Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name alexdaoud-trainer-bagir-8911-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-8911-v1-mkmlizer to finish
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ _____ __ __ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ /___/ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ Version: 0.11.12 ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ https://mk1.ai ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ The license key for the current software has been verified as ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ belonging to: ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ Chai Research Corp. ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-8911-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-8911-v1-mkmlizer: Downloaded to shared memory in 31.981s
alexdaoud-trainer-bagir-8911-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmptc3c2ffn, device:0
alexdaoud-trainer-bagir-8911-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-8911-v1-mkmlizer: quantized model in 85.762s
alexdaoud-trainer-bagir-8911-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-108 in 117.743s
alexdaoud-trainer-bagir-8911-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-8911-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-8911-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1
alexdaoud-trainer-bagir-8911-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1/config.json
alexdaoud-trainer-bagir-8911-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1/special_tokens_map.json
alexdaoud-trainer-bagir-8911-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1/tokenizer_config.json
alexdaoud-trainer-bagir-8911-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1/tokenizer.json
alexdaoud-trainer-bagir-8911-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-8911-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-8911-v1-mkmlizer:
Loading 0: 0%| | 0/291 [00:00<?, ?it/s]
Loading 0: 1%| | 3/291 [00:00<00:56, 5.08it/s]
Loading 0: 1%|▏ | 4/291 [00:01<01:31, 3.12it/s]
Loading 0: 2%|▏ | 5/291 [00:01<02:03, 2.32it/s]
Loading 0: 3%|▎ | 8/291 [00:02<01:03, 4.43it/s]
Loading 0: 3%|▎ | 9/291 [00:02<01:02, 4.50it/s]
Loading 0: 3%|▎ | 10/291 [00:02<00:54, 5.13it/s]
Loading 0: 4%|▍ | 12/291 [00:02<01:05, 4.28it/s]
Loading 0: 4%|▍ | 13/291 [00:03<01:26, 3.21it/s]
Loading 0: 5%|▍ | 14/291 [00:04<01:49, 2.52it/s]
Loading 0: 6%|▌ | 17/291 [00:04<01:03, 4.33it/s]
Loading 0: 6%|▌ | 18/291 [00:04<00:59, 4.57it/s]
Loading 0: 7%|▋ | 19/291 [00:04<00:52, 5.16it/s]
Loading 0: 7%|▋ | 21/291 [00:05<01:02, 4.32it/s]
Loading 0: 8%|▊ | 22/291 [00:05<01:22, 3.26it/s]
Loading 0: 8%|▊ | 23/291 [00:06<01:45, 2.53it/s]
Loading 0: 9%|▉ | 26/291 [00:06<01:01, 4.32it/s]
Loading 0: 9%|▉ | 27/291 [00:06<00:57, 4.56it/s]
Loading 0: 10%|▉ | 28/291 [00:07<00:51, 5.09it/s]
Loading 0: 10%|█ | 30/291 [00:07<01:00, 4.29it/s]
Loading 0: 11%|█ | 31/291 [00:08<01:20, 3.25it/s]
Loading 0: 11%|█ | 32/291 [00:08<01:41, 2.55it/s]
Loading 0: 12%|█▏ | 35/291 [00:09<00:59, 4.33it/s]
Loading 0: 12%|█▏ | 36/291 [00:09<00:55, 4.58it/s]
Loading 0: 13%|█▎ | 37/291 [00:09<00:49, 5.16it/s]
Loading 0: 13%|█▎ | 39/291 [00:09<00:58, 4.33it/s]
Loading 0: 14%|█▎ | 40/291 [00:10<01:16, 3.27it/s]
Loading 0: 14%|█▍ | 41/291 [00:11<01:37, 2.57it/s]
Loading 0: 15%|█▌ | 44/291 [00:11<00:56, 4.38it/s]
Loading 0: 15%|█▌ | 45/291 [00:11<00:53, 4.62it/s]
Loading 0: 16%|█▌ | 46/291 [00:11<00:47, 5.21it/s]
Loading 0: 16%|█▋ | 48/291 [00:12<00:55, 4.36it/s]
Loading 0: 17%|█▋ | 49/291 [00:12<01:13, 3.28it/s]
Loading 0: 17%|█▋ | 50/291 [00:13<01:32, 2.60it/s]
Loading 0: 18%|█▊ | 53/291 [00:13<00:53, 4.42it/s]
Loading 0: 19%|█▊ | 54/291 [00:13<00:50, 4.66it/s]
Loading 0: 19%|█▉ | 55/291 [00:13<00:44, 5.26it/s]
Loading 0: 20%|█▉ | 57/291 [00:14<00:53, 4.39it/s]
Loading 0: 20%|█▉ | 58/291 [00:15<01:10, 3.30it/s]
Loading 0: 20%|██ | 59/291 [00:15<01:29, 2.59it/s]
Loading 0: 21%|██▏ | 62/291 [00:15<00:51, 4.45it/s]
Loading 0: 22%|██▏ | 63/291 [00:16<00:48, 4.69it/s]
Loading 0: 22%|██▏ | 64/291 [00:16<00:42, 5.29it/s]
Loading 0: 23%|██▎ | 66/291 [00:16<00:51, 4.36it/s]
Loading 0: 23%|██▎ | 67/291 [00:17<01:08, 3.28it/s]
Loading 0: 23%|██▎ | 68/291 [00:18<01:27, 2.56it/s]
Loading 0: 24%|██▍ | 71/291 [00:18<00:50, 4.34it/s]
Loading 0: 25%|██▍ | 72/291 [00:18<00:47, 4.57it/s]
Loading 0: 25%|██▌ | 73/291 [00:18<00:42, 5.13it/s]
Loading 0: 26%|██▌ | 75/291 [00:19<00:50, 4.31it/s]
Loading 0: 26%|██▌ | 76/291 [00:19<01:06, 3.25it/s]
Loading 0: 26%|██▋ | 77/291 [00:20<01:22, 2.58it/s]
Loading 0: 27%|██▋ | 80/291 [00:20<00:47, 4.40it/s]
Loading 0: 28%|██▊ | 81/291 [00:20<00:45, 4.63it/s]
Loading 0: 28%|██▊ | 82/291 [00:20<00:40, 5.16it/s]
Loading 0: 29%|██▊ | 83/291 [00:21<00:40, 5.17it/s]
Loading 0: 29%|██▉ | 84/291 [00:21<01:00, 3.42it/s]
Loading 0: 29%|██▉ | 85/291 [00:22<01:15, 2.72it/s]
Loading 0: 30%|██▉ | 86/291 [00:22<01:30, 2.26it/s]
Loading 0: 31%|███ | 89/291 [00:23<00:48, 4.20it/s]
Loading 0: 31%|███ | 90/291 [00:23<00:44, 4.48it/s]
Loading 0: 31%|███▏ | 91/291 [00:23<00:39, 5.06it/s]
Loading 0: 32%|███▏ | 93/291 [00:23<00:46, 4.27it/s]
Loading 0: 32%|███▏ | 94/291 [00:24<01:01, 3.21it/s]
Loading 0: 33%|███▎ | 95/291 [00:25<01:16, 2.55it/s]
Loading 0: 34%|███▎ | 98/291 [00:25<00:44, 4.36it/s]
Loading 0: 34%|███▍ | 99/291 [00:25<00:41, 4.60it/s]
Loading 0: 34%|███▍ | 100/291 [00:25<00:36, 5.21it/s]
Loading 0: 35%|███▌ | 102/291 [00:26<00:43, 4.35it/s]
Loading 0: 35%|███▌ | 103/291 [00:26<00:57, 3.28it/s]
Loading 0: 36%|███▌ | 104/291 [00:27<01:12, 2.58it/s]
Loading 0: 37%|███▋ | 107/291 [00:27<00:41, 4.44it/s]
Loading 0: 37%|███▋ | 108/291 [00:27<00:39, 4.67it/s]
Loading 0: 38%|███▊ | 110/291 [00:27<00:28, 6.42it/s]
Loading 0: 38%|███▊ | 112/291 [00:29<00:53, 3.33it/s]
Loading 0: 39%|███▉ | 113/291 [00:29<01:05, 2.71it/s]
Loading 0: 40%|███▉ | 116/291 [00:29<00:40, 4.28it/s]
Loading 0: 40%|████ | 117/291 [00:30<00:38, 4.51it/s]
Loading 0: 41%|████ | 118/291 [00:30<00:34, 5.07it/s]
Loading 0: 41%|████ | 120/291 [00:30<00:39, 4.32it/s]
Loading 0: 42%|████▏ | 121/291 [00:31<00:51, 3.30it/s]
Loading 0: 42%|████▏ | 122/291 [00:31<01:04, 2.62it/s]
Loading 0: 43%|████▎ | 125/291 [00:32<00:37, 4.40it/s]
Loading 0: 43%|████▎ | 126/291 [00:32<00:35, 4.64it/s]
Loading 0: 44%|████▎ | 127/291 [00:32<00:31, 5.23it/s]
Loading 0: 44%|████▍ | 129/291 [00:33<00:36, 4.38it/s]
Loading 0: 45%|████▍ | 130/291 [00:33<00:48, 3.30it/s]
Loading 0: 45%|████▌ | 131/291 [00:34<01:01, 2.61it/s]
Loading 0: 46%|████▌ | 134/291 [00:34<00:34, 4.49it/s]
Loading 0: 46%|████▋ | 135/291 [00:34<00:32, 4.73it/s]
Loading 0: 47%|████▋ | 136/291 [00:34<00:29, 5.32it/s]
Loading 0: 47%|████▋ | 138/291 [00:35<00:34, 4.40it/s]
Loading 0: 48%|████▊ | 139/291 [00:35<00:45, 3.31it/s]
Loading 0: 48%|████▊ | 140/291 [00:36<00:58, 2.59it/s]
Loading 0: 49%|████▉ | 143/291 [00:36<00:33, 4.40it/s]
Loading 0: 49%|████▉ | 144/291 [00:36<00:31, 4.65it/s]
Loading 0: 50%|████▉ | 145/291 [00:37<00:27, 5.24it/s]
Loading 0: 51%|█████ | 147/291 [00:37<00:32, 4.39it/s]
Loading 0: 51%|█████ | 148/291 [00:38<00:43, 3.32it/s]
Loading 0: 51%|█████ | 149/291 [00:38<00:55, 2.57it/s]
Loading 0: 52%|█████▏ | 152/291 [00:39<00:31, 4.37it/s]
Loading 0: 53%|█████▎ | 153/291 [00:39<00:30, 4.59it/s]
Loading 0: 53%|█████▎ | 154/291 [00:39<00:26, 5.19it/s]
Loading 0: 54%|█████▎ | 156/291 [00:39<00:31, 4.34it/s]
Loading 0: 54%|█████▍ | 157/291 [00:40<00:40, 3.28it/s]
Loading 0: 54%|█████▍ | 158/291 [00:41<00:51, 2.58it/s]
Loading 0: 55%|█████▌ | 161/291 [00:41<00:29, 4.43it/s]
Loading 0: 56%|█████▌ | 162/291 [00:41<00:27, 4.65it/s]
Loading 0: 56%|█████▌ | 163/291 [00:41<00:24, 5.18it/s]
Loading 0: 57%|█████▋ | 165/291 [00:42<00:28, 4.36it/s]
Loading 0: 57%|█████▋ | 166/291 [00:42<00:37, 3.29it/s]
Loading 0: 57%|█████▋ | 167/291 [00:43<00:47, 2.61it/s]
Loading 0: 58%|█████▊ | 170/291 [00:43<00:26, 4.49it/s]
Loading 0: 59%|█████▉ | 171/291 [00:43<00:25, 4.72it/s]
Loading 0: 59%|█████▉ | 172/291 [00:43<00:22, 5.33it/s]
Loading 0: 59%|█████▉ | 173/291 [00:44<00:32, 3.59it/s]
Loading 0: 60%|██████ | 175/291 [00:44<00:23, 4.83it/s]
Loading 0: 60%|██████ | 176/291 [00:44<00:22, 5.03it/s]
Loading 0: 61%|██████ | 177/291 [00:44<00:20, 5.58it/s]
Loading 0: 62%|██████▏ | 179/291 [00:45<00:25, 4.48it/s]
Loading 0: 62%|██████▏ | 180/291 [00:46<00:33, 3.31it/s]
Loading 0: 62%|██████▏ | 181/291 [00:46<00:42, 2.59it/s]
Loading 0: 63%|██████▎ | 184/291 [00:46<00:23, 4.55it/s]
Loading 0: 64%|██████▎ | 185/291 [00:47<00:22, 4.79it/s]
Loading 0: 64%|██████▍ | 186/291 [00:47<00:19, 5.40it/s]
Loading 0: 64%|██████▍ | 187/291 [00:47<00:19, 5.45it/s]
Loading 0: 65%|██████▍ | 188/291 [00:47<00:29, 3.52it/s]
Loading 0: 65%|██████▍ | 189/291 [00:48<00:38, 2.64it/s]
Loading 0: 66%|██████▌ | 192/291 [00:49<00:27, 3.57it/s]
Loading 0: 66%|██████▋ | 193/291 [00:49<00:33, 2.94it/s]
Loading 0: 67%|██████▋ | 194/291 [00:50<00:39, 2.45it/s]
Loading 0: 68%|██████▊ | 197/291 [00:50<00:22, 4.14it/s]
Loading 0: 68%|██████▊ | 198/291 [00:50<00:21, 4.40it/s]
Loading 0: 68%|██████▊ | 199/291 [00:50<00:18, 4.99it/s]
Loading 0: 69%|██████▉ | 201/291 [00:51<00:21, 4.24it/s]
Loading 0: 69%|██████▉ | 202/291 [00:51<00:27, 3.24it/s]
Loading 0: 70%|██████▉ | 203/291 [00:52<00:33, 2.60it/s]
Loading 0: 71%|███████ | 206/291 [00:52<00:19, 4.41it/s]
Loading 0: 71%|███████ | 207/291 [00:53<00:18, 4.66it/s]
Loading 0: 71%|███████▏ | 208/291 [00:53<00:15, 5.26it/s]
Loading 0: 72%|███████▏ | 210/291 [00:53<00:18, 4.39it/s]
Loading 0: 73%|███████▎ | 211/291 [00:54<00:24, 3.31it/s]
Loading 0: 73%|███████▎ | 212/291 [00:54<00:29, 2.63it/s]
Loading 0: 74%|███████▍ | 215/291 [00:55<00:17, 4.47it/s]
Loading 0: 74%|███████▍ | 216/291 [00:55<00:15, 4.71it/s]
Loading 0: 75%|███████▍ | 217/291 [00:55<00:13, 5.30it/s]
Loading 0: 75%|███████▌ | 219/291 [00:55<00:16, 4.41it/s]
Loading 0: 76%|███████▌ | 220/291 [00:56<00:21, 3.32it/s]
Loading 0: 76%|███████▌ | 221/291 [00:57<00:26, 2.61it/s]
Loading 0: 77%|███████▋ | 224/291 [00:57<00:14, 4.49it/s]
Loading 0: 77%|███████▋ | 225/291 [00:57<00:13, 4.73it/s]
Loading 0: 78%|███████▊ | 226/291 [00:57<00:12, 5.32it/s]
Loading 0: 78%|███████▊ | 228/291 [00:58<00:14, 4.43it/s]
Loading 0: 79%|███████▊ | 229/291 [00:58<00:18, 3.33it/s]
Loading 0: 79%|███████▉ | 230/291 [00:59<00:23, 2.62it/s]
Loading 0: 80%|████████ | 233/291 [00:59<00:12, 4.50it/s]
Loading 0: 80%|████████ | 234/291 [00:59<00:12, 4.75it/s]
Loading 0: 81%|████████ | 235/291 [00:59<00:10, 5.27it/s]
Loading 0: 81%|████████▏ | 237/291 [01:00<00:12, 4.36it/s]
Loading 0: 82%|████████▏ | 238/291 [01:01<00:16, 3.28it/s]
Loading 0: 82%|████████▏ | 239/291 [01:01<00:19, 2.61it/s]
Loading 0: 83%|████████▎ | 242/291 [01:01<00:11, 4.43it/s]
Loading 0: 84%|████████▎ | 243/291 [01:02<00:10, 4.67it/s]
Loading 0: 84%|████████▍ | 244/291 [01:02<00:09, 5.22it/s]
Loading 0: 85%|████████▍ | 246/291 [01:02<00:10, 4.37it/s]
Loading 0: 85%|████████▍ | 247/291 [01:03<00:13, 3.30it/s]
Loading 0: 85%|████████▌ | 248/291 [01:03<00:16, 2.62it/s]
Loading 0: 86%|████████▋ | 251/291 [01:04<00:08, 4.51it/s]
Loading 0: 87%|████████▋ | 252/291 [01:04<00:08, 4.75it/s]
Loading 0: 87%|████████▋ | 254/291 [01:04<00:05, 6.49it/s]
Loading 0: 88%|████████▊ | 256/291 [01:05<00:10, 3.40it/s]
Loading 0: 88%|████████▊ | 257/291 [01:06<00:12, 2.78it/s]
Loading 0: 89%|████████▉ | 260/291 [01:06<00:07, 4.41it/s]
Loading 0: 90%|████████▉ | 261/291 [01:06<00:06, 4.64it/s]
Loading 0: 90%|█████████ | 262/291 [01:06<00:05, 5.18it/s]
Loading 0: 91%|█████████ | 264/291 [01:07<00:06, 4.39it/s]
Loading 0: 91%|█████████ | 265/291 [01:07<00:07, 3.34it/s]
Loading 0: 91%|█████████▏| 266/291 [01:08<00:09, 2.65it/s]
Loading 0: 92%|█████████▏| 269/291 [01:08<00:04, 4.50it/s]
Loading 0: 93%|█████████▎| 270/291 [01:08<00:04, 4.74it/s]
Loading 0: 93%|█████████▎| 271/291 [01:08<00:03, 5.27it/s]
Loading 0: 94%|█████████▍| 273/291 [01:09<00:04, 4.41it/s]
Loading 0: 94%|█████████▍| 274/291 [01:10<00:05, 3.33it/s]
Loading 0: 95%|█████████▍| 275/291 [01:10<00:06, 2.62it/s]
Loading 0: 96%|█████████▌| 278/291 [01:10<00:02, 4.49it/s]
Loading 0: 96%|█████████▌| 279/291 [01:11<00:02, 4.72it/s]
Loading 0: 96%|█████████▌| 280/291 [01:11<00:02, 5.31it/s]
Loading 0: 97%|█████████▋| 281/291 [01:11<00:02, 3.58it/s]
Loading 0: 97%|█████████▋| 282/291 [01:12<00:03, 2.68it/s]
Loading 0: 98%|█████████▊| 284/291 [01:12<00:01, 3.86it/s]
Loading 0: 98%|█████████▊| 285/291 [01:12<00:01, 4.21it/s]
Loading 0: 98%|█████████▊| 286/291 [01:12<00:01, 4.89it/s]
Loading 0: 99%|█████████▊| 287/291 [01:13<00:00, 5.11it/s]
Loading 0: 99%|█████████▉| 288/291 [01:13<00:00, 3.34it/s]
Job alexdaoud-trainer-bagir-8911-v1-mkmlizer completed after 145.4s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-8911-v1-mkmlizer
Pipeline stage MKMLizer completed in 145.91s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.17s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-8911-v1
Waiting for inference service alexdaoud-trainer-bagir-8911-v1 to be ready
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Connection pool is full, discarding connection: %s. Connection pool size: %s
Inference service alexdaoud-trainer-bagir-8911-v1 ready after 252.53782033920288s
Pipeline stage MKMLDeployer completed in 253.12s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.073209285736084s
Received healthy response to inference request in 5.787472724914551s
Received healthy response to inference request in 2.379596471786499s
Received healthy response to inference request in 4.073566675186157s
Received healthy response to inference request in 2.9748098850250244s
5 requests
0 failed requests
5th percentile: 2.498639154434204
10th percentile: 2.6176818370819093
20th percentile: 2.8557672023773195
30th percentile: 2.9944897651672364
40th percentile: 3.03384952545166
50th percentile: 3.073209285736084
60th percentile: 3.473352241516113
70th percentile: 3.8734951972961422
80th percentile: 4.416347885131836
90th percentile: 5.1019103050231935
95th percentile: 5.444691514968872
99th percentile: 5.718916482925415
mean time: 3.6577310085296633
%s, retrying in %s seconds...
Received healthy response to inference request in 3.547494649887085s
Received healthy response to inference request in 4.073184967041016s
Received healthy response to inference request in 2.998370885848999s
Received healthy response to inference request in 3.0603132247924805s
Received healthy response to inference request in 2.213198661804199s
5 requests
0 failed requests
5th percentile: 2.370233106613159
10th percentile: 2.5272675514221192
20th percentile: 2.8413364410400392
30th percentile: 3.0107593536376953
40th percentile: 3.035536289215088
50th percentile: 3.0603132247924805
60th percentile: 3.2551857948303224
70th percentile: 3.450058364868164
80th percentile: 3.652632713317871
90th percentile: 3.8629088401794434
95th percentile: 3.9680469036102295
99th percentile: 4.052157354354859
mean time: 3.1785124778747558
Pipeline stage StressChecker completed in 36.74s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyTriggerPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage OfflineFamilyFriendlyTriggerPipeline completed in 2.54s
run pipeline stage %s
Running pipeline stage TriggerMKMLProfilingPipeline
run_pipeline:run_in_cloud %s
starting trigger_guanaco_pipeline args=%s
triggered trigger_guanaco_pipeline args=%s
Pipeline stage TriggerMKMLProfilingPipeline completed in 2.32s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_8911_v1 status is now deployed due to DeploymentManager action
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Skipping teardown as no inference service was successfully deployed
Pipeline stage MKMLProfilerDeleter completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-8911-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-8911-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-8911-v1-profiler ready after 250.54141092300415s
Pipeline stage MKMLProfilerDeployer completed in 250.89s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplo26rhq:/code/chaiverse_profiler_1734609425 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplo26rhq --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734609425 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734609425/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplo26rhq:/code/chaiverse_profiler_1734612223 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplo26rhq:/code/chaiverse_profiler_1734612223 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplo26rhq --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734612223 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734612223/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-8911-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-8911-v1-profiler
Service alexdaoud-trainer-bagir-8911-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.48s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-8911-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.86s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-8911-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-8911-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-8911-v1-profiler ready after 240.62499809265137s
Pipeline stage MKMLProfilerDeployer completed in 240.98s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplonkjg9:/code/chaiverse_profiler_1734613050 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplonkjg9 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734613050 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734613050/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplonkjg9:/code/chaiverse_profiler_1734615848 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplonkjg9 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734615848 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734615848/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-8911-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-8911-v1-profiler
Service alexdaoud-trainer-bagir-8911-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.63s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-8911-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.73s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.13s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-8911-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-8911-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-8911-v1-profiler ready after 40.111377477645874s
Pipeline stage MKMLProfilerDeployer completed in 40.46s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplor5q9s:/code/chaiverse_profiler_1734616481 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplor5q9s --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734616481 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734616481/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplor5q9s:/code/chaiverse_profiler_1734619249 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-ba3438fccbc2d98fee8cfd64e11433d8b8-deplor5q9s --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734619249 && python profiles.py profile --best_of_n 1 --auto_batch 5 --batches 1,5,10,15,20,25,30,35,40,45,50,55,60,65,70,75,80,85,90,95,100,105,110,115,120,125,130,135,140,145,150,155,160,165,170,175,180,185,190,195 --samples 200 --input_tokens 256 --output_tokens 1 --summary /code/chaiverse_profiler_1734619249/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-8911-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-8911-v1-profiler
Service alexdaoud-trainer-bagir-8911-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.69s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_8911_v1 status is now inactive due to auto deactivation removed underperforming models