alexdaoud-trainer-bagir-_1291

developer_uid: chai_backend_admin
submission_id: alexdaoud-trainer-bagir-_1291_v1
model_name: alexdaoud-trainer-bagir-_1291_v1
model_group: alexdaoud/trainer_bagir_
status: inactive
timestamp: 2024-12-15T22:51:25+00:00
num_battles: 23672
num_wins: 12545
celo_rating: 1265.85
family_friendly_score: 0.5808
family_friendly_standard_error: 0.006978128115762852
submission_type: basic
model_repo: alexdaoud/trainer_bagir_2024-12-11-checkpoint-45
model_architecture: LlamaForSequenceClassification
model_num_parameters: 8030261248.0
best_of: 1
max_input_tokens: 256
max_output_tokens: 1
display_name: alexdaoud-trainer-bagir-_1291_v1
ineligible_reason: max_output_tokens!=64
is_internal_developer: True
language_model: alexdaoud/trainer_bagir_2024-12-11-checkpoint-45
model_size: 8B
ranking_group: single
us_pacific_date: 2024-12-15
win_ratio: 0.529950996958432
generation_params: {'temperature': 1.0, 'top_p': 1.0, 'min_p': 0.0, 'top_k': 40, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 256, 'best_of': 1, 'max_output_tokens': 1}
formatter: {'memory_template': '', 'prompt_template': '', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '', 'truncate_by_message': True}
Resubmit model
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-1291-v1-mkmlizer
Waiting for job on alexdaoud-trainer-bagir-1291-v1-mkmlizer to finish
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║     _____            __           __                                ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║    / _/ /_ ___    __/ /  ___ ___ / /                                ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║   / _/ / // / |/|/ / _ \/ -_) -_) /                                 ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  /_//_/\_, /|__,__/_//_/\__/\__/_/                                  ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║       /___/                                                         ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  Version: 0.11.12                                                   ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  Copyright 2023 MK ONE TECHNOLOGIES Inc.                            ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  https://mk1.ai                                                     ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  The license key for the current software has been verified as      ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  belonging to:                                                      ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  Chai Research Corp.                                                ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║  Expiration: 2025-01-15 23:59:59                                    ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ║                                                                     ║
alexdaoud-trainer-bagir-1291-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
alexdaoud-trainer-bagir-1291-v1-mkmlizer: Downloaded to shared memory in 32.098s
alexdaoud-trainer-bagir-1291-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmpk8x4f5l6, device:0
alexdaoud-trainer-bagir-1291-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
alexdaoud-trainer-bagir-1291-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<01:32,  3.10it/s]
Loading 0:   2%|▏         | 5/291 [00:01<02:02,  2.33it/s]
Loading 0:   3%|▎         | 8/291 [00:02<01:03,  4.44it/s]
Loading 0:   3%|▎         | 9/291 [00:02<01:02,  4.49it/s]
Loading 0:   3%|▎         | 10/291 [00:02<00:54,  5.11it/s]
Loading 0:   4%|▍         | 12/291 [00:02<01:05,  4.26it/s]
Loading 0:   4%|▍         | 13/291 [00:03<01:26,  3.21it/s]
Loading 0:   5%|▍         | 14/291 [00:04<01:50,  2.50it/s]
Loading 0:   6%|▌         | 17/291 [00:04<01:03,  4.30it/s]
Loading 0:   6%|▌         | 18/291 [00:04<01:00,  4.54it/s]
Loading 0:   7%|▋         | 19/291 [00:04<00:53,  5.12it/s]
Loading 0:   7%|▋         | 21/291 [00:05<01:02,  4.31it/s]
Loading 0:   8%|▊         | 22/291 [00:05<01:22,  3.26it/s]
Loading 0:   8%|▊         | 23/291 [00:06<01:44,  2.55it/s]
Loading 0:   9%|▉         | 26/291 [00:06<01:00,  4.34it/s]
Loading 0:   9%|▉         | 27/291 [00:06<00:57,  4.59it/s]
Loading 0:  10%|▉         | 28/291 [00:07<00:50,  5.19it/s]
Loading 0:  10%|█         | 30/291 [00:07<01:00,  4.34it/s]
Loading 0:  11%|█         | 31/291 [00:08<01:19,  3.28it/s]
Loading 0:  11%|█         | 32/291 [00:08<01:40,  2.57it/s]
Loading 0:  12%|█▏        | 35/291 [00:09<00:58,  4.37it/s]
Loading 0:  12%|█▏        | 36/291 [00:09<00:55,  4.61it/s]
Loading 0:  13%|█▎        | 37/291 [00:09<00:48,  5.21it/s]
Loading 0:  13%|█▎        | 39/291 [00:09<00:57,  4.36it/s]
Loading 0:  14%|█▎        | 40/291 [00:10<01:16,  3.29it/s]
Loading 0:  14%|█▍        | 41/291 [00:11<01:36,  2.60it/s]
Loading 0:  15%|█▌        | 44/291 [00:11<00:56,  4.41it/s]
Loading 0:  15%|█▌        | 45/291 [00:11<00:53,  4.63it/s]
Loading 0:  16%|█▌        | 46/291 [00:11<00:47,  5.12it/s]
Loading 0:  16%|█▋        | 48/291 [00:12<00:56,  4.32it/s]
Loading 0:  17%|█▋        | 49/291 [00:12<01:14,  3.27it/s]
Loading 0:  17%|█▋        | 50/291 [00:13<01:33,  2.57it/s]
Loading 0:  18%|█▊        | 53/291 [00:13<00:54,  4.37it/s]
Loading 0:  19%|█▊        | 54/291 [00:13<00:50,  4.68it/s]
Loading 0:  19%|█▉        | 55/291 [00:13<00:44,  5.28it/s]
Loading 0:  20%|█▉        | 57/291 [00:14<00:53,  4.39it/s]
Loading 0:  20%|█▉        | 58/291 [00:15<01:10,  3.31it/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,  4.68it/s]
Loading 0:  22%|██▏       | 64/291 [00:16<00:43,  5.25it/s]
Loading 0:  23%|██▎       | 66/291 [00:16<00:51,  4.37it/s]
Loading 0:  23%|██▎       | 67/291 [00:17<01:08,  3.29it/s]
Loading 0:  23%|██▎       | 68/291 [00:18<01:25,  2.60it/s]
Loading 0:  24%|██▍       | 71/291 [00:18<00:49,  4.41it/s]
Loading 0:  25%|██▍       | 72/291 [00:18<00:47,  4.64it/s]
Loading 0:  25%|██▌       | 73/291 [00:18<00:41,  5.23it/s]
Loading 0:  26%|██▌       | 75/291 [00:19<00:49,  4.38it/s]
Loading 0:  26%|██▌       | 76/291 [00:19<01:04,  3.31it/s]
Loading 0:  26%|██▋       | 77/291 [00:20<01:22,  2.59it/s]
Loading 0:  27%|██▋       | 80/291 [00:20<00:47,  4.45it/s]
Loading 0:  28%|██▊       | 81/291 [00:20<00:44,  4.77it/s]
Loading 0:  28%|██▊       | 82/291 [00:20<00:39,  5.36it/s]
Loading 0:  29%|██▊       | 83/291 [00:20<00:39,  5.31it/s]
Loading 0:  29%|██▉       | 84/291 [00:21<00:59,  3.49it/s]
Loading 0:  29%|██▉       | 85/291 [00:22<01:15,  2.75it/s]
Loading 0:  30%|██▉       | 86/291 [00:22<01:31,  2.25it/s]
Loading 0:  31%|███       | 89/291 [00:22<00:48,  4.13it/s]
Loading 0:  31%|███       | 90/291 [00:23<00:45,  4.42it/s]
Loading 0:  31%|███▏      | 91/291 [00:23<00:39,  5.04it/s]
Loading 0:  32%|███▏      | 93/291 [00:23<00:46,  4.28it/s]
Loading 0:  32%|███▏      | 94/291 [00:24<01:00,  3.23it/s]
Loading 0:  33%|███▎      | 95/291 [00:25<01:16,  2.55it/s]
Loading 0:  34%|███▎      | 98/291 [00:25<00:43,  4.41it/s]
Loading 0:  34%|███▍      | 99/291 [00:25<00:41,  4.64it/s]
Loading 0:  34%|███▍      | 100/291 [00:25<00:36,  5.22it/s]
Loading 0:  35%|███▌      | 102/291 [00:26<00:43,  4.35it/s]
Loading 0:  35%|███▌      | 103/291 [00:26<00:57,  3.29it/s]
Loading 0:  36%|███▌      | 104/291 [00:27<01:11,  2.60it/s]
Loading 0:  37%|███▋      | 107/291 [00:27<00:41,  4.42it/s]
Loading 0:  37%|███▋      | 108/291 [00:27<00:39,  4.66it/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,  2.61it/s]
Loading 0:  40%|███▉      | 116/291 [00:29<00:39,  4.43it/s]
Loading 0:  40%|████      | 117/291 [00:29<00:36,  4.74it/s]
Loading 0:  41%|████      | 118/291 [00:30<00:32,  5.34it/s]
Loading 0:  41%|████      | 120/291 [00:30<00:38,  4.43it/s]
Loading 0:  42%|████▏     | 121/291 [00:31<00:51,  3.33it/s]
Loading 0:  42%|████▏     | 122/291 [00:31<01:04,  2.63it/s]
Loading 0:  43%|████▎     | 125/291 [00:32<00:37,  4.46it/s]
Loading 0:  43%|████▎     | 126/291 [00:32<00:35,  4.70it/s]
Loading 0:  44%|████▎     | 127/291 [00:32<00:31,  5.28it/s]
Loading 0:  44%|████▍     | 129/291 [00:32<00:36,  4.40it/s]
Loading 0:  45%|████▍     | 130/291 [00:33<00:48,  3.31it/s]
Loading 0:  45%|████▌     | 131/291 [00:34<01:02,  2.56it/s]
Loading 0:  46%|████▌     | 134/291 [00:34<00:36,  4.35it/s]
Loading 0:  46%|████▋     | 135/291 [00:34<00:33,  4.61it/s]
Loading 0:  47%|████▋     | 136/291 [00:34<00:30,  5.16it/s]
Loading 0:  47%|████▋     | 138/291 [00:35<00:35,  4.35it/s]
Loading 0:  48%|████▊     | 139/291 [00:35<00:46,  3.30it/s]
Loading 0:  48%|████▊     | 140/291 [00:36<00:58,  2.60it/s]
Loading 0:  49%|████▉     | 143/291 [00:36<00:33,  4.41it/s]
Loading 0:  49%|████▉     | 144/291 [00:36<00:31,  4.66it/s]
Loading 0:  50%|████▉     | 145/291 [00:36<00:27,  5.26it/s]
Loading 0:  51%|█████     | 147/291 [00:37<00:32,  4.40it/s]
Loading 0:  51%|█████     | 148/291 [00:38<00:43,  3.31it/s]
Loading 0:  51%|█████     | 149/291 [00:38<00:54,  2.61it/s]
Loading 0:  52%|█████▏    | 152/291 [00:38<00:30,  4.50it/s]
Loading 0:  53%|█████▎    | 153/291 [00:39<00:29,  4.74it/s]
Loading 0:  53%|█████▎    | 154/291 [00:39<00:25,  5.34it/s]
Loading 0:  54%|█████▎    | 156/291 [00:39<00:30,  4.43it/s]
Loading 0:  54%|█████▍    | 157/291 [00:40<00:40,  3.34it/s]
Loading 0:  54%|█████▍    | 158/291 [00:40<00:50,  2.64it/s]
Loading 0:  55%|█████▌    | 161/291 [00:41<00:28,  4.49it/s]
Loading 0:  56%|█████▌    | 162/291 [00:41<00:27,  4.73it/s]
Loading 0:  56%|█████▌    | 163/291 [00:41<00:24,  5.33it/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,  2.62it/s]
Loading 0:  58%|█████▊    | 170/291 [00:43<00:26,  4.51it/s]
Loading 0:  59%|█████▉    | 171/291 [00:43<00:25,  4.74it/s]
Loading 0:  59%|█████▉    | 172/291 [00:43<00:22,  5.30it/s]
Loading 0:  59%|█████▉    | 173/291 [00:44<00:32,  3.58it/s]
Loading 0:  60%|██████    | 175/291 [00:44<00:23,  4.88it/s]
Loading 0:  60%|██████    | 176/291 [00:44<00:22,  5.11it/s]
Loading 0:  61%|██████    | 177/291 [00:44<00:20,  5.68it/s]
Loading 0:  62%|██████▏   | 179/291 [00:45<00:25,  4.46it/s]
Loading 0:  62%|██████▏   | 180/291 [00:45<00:33,  3.30it/s]
Loading 0:  62%|██████▏   | 181/291 [00:46<00:42,  2.58it/s]
Loading 0:  63%|██████▎   | 184/291 [00:46<00:24,  4.45it/s]
Loading 0:  64%|██████▎   | 185/291 [00:46<00:22,  4.70it/s]
Loading 0:  64%|██████▍   | 186/291 [00:47<00:20,  5.21it/s]
Loading 0:  64%|██████▍   | 187/291 [00:47<00:19,  5.25it/s]
Loading 0:  65%|██████▍   | 188/291 [00:47<00:29,  3.48it/s]
Loading 0:  65%|██████▍   | 189/291 [00:48<00:39,  2.59it/s]
Loading 0:  66%|██████▌   | 192/291 [00:49<00:28,  3.53it/s]
Loading 0:  66%|██████▋   | 193/291 [00:49<00:33,  2.93it/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,  4.41it/s]
Loading 0:  68%|██████▊   | 199/291 [00:50<00:18,  4.98it/s]
Loading 0:  69%|██████▉   | 201/291 [00:51<00:21,  4.28it/s]
Loading 0:  69%|██████▉   | 202/291 [00:51<00:27,  3.27it/s]
Loading 0:  70%|██████▉   | 203/291 [00:52<00:33,  2.61it/s]
Loading 0:  71%|███████   | 206/291 [00:52<00:19,  4.42it/s]
Loading 0:  71%|███████   | 207/291 [00:52<00:18,  4.66it/s]
Loading 0:  71%|███████▏  | 208/291 [00:52<00:16,  5.18it/s]
Loading 0:  72%|███████▏  | 210/291 [00:53<00:18,  4.38it/s]
Loading 0:  73%|███████▎  | 211/291 [00:54<00:24,  3.31it/s]
Loading 0:  73%|███████▎  | 212/291 [00:54<00:30,  2.62it/s]
Loading 0:  74%|███████▍  | 215/291 [00:54<00:17,  4.46it/s]
Loading 0:  74%|███████▍  | 216/291 [00:55<00:15,  4.69it/s]
Loading 0:  75%|███████▍  | 217/291 [00:55<00:14,  5.22it/s]
Loading 0:  75%|███████▌  | 219/291 [00:55<00:16,  4.38it/s]
Loading 0:  76%|███████▌  | 220/291 [00:56<00:21,  3.32it/s]
Loading 0:  76%|███████▌  | 221/291 [00:57<00:26,  2.64it/s]
Loading 0:  77%|███████▋  | 224/291 [00:57<00:14,  4.52it/s]
Loading 0:  77%|███████▋  | 225/291 [00:57<00:13,  4.74it/s]
Loading 0:  78%|███████▊  | 226/291 [00:57<00:12,  5.26it/s]
Loading 0:  78%|███████▊  | 228/291 [00:58<00:14,  4.36it/s]
Loading 0:  79%|███████▊  | 229/291 [00:58<00:18,  3.28it/s]
Loading 0:  79%|███████▉  | 230/291 [00:59<00:23,  2.60it/s]
Loading 0:  80%|████████  | 233/291 [00:59<00:13,  4.45it/s]
Loading 0:  80%|████████  | 234/291 [00:59<00:12,  4.68it/s]
Loading 0:  81%|████████  | 235/291 [00:59<00:10,  5.23it/s]
Loading 0:  81%|████████▏ | 237/291 [01:00<00:12,  4.35it/s]
Loading 0:  82%|████████▏ | 238/291 [01:00<00:16,  3.30it/s]
Loading 0:  82%|████████▏ | 239/291 [01:01<00:20,  2.58it/s]
Loading 0:  83%|████████▎ | 242/291 [01:01<00:11,  4.41it/s]
Loading 0:  84%|████████▎ | 243/291 [01:01<00:10,  4.62it/s]
Loading 0:  84%|████████▍ | 244/291 [01:02<00:09,  5.15it/s]
Loading 0:  85%|████████▍ | 246/291 [01:02<00:10,  4.19it/s]
Loading 0:  85%|████████▍ | 247/291 [01:03<00:13,  3.15it/s]
Loading 0:  85%|████████▌ | 248/291 [01:03<00:17,  2.48it/s]
Loading 0:  86%|████████▋ | 251/291 [01:04<00:09,  4.25it/s]
Loading 0:  87%|████████▋ | 252/291 [01:04<00:08,  4.48it/s]
Loading 0:  87%|████████▋ | 253/291 [01:04<00:07,  5.02it/s]
Loading 0:  88%|████████▊ | 255/291 [01:05<00:08,  4.24it/s]
Loading 0:  88%|████████▊ | 256/291 [01:05<00:10,  3.25it/s]
Loading 0:  88%|████████▊ | 257/291 [01:06<00:13,  2.60it/s]
Loading 0:  89%|████████▉ | 260/291 [01:06<00:07,  4.39it/s]
Loading 0:  90%|████████▉ | 261/291 [01:06<00:06,  4.61it/s]
Loading 0:  90%|█████████ | 262/291 [01:06<00:05,  5.10it/s]
Loading 0:  91%|█████████ | 264/291 [01:07<00:06,  4.28it/s]
Loading 0:  91%|█████████ | 265/291 [01:07<00:08,  3.24it/s]
Loading 0:  91%|█████████▏| 266/291 [01:08<00:09,  2.58it/s]
Loading 0:  92%|█████████▏| 269/291 [01:08<00:04,  4.44it/s]
Loading 0:  93%|█████████▎| 270/291 [01:08<00:04,  4.67it/s]
Loading 0:  93%|█████████▎| 271/291 [01:09<00:03,  5.24it/s]
Loading 0:  94%|█████████▍| 273/291 [01:09<00:04,  4.34it/s]
Loading 0:  94%|█████████▍| 274/291 [01:10<00:05,  3.26it/s]
Loading 0:  95%|█████████▍| 275/291 [01:10<00:06,  2.57it/s]
Loading 0:  96%|█████████▌| 278/291 [01:11<00:02,  4.40it/s]
Loading 0:  96%|█████████▌| 279/291 [01:11<00:02,  4.63it/s]
Loading 0:  96%|█████████▌| 280/291 [01:11<00:02,  5.02it/s]
Loading 0:  97%|█████████▋| 281/291 [01:11<00:02,  3.40it/s]
Loading 0:  97%|█████████▋| 282/291 [01:12<00:03,  2.54it/s]
Loading 0:  98%|█████████▊| 284/291 [01:12<00:01,  3.66it/s]
Loading 0:  98%|█████████▊| 285/291 [01:13<00:01,  4.02it/s]
Loading 0:  98%|█████████▊| 286/291 [01:13<00:01,  4.65it/s]
Loading 0:  99%|█████████▊| 287/291 [01:13<00:00,  4.79it/s]
Loading 0:  99%|█████████▉| 288/291 [01:13<00:00,  3.17it/s]
                                                            
Job alexdaoud-trainer-bagir-1291-v1-mkmlizer completed after 153.4s with status: succeeded
Stopping job with name alexdaoud-trainer-bagir-1291-v1-mkmlizer
Pipeline stage MKMLizer completed in 153.96s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.22s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service alexdaoud-trainer-bagir-1291-v1
Waiting for inference service alexdaoud-trainer-bagir-1291-v1 to be ready
Inference service alexdaoud-trainer-bagir-1291-v1 ready after 210.7981264591217s
Pipeline stage MKMLDeployer completed in 211.38s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.7510182857513428s
Received healthy response to inference request in 3.2313060760498047s
Received healthy response to inference request in 2.1622250080108643s
Received healthy response to inference request in 2.366624116897583s
Received healthy response to inference request in 5.447012901306152s
5 requests
0 failed requests
5th percentile: 2.203104829788208
10th percentile: 2.243984651565552
20th percentile: 2.325744295120239
30th percentile: 2.5395605087280275
40th percentile: 2.885433292388916
50th percentile: 3.2313060760498047
60th percentile: 3.43919095993042
70th percentile: 3.647075843811035
80th percentile: 4.090217208862305
90th percentile: 4.768615055084228
95th percentile: 5.10781397819519
99th percentile: 5.37917311668396
mean time: 3.3916372776031496
Pipeline stage StressChecker completed in 18.22s
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 2.43s
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 2.25s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1291_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 0.11s
run pipeline stage %s
Running pipeline stage MKMLProfilerTemplater
Pipeline stage MKMLProfilerTemplater completed in 0.09s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1291-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1291-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1291-v1-profiler ready after 210.47577238082886s
Pipeline stage MKMLProfilerDeployer completed in 210.80s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplonzhxr:/code/chaiverse_profiler_1734303711 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplonzhxr --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734303711 && 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_1734303711/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplonzhxr:/code/chaiverse_profiler_1734306466 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplonzhxr --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734306466 && 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_1734306466/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1291-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1291-v1-profiler
Service alexdaoud-trainer-bagir-1291-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.26s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1291-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 0.10s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeployer
Creating inference service alexdaoud-trainer-bagir-1291-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1291-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1291-v1-profiler ready after 40.11312246322632s
Pipeline stage MKMLProfilerDeployer completed in 40.38s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplohhhjw:/code/chaiverse_profiler_1734307165 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplohhhjw --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734307165 && 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_1734307165/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplohhhjw:/code/chaiverse_profiler_1734309942 --namespace tenant-chaiml-guanaco
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplohhhjw:/code/chaiverse_profiler_1734309942 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplohhhjw --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734309942 && 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_1734309942/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1291-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1291-v1-profiler
Service alexdaoud-trainer-bagir-1291-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.12s
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1291-v1-profiler is running
Skipping teardown as no inference service was found
Pipeline stage MKMLProfilerDeleter completed in 2.44s
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-1291-v1-profiler
Waiting for inference service alexdaoud-trainer-bagir-1291-v1-profiler to be ready
Inference service alexdaoud-trainer-bagir-1291-v1-profiler ready after 70.1758177280426s
Pipeline stage MKMLProfilerDeployer completed in 70.49s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplowkvz4:/code/chaiverse_profiler_1734310818 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplowkvz4 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734310818 && 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_1734310818/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplowkvz4:/code/chaiverse_profiler_1734313603 --namespace tenant-chaiml-guanaco
kubectl exec -it alexdaoud-trainer-baa1486edb390d3827558b06e06ba73616-deplowkvz4 --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1734313603 && 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_1734313603/summary.json'
Received signal 2, running shutdown handler
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service alexdaoud-trainer-bagir-1291-v1-profiler is running
Tearing down inference service alexdaoud-trainer-bagir-1291-v1-profiler
Service alexdaoud-trainer-bagir-1291-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.19s
Shutdown handler de-registered
alexdaoud-trainer-bagir-_1291_v1 status is now inactive due to auto deactivation removed underperforming models