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-1658-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-1658-v1-mkmlizer to finish
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ _____ __ __ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ /___/ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ Version: 0.11.12 ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ https://mk1.ai ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ The license key for the current software has been verified as ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ belonging to: ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ Chai Research Corp. ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ Expiration: 2025-01-15 23:59:59 ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ║ ║
alexdaoud-trainer-bagir-1658-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-1658-v1-mkmlizer: Downloaded to shared memory in 31.840s
alexdaoud-trainer-bagir-1658-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmpfofhbtmc, device:0
alexdaoud-trainer-bagir-1658-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-1658-v1-mkmlizer: quantized model in 85.387s
alexdaoud-trainer-bagir-1658-v1-mkmlizer: Processed model alexdaoud/trainer_bagir_2024-12-11-checkpoint-36 in 117.228s
alexdaoud-trainer-bagir-1658-v1-mkmlizer: creating bucket guanaco-mkml-models
alexdaoud-trainer-bagir-1658-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
alexdaoud-trainer-bagir-1658-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1
alexdaoud-trainer-bagir-1658-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1/special_tokens_map.json
alexdaoud-trainer-bagir-1658-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1/config.json
alexdaoud-trainer-bagir-1658-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1/tokenizer_config.json
alexdaoud-trainer-bagir-1658-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1/tokenizer.json
alexdaoud-trainer-bagir-1658-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/alexdaoud-trainer-bagir-1658-v1/flywheel_model.0.safetensors
alexdaoud-trainer-bagir-1658-v1-mkmlizer:
Loading 0: 0%| | 0/291 [00:00<?, ?it/s]
Loading 0: 1%| | 3/291 [00:00<00:56, 5.07it/s]
Loading 0: 1%|▏ | 4/291 [00:01<01:31, 3.13it/s]
Loading 0: 2%|▏ | 5/291 [00:01<02:00, 2.37it/s]
Loading 0: 3%|▎ | 8/291 [00:02<01:02, 4.49it/s]
Loading 0: 3%|▎ | 9/291 [00:02<01:01, 4.55it/s]
Loading 0: 3%|▎ | 10/291 [00:02<00:55, 5.10it/s]
Loading 0: 4%|▍ | 12/291 [00:02<01:05, 4.27it/s]
Loading 0: 4%|▍ | 13/291 [00:03<01:26, 3.22it/s]
Loading 0: 5%|▍ | 14/291 [00:04<01:49, 2.53it/s]
Loading 0: 6%|▌ | 17/291 [00:04<01:02, 4.35it/s]
Loading 0: 6%|▌ | 18/291 [00:04<00:59, 4.58it/s]
Loading 0: 7%|▋ | 19/291 [00:04<00:53, 5.08it/s]
Loading 0: 7%|▋ | 21/291 [00:05<01:02, 4.29it/s]
Loading 0: 8%|▊ | 22/291 [00:05<01:22, 3.24it/s]
Loading 0: 8%|▊ | 23/291 [00:06<01:44, 2.55it/s]
Loading 0: 9%|▉ | 26/291 [00:06<01:00, 4.35it/s]
Loading 0: 9%|▉ | 27/291 [00:06<00:57, 4.56it/s]
Loading 0: 10%|▉ | 28/291 [00:07<00:51, 5.06it/s]
Loading 0: 10%|█ | 30/291 [00:07<01:00, 4.30it/s]
Loading 0: 11%|█ | 31/291 [00:08<01:19, 3.26it/s]
Loading 0: 11%|█ | 32/291 [00:08<01:41, 2.56it/s]
Loading 0: 12%|█▏ | 35/291 [00:09<00:58, 4.35it/s]
Loading 0: 12%|█▏ | 36/291 [00:09<00:55, 4.59it/s]
Loading 0: 13%|█▎ | 37/291 [00:09<00:49, 5.17it/s]
Loading 0: 13%|█▎ | 39/291 [00:09<00:58, 4.32it/s]
Loading 0: 14%|█▎ | 40/291 [00:10<01:16, 3.26it/s]
Loading 0: 14%|█▍ | 41/291 [00:11<01:36, 2.58it/s]
Loading 0: 15%|█▌ | 44/291 [00:11<00:55, 4.44it/s]
Loading 0: 15%|█▌ | 45/291 [00:11<00:52, 4.67it/s]
Loading 0: 16%|█▌ | 46/291 [00:11<00:47, 5.18it/s]
Loading 0: 16%|█▋ | 48/291 [00:12<00:55, 4.35it/s]
Loading 0: 17%|█▋ | 49/291 [00:12<01:13, 3.29it/s]
Loading 0: 17%|█▋ | 50/291 [00:13<01:33, 2.58it/s]
Loading 0: 18%|█▊ | 53/291 [00:13<00:53, 4.45it/s]
Loading 0: 19%|█▊ | 54/291 [00:13<00:50, 4.69it/s]
Loading 0: 19%|█▉ | 56/291 [00:13<00:36, 6.44it/s]
Loading 0: 20%|█▉ | 58/291 [00:15<01:09, 3.37it/s]
Loading 0: 20%|██ | 59/291 [00:15<01:24, 2.76it/s]
Loading 0: 21%|██▏ | 62/291 [00:15<00:51, 4.41it/s]
Loading 0: 22%|██▏ | 63/291 [00:16<00:49, 4.64it/s]
Loading 0: 22%|██▏ | 64/291 [00:16<00:44, 5.15it/s]
Loading 0: 23%|██▎ | 66/291 [00:16<00:51, 4.37it/s]
Loading 0: 23%|██▎ | 67/291 [00:17<01:07, 3.31it/s]
Loading 0: 23%|██▎ | 68/291 [00:17<01:24, 2.64it/s]
Loading 0: 24%|██▍ | 71/291 [00:18<00:49, 4.49it/s]
Loading 0: 25%|██▍ | 72/291 [00:18<00:46, 4.71it/s]
Loading 0: 25%|██▌ | 73/291 [00:18<00:41, 5.21it/s]
Loading 0: 26%|██▌ | 75/291 [00:18<00:49, 4.37it/s]
Loading 0: 26%|██▌ | 76/291 [00:19<01:05, 3.29it/s]
Loading 0: 26%|██▋ | 77/291 [00:20<01:22, 2.61it/s]
Loading 0: 27%|██▋ | 80/291 [00:20<00:47, 4.45it/s]
Loading 0: 28%|██▊ | 81/291 [00:20<00:44, 4.69it/s]
Loading 0: 28%|██▊ | 82/291 [00:20<00:39, 5.25it/s]
Loading 0: 29%|██▊ | 83/291 [00:20<00:39, 5.32it/s]
Loading 0: 29%|██▉ | 84/291 [00:21<00:59, 3.48it/s]
Loading 0: 29%|██▉ | 85/291 [00:22<01:14, 2.75it/s]
Loading 0: 30%|██▉ | 86/291 [00:22<01:30, 2.27it/s]
Loading 0: 31%|███ | 89/291 [00:22<00:48, 4.19it/s]
Loading 0: 31%|███ | 90/291 [00:23<00:44, 4.48it/s]
Loading 0: 31%|███▏ | 91/291 [00:23<00:39, 5.11it/s]
Loading 0: 32%|███▏ | 93/291 [00:23<00:45, 4.32it/s]
Loading 0: 32%|███▏ | 94/291 [00:24<01:00, 3.26it/s]
Loading 0: 33%|███▎ | 95/291 [00:24<01:16, 2.57it/s]
Loading 0: 34%|███▎ | 98/291 [00:25<00:43, 4.46it/s]
Loading 0: 34%|███▍ | 99/291 [00:25<00:40, 4.70it/s]
Loading 0: 34%|███▍ | 100/291 [00:25<00:35, 5.31it/s]
Loading 0: 35%|███▌ | 102/291 [00:25<00:42, 4.40it/s]
Loading 0: 35%|███▌ | 103/291 [00:26<00:56, 3.32it/s]
Loading 0: 36%|███▌ | 104/291 [00:27<01:11, 2.63it/s]
Loading 0: 37%|███▋ | 107/291 [00:27<00:41, 4.45it/s]
Loading 0: 37%|███▋ | 108/291 [00:27<00:39, 4.68it/s]
Loading 0: 37%|███▋ | 109/291 [00:27<00:34, 5.21it/s]
Loading 0: 38%|███▊ | 111/291 [00:28<00:41, 4.37it/s]
Loading 0: 38%|███▊ | 112/291 [00:28<00:54, 3.30it/s]
Loading 0: 39%|███▉ | 113/291 [00:29<01:08, 2.59it/s]
Loading 0: 40%|███▉ | 116/291 [00:29<00:39, 4.39it/s]
Loading 0: 40%|████ | 117/291 [00:29<00:37, 4.61it/s]
Loading 0: 41%|████ | 118/291 [00:29<00:33, 5.20it/s]
Loading 0: 41%|████ | 120/291 [00:30<00:39, 4.34it/s]
Loading 0: 42%|████▏ | 121/291 [00:31<00:52, 3.26it/s]
Loading 0: 42%|████▏ | 122/291 [00:31<01:05, 2.59it/s]
Loading 0: 43%|████▎ | 125/291 [00:31<00:37, 4.44it/s]
Loading 0: 43%|████▎ | 126/291 [00:32<00:35, 4.68it/s]
Loading 0: 44%|████▎ | 127/291 [00:32<00:31, 5.21it/s]
Loading 0: 44%|████▍ | 129/291 [00:32<00:37, 4.37it/s]
Loading 0: 45%|████▍ | 130/291 [00:33<00:48, 3.31it/s]
Loading 0: 45%|████▌ | 131/291 [00:34<01:01, 2.62it/s]
Loading 0: 46%|████▌ | 134/291 [00:34<00:34, 4.51it/s]
Loading 0: 46%|████▋ | 135/291 [00:34<00:32, 4.74it/s]
Loading 0: 47%|████▋ | 136/291 [00:34<00:29, 5.34it/s]
Loading 0: 47%|████▋ | 138/291 [00:35<00:34, 4.44it/s]
Loading 0: 48%|████▊ | 139/291 [00:35<00:45, 3.34it/s]
Loading 0: 48%|████▊ | 140/291 [00:36<00:57, 2.64it/s]
Loading 0: 49%|████▉ | 143/291 [00:36<00:32, 4.53it/s]
Loading 0: 49%|████▉ | 144/291 [00:36<00:30, 4.76it/s]
Loading 0: 50%|████▉ | 145/291 [00:36<00:27, 5.36it/s]
Loading 0: 51%|█████ | 147/291 [00:37<00:32, 4.44it/s]
Loading 0: 51%|█████ | 148/291 [00:37<00:42, 3.34it/s]
Loading 0: 51%|█████ | 149/291 [00:38<00:53, 2.64it/s]
Loading 0: 52%|█████▏ | 152/291 [00:38<00:30, 4.54it/s]
Loading 0: 53%|█████▎ | 153/291 [00:38<00:28, 4.78it/s]
Loading 0: 53%|█████▎ | 154/291 [00:38<00:25, 5.30it/s]
Loading 0: 54%|█████▎ | 156/291 [00:39<00:30, 4.43it/s]
Loading 0: 54%|█████▍ | 157/291 [00:40<00:40, 3.33it/s]
Loading 0: 54%|█████▍ | 158/291 [00:40<00:50, 2.64it/s]
Loading 0: 55%|█████▌ | 161/291 [00:40<00:28, 4.49it/s]
Loading 0: 56%|█████▌ | 162/291 [00:41<00:27, 4.72it/s]
Loading 0: 56%|█████▌ | 163/291 [00:41<00:24, 5.32it/s]
Loading 0: 57%|█████▋ | 165/291 [00:41<00:28, 4.42it/s]
Loading 0: 57%|█████▋ | 166/291 [00:42<00:37, 3.32it/s]
Loading 0: 57%|█████▋ | 167/291 [00:43<00:47, 2.60it/s]
Loading 0: 58%|█████▊ | 170/291 [00:43<00:27, 4.38it/s]
Loading 0: 59%|█████▉ | 171/291 [00:43<00:25, 4.63it/s]
Loading 0: 59%|█████▉ | 172/291 [00:43<00:22, 5.23it/s]
Loading 0: 59%|█████▉ | 173/291 [00:44<00:33, 3.56it/s]
Loading 0: 60%|██████ | 175/291 [00:44<00:23, 4.89it/s]
Loading 0: 60%|██████ | 176/291 [00:44<00:22, 5.12it/s]
Loading 0: 61%|██████ | 177/291 [00:44<00:19, 5.79it/s]
Loading 0: 62%|██████▏ | 179/291 [00:45<00:24, 4.57it/s]
Loading 0: 62%|██████▏ | 180/291 [00:45<00:33, 3.36it/s]
Loading 0: 62%|██████▏ | 181/291 [00:46<00:41, 2.62it/s]
Loading 0: 63%|██████▎ | 184/291 [00:46<00:23, 4.58it/s]
Loading 0: 64%|██████▎ | 185/291 [00:46<00:22, 4.81it/s]
Loading 0: 64%|██████▍ | 186/291 [00:46<00:19, 5.40it/s]
Loading 0: 64%|██████▍ | 187/291 [00:46<00:18, 5.50it/s]
Loading 0: 65%|██████▍ | 188/291 [00:47<00:28, 3.57it/s]
Loading 0: 65%|██████▍ | 189/291 [00:48<00:38, 2.65it/s]
Loading 0: 66%|██████▌ | 192/291 [00:48<00:27, 3.60it/s]
Loading 0: 66%|██████▋ | 193/291 [00:49<00:32, 2.97it/s]
Loading 0: 67%|██████▋ | 194/291 [00:49<00:39, 2.48it/s]
Loading 0: 68%|██████▊ | 197/291 [00:50<00:22, 4.24it/s]
Loading 0: 68%|██████▊ | 198/291 [00:50<00:20, 4.51it/s]
Loading 0: 68%|██████▊ | 199/291 [00:50<00:18, 5.09it/s]
Loading 0: 69%|██████▉ | 201/291 [00:50<00:20, 4.33it/s]
Loading 0: 69%|██████▉ | 202/291 [00:51<00:27, 3.29it/s]
Loading 0: 70%|██████▉ | 203/291 [00:52<00:33, 2.61it/s]
Loading 0: 71%|███████ | 206/291 [00:52<00:19, 4.43it/s]
Loading 0: 71%|███████ | 207/291 [00:52<00:17, 4.68it/s]
Loading 0: 71%|███████▏ | 208/291 [00:52<00:15, 5.25it/s]
Loading 0: 72%|███████▏ | 210/291 [00:53<00:18, 4.40it/s]
Loading 0: 73%|███████▎ | 211/291 [00:53<00:24, 3.31it/s]
Loading 0: 73%|███████▎ | 212/291 [00:54<00:29, 2.64it/s]
Loading 0: 74%|███████▍ | 215/291 [00:54<00:16, 4.48it/s]
Loading 0: 74%|███████▍ | 216/291 [00:54<00:15, 4.72it/s]
Loading 0: 75%|███████▍ | 217/291 [00:54<00:14, 5.20it/s]
Loading 0: 75%|███████▌ | 219/291 [00:55<00:16, 4.39it/s]
Loading 0: 76%|███████▌ | 220/291 [00:56<00:21, 3.32it/s]
Loading 0: 76%|███████▌ | 221/291 [00:56<00:26, 2.64it/s]
Loading 0: 77%|███████▋ | 224/291 [00:56<00:14, 4.52it/s]
Loading 0: 77%|███████▋ | 225/291 [00:57<00:13, 4.76it/s]
Loading 0: 78%|███████▊ | 226/291 [00:57<00:12, 5.35it/s]
Loading 0: 78%|███████▊ | 228/291 [00:57<00:14, 4.46it/s]
Loading 0: 79%|███████▊ | 229/291 [00:58<00:18, 3.35it/s]
Loading 0: 79%|███████▉ | 230/291 [00:58<00:23, 2.63it/s]
Loading 0: 80%|████████ | 233/291 [00:59<00:13, 4.46it/s]
Loading 0: 80%|████████ | 234/291 [00:59<00:12, 4.70it/s]
Loading 0: 81%|████████ | 235/291 [00:59<00:10, 5.28it/s]
Loading 0: 81%|████████▏ | 237/291 [01:00<00:12, 4.42it/s]
Loading 0: 82%|████████▏ | 238/291 [01:00<00:15, 3.34it/s]
Loading 0: 82%|████████▏ | 239/291 [01:01<00:19, 2.65it/s]
Loading 0: 83%|████████▎ | 242/291 [01:01<00:10, 4.55it/s]
Loading 0: 84%|████████▎ | 243/291 [01:01<00:10, 4.77it/s]
Loading 0: 84%|████████▍ | 244/291 [01:01<00:08, 5.33it/s]
Loading 0: 85%|████████▍ | 246/291 [01:02<00:10, 4.42it/s]
Loading 0: 85%|████████▍ | 247/291 [01:02<00:13, 3.32it/s]
Loading 0: 85%|████████▌ | 248/291 [01:03<00:16, 2.64it/s]
Loading 0: 86%|████████▋ | 251/291 [01:03<00:08, 4.53it/s]
Loading 0: 87%|████████▋ | 252/291 [01:03<00:08, 4.76it/s]
Loading 0: 87%|████████▋ | 253/291 [01:03<00:07, 5.35it/s]
Loading 0: 88%|████████▊ | 255/291 [01:04<00:08, 4.45it/s]
Loading 0: 88%|████████▊ | 256/291 [01:05<00:10, 3.36it/s]
Loading 0: 88%|████████▊ | 257/291 [01:05<00:12, 2.65it/s]
Loading 0: 89%|████████▉ | 260/291 [01:05<00:06, 4.55it/s]
Loading 0: 90%|████████▉ | 261/291 [01:06<00:06, 4.79it/s]
Loading 0: 90%|█████████ | 262/291 [01:06<00:05, 5.39it/s]
Loading 0: 91%|█████████ | 264/291 [01:06<00:06, 4.46it/s]
Loading 0: 91%|█████████ | 265/291 [01:07<00:07, 3.37it/s]
Loading 0: 91%|█████████▏| 266/291 [01:07<00:09, 2.64it/s]
Loading 0: 92%|█████████▏| 269/291 [01:08<00:04, 4.53it/s]
Loading 0: 93%|█████████▎| 270/291 [01:08<00:04, 4.77it/s]
Loading 0: 93%|█████████▎| 271/291 [01:08<00:03, 5.32it/s]
Loading 0: 94%|█████████▍| 273/291 [01:08<00:04, 4.44it/s]
Loading 0: 94%|█████████▍| 274/291 [01:09<00:05, 3.36it/s]
Loading 0: 95%|█████████▍| 275/291 [01:10<00:06, 2.64it/s]
Loading 0: 96%|█████████▌| 278/291 [01:10<00:02, 4.53it/s]
Loading 0: 96%|█████████▌| 279/291 [01:10<00:02, 4.76it/s]
Loading 0: 96%|█████████▌| 280/291 [01:10<00:02, 5.34it/s]
Loading 0: 97%|█████████▋| 281/291 [01:11<00:02, 3.57it/s]
Loading 0: 97%|█████████▋| 282/291 [01:11<00:03, 2.67it/s]
Loading 0: 98%|█████████▊| 284/291 [01:12<00:01, 3.83it/s]
Loading 0: 98%|█████████▊| 285/291 [01:12<00:01, 4.16it/s]
Loading 0: 98%|█████████▊| 286/291 [01:12<00:01, 4.81it/s]
Loading 0: 99%|█████████▊| 287/291 [01:12<00:00, 4.99it/s]
Loading 0: 99%|█████████▉| 288/291 [01:13<00:00, 3.24it/s]
Job alexdaoud-trainer-bagir-1658-v1-mkmlizer completed after 146.81s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-1658-v1-mkmlizer
Pipeline stage MKMLizer completed in 147.41s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-1658-v1
Waiting for inference service alexdaoud-trainer-bagir-1658-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-1658-v1 ready after 221.4534137248993s
Pipeline stage MKMLDeployer completed in 222.04s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.76615834236145s
Received healthy response to inference request in 4.537001132965088s
Received healthy response to inference request in 3.985478639602661s
Received healthy response to inference request in 4.040911912918091s
Received healthy response to inference request in 4.96366810798645s
5 requests
0 failed requests
5th percentile: 3.810022401809692
10th percentile: 3.8538864612579347
20th percentile: 3.941614580154419
30th percentile: 3.9965652942657472
40th percentile: 4.018738603591919
50th percentile: 4.040911912918091
60th percentile: 4.23934760093689
70th percentile: 4.437783288955688
80th percentile: 4.62233452796936
90th percentile: 4.793001317977906
95th percentile: 4.878334712982178
99th percentile: 4.946601428985596
mean time: 4.258643627166748
%s, retrying in %s seconds...
Received healthy response to inference request in 3.2177329063415527s
Received healthy response to inference request in 4.03007698059082s
Received healthy response to inference request in 4.918528318405151s
Received healthy response to inference request in 4.181771993637085s
Received healthy response to inference request in 3.325665235519409s
5 requests
0 failed requests
5th percentile: 3.239319372177124
10th percentile: 3.2609058380126954
20th percentile: 3.304078769683838
30th percentile: 3.4665475845336915
40th percentile: 3.7483122825622557
50th percentile: 4.03007698059082
60th percentile: 4.090754985809326
70th percentile: 4.151432991027832
80th percentile: 4.329123258590698
90th percentile: 4.623825788497925
95th percentile: 4.771177053451538
99th percentile: 4.889058065414429
mean time: 3.9347550868988037
%s, retrying in %s seconds...
Received healthy response to inference request in 3.5692403316497803s
Received healthy response to inference request in 4.211401462554932s
Received healthy response to inference request in 3.3824703693389893s
Received healthy response to inference request in 3.3431236743927s
Received healthy response to inference request in 3.518662452697754s
5 requests
0 failed requests
5th percentile: 3.350993013381958
10th percentile: 3.358862352371216
20th percentile: 3.3746010303497314
30th percentile: 3.409708786010742
40th percentile: 3.464185619354248
50th percentile: 3.518662452697754
60th percentile: 3.5388936042785644
70th percentile: 3.559124755859375
80th percentile: 3.6976725578308107
90th percentile: 3.954537010192871
95th percentile: 4.082969236373901
99th percentile: 4.185715017318725
mean time: 3.604979658126831
Pipeline stage StressChecker completed in 64.05s
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 2.62s
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 2.30s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1658_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 0.12s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1658-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1658-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1658-v1-profiler ready after 210.49325609207153s
Pipeline stage MKMLProfilerDeployer completed in 210.86s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplod7zd7:/code/chaiverse_profiler_1734278599 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplod7zd7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734278599 && 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_1734278599/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplod7zd7:/code/chaiverse_profiler_1734281376 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplod7zd7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734281376 && 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_1734281376/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1658-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1658-v1-profiler
Service alexdaoud-trainer-bagir-1658-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.33s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1658-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.38s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1658-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1658-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1658-v1-profiler ready after 80.20351839065552s
Pipeline stage MKMLProfilerDeployer completed in 80.57s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplo274t7:/code/chaiverse_profiler_1734282101 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplo274t7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734282101 && 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_1734282101/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplo274t7:/code/chaiverse_profiler_1734284877 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplo274t7:/code/chaiverse_profiler_1734284878 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplo274t7 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734284878 && 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_1734284878/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1658-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1658-v1-profiler
Service alexdaoud-trainer-bagir-1658-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.53s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1658-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.55s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.14s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1658-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1658-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1658-v1-profiler ready after 160.36604380607605s
Pipeline stage MKMLProfilerDeployer completed in 160.74s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplognz94:/code/chaiverse_profiler_1734285811 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplognz94 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734285811 && 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_1734285811/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplognz94:/code/chaiverse_profiler_1734288588 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplognz94:/code/chaiverse_profiler_1734288589 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-bae6ac2fe14c2ddfb28bf4816b7ff3abc8-deplognz94 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734288589 && 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_1734288589/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1658-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1658-v1-profiler
Service alexdaoud-trainer-bagir-1658-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.55s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1658_v1 status is now inactive due to auto deactivation removed underperforming models