 0 has a total capacity of 23.52 GiB of which 47.62 MiB is free. Including non-PyTorch memory, this process has 23.46 GiB memory in use. Of the allocated memory 22.88 GiB is allocated by PyTorch, and 42.94 MiB is reserved by PyTorch but unallocated. If reserved but unallocated memory is large try setting PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True to avoid fragmentation. See documentation for Memory Management (https://docs.pytorch.org/docs/stable/notes/cuda.html#optimizing-memory-usage-with-pytorch-cuda-alloc-conf)
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2026-06-14 00:43:10.524[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:187][worker 0] finished dielv_s04
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2026-06-14 00:44:26.366[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:49:26.369[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:54:26.370[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 00:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 00:59:26.371[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:04:26.375[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:09:26.377[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:14:26.378[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:19:26.383[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:24:26.387[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:29:26.390[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:34:26.390[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:39:26.394[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:44:26.397[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:49:26.398[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:54:26.403[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 01:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 01:59:26.407[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:04:26.409[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:09:26.410[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:14:26.414[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:19:26.417[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:24:26.418[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:29:26.418[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:34:26.422[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:39:26.424[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:44:26.425[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:49:26.429[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:54:26.432[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 02:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 02:59:26.434[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:04:26.435[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:09:26.440[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:14:26.443[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:19:26.444[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:24:26.449[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:29:26.453[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:34:26.455[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:39:26.455[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:44:26.459[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:49:26.462[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:54:26.463[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 03:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 03:59:26.468[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:04:26.470[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:09:26.473[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:14:26.473[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:19:26.477[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:24:26.480[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:29:26.481[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:34:26.486[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:39:26.490[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:44:26.492[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:49:26.493[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:54:26.497[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 04:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 04:59:26.501[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:04:26.502[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:09:26.502[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:14:26.507[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:19:26.509[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:24:26.510[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:29:26.515[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:34:26.518[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:39:26.520[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:44:26.521[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:49:26.525[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:54:26.528[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 05:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 05:59:26.529[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:04:26.534[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:09:26.538[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:14:26.541[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:19:26.542[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:24:26.546[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:29:26.549[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:34:26.551[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:39:26.555[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:44:26.559[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:49:26.561[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:54:26.562[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 06:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 06:59:26.566[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:04:26.569[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:09:26.571[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:14:26.571[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:19:26.575[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:24:26.577[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:29:26.578[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:34:26.583[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:39:26.586[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:44:26.588[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:49:26.589[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:54:26.593[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 07:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 07:59:26.596[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:04:26.598[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:09:26.598[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:14:26.599[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:19:26.601[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:24:26.602[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:29:26.606[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:34:26.608[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:39:26.609[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:44:26.614[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:49:26.617[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:54:26.619[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 08:58:07.786[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 08:59:26.619[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:04:26.623[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:09:26.626[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:14:26.627[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:19:26.633[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:24:26.637[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:29:26.639[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:34:26.640[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:39:26.645[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:44:26.648[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:49:26.649[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:54:26.649[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 09:58:07.787[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 09:59:26.653[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:04:26.656[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:09:26.656[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:14:26.661[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:19:26.664[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:24:26.666[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:29:26.665[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:34:26.666[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:39:26.668[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:44:26.669[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:49:26.673[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:54:26.676[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 10:58:07.788[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 10:59:26.677[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:04:26.677[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:09:26.681[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:14:26.684[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:19:26.685[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:24:26.690[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:29:26.693[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:34:26.696[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:39:26.695[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:44:26.698[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:49:26.700[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:54:26.701[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 11:58:07.787[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 11:59:26.706[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:04:26.709[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:09:26.710[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:14:26.711[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:19:26.715[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:24:26.718[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:29:26.719[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:34:26.724[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:39:26.726[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:44:26.727[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:49:26.728[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:54:26.731[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 12:58:07.787[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 12:59:26.733[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:04:26.734[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:09:26.738[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:14:26.741[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:19:26.743[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:24:26.743[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:29:26.747[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:34:26.750[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:39:26.751[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:44:26.756[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:49:26.758[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:54:26.760[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 13:58:07.788[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 13:59:26.760[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:04:26.763[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:09:26.766[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:14:26.766[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:19:26.771[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:24:26.774[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:29:26.776[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:34:26.776[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:39:26.780[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:44:26.782[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:49:26.783[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:54:26.788[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 14:58:07.787[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 14:59:26.790[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:04:26.792[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:09:26.792[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:14:26.797[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:19:26.799[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:24:26.800[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:29:26.805[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:34:26.809[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:39:26.811[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:44:26.811[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:49:26.815[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:54:26.818[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 15:58:07.787[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:39]cleanup_expired_tasks() called ...
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2026-06-14 15:59:26.819[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 16:04:26.824[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 16:09:26.828[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 16:14:26.830[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 16:19:26.830[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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2026-06-14 16:24:26.834[webapp][debug][/data/ymq/wan22-service/py3/lib/python3.10/site-packages/longtasks/longtasks.py:104]recover_stuck_tasks() called
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