junhua024-chai-06-full-_59231

developer_uid: junhua024
submission_id: junhua024-chai-06-full-_59231_v3
model_name: junhua024-chai-06-full-_59231_v3
model_group: junhua024/chai_06_full_0
status: torndown
timestamp: 2025-07-17T18:33:28+00:00
num_battles: 8115
num_wins: 4021
celo_rating: 1279.06
family_friendly_score: 0.5646
family_friendly_standard_error: 0.0070118020508283035
submission_type: basic
model_repo: junhua024/chai_06_full_02108_2024
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.5955842855471131, 'latency_mean': 1.6789027047157288, 'latency_p50': 1.6737332344055176, 'latency_p90': 1.8465497493743896}, {'batch_size': 3, 'throughput': 1.0737617777580666, 'latency_mean': 2.7873746073246, 'latency_p50': 2.77802574634552, 'latency_p90': 3.1055428266525267}, {'batch_size': 5, 'throughput': 1.3076289184744903, 'latency_mean': 3.803553642034531, 'latency_p50': 3.7497438192367554, 'latency_p90': 4.240948915481567}, {'batch_size': 6, 'throughput': 1.3536807419873929, 'latency_mean': 4.415419106483459, 'latency_p50': 4.412023305892944, 'latency_p90': 4.900432920455932}, {'batch_size': 8, 'throughput': 1.4189216171825625, 'latency_mean': 5.593540266752243, 'latency_p50': 5.632370591163635, 'latency_p90': 6.353191566467285}, {'batch_size': 10, 'throughput': 1.4539312236833235, 'latency_mean': 6.8097298002243045, 'latency_p50': 6.855787754058838, 'latency_p90': 7.645300722122192}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: junhua024-chai-06-full-_59231_v3
is_internal_developer: False
language_model: junhua024/chai_06_full_02108_2024
model_size: 13B
ranking_group: single
throughput_3p7s: 1.3
us_pacific_date: 2025-07-17
win_ratio: 0.49550215650030804
generation_params: {'temperature': 1.0, 'top_p': 0.88, 'min_p': 0.0, 'top_k': 10, 'presence_penalty': 0.0, 'frequency_penalty': 0.0, 'stopping_words': ['\n'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
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 junhua024-chai-06-full-59231-v3-mkmlizer
Waiting for job on junhua024-chai-06-full-59231-v3-mkmlizer to finish
junhua024-chai-06-full-59231-v3-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
junhua024-chai-06-full-59231-v3-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   ██████   ██████  █████   ████  ████                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  ░░██████ ██████  ░░███   ███░  ░░███                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   ░███░█████░███   ░███  ███     ░███                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   ░███░░███ ░███   ░███████      ░███                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   ░███ ░░░  ░███   ░███░░███     ░███                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   ░███      ░███   ░███ ░░███    ░███                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║   █████     █████  █████ ░░████  █████                              ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  ░░░░░     ░░░░░  ░░░░░   ░░░░  ░░░░░                               ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Version: 0.29.15                                                   ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Features: FLYWHEEL, CUDA                                           ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Copyright 2023-2025 MK ONE TECHNOLOGIES Inc.                       ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  https://mk1.ai                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  The license key for the current software has been verified as      ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  belonging to:                                                      ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Chai Research Corp.                                                ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f                   ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║  Expiration: 2028-03-31 23:59:59                                    ║
junhua024-chai-06-full-59231-v3-mkmlizer: ║                                                                     ║
junhua024-chai-06-full-59231-v3-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
Failed to get response for submission junhua024-chai-06-full-_60967_v6: HTTPConnectionPool(host='junhua024-chai-06-full-60967-v6-predictor.tenant-chaiml-guanaco.k.chaiverse.com', port=80): Read timed out. (read timeout=12.0)
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Xet Storage is enabled for this repo, but the 'hf_xet' package is not installed. Falling back to regular HTTP download. For better performance, install the package with: `pip install huggingface_hub[hf_xet]` or `pip install hf_xet`
junhua024-chai-06-full-59231-v3-mkmlizer: Downloaded to shared memory in 113.414s
junhua024-chai-06-full-59231-v3-mkmlizer: Checking if junhua024/chai_06_full_02108_2024 already exists in ChaiML
junhua024-chai-06-full-59231-v3-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpzirc241e, device:0
junhua024-chai-06-full-59231-v3-mkmlizer: Saving flywheel model at /dev/shm/model_cache
junhua024-chai-06-full-59231-v3-mkmlizer: quantized model in 32.885s
junhua024-chai-06-full-59231-v3-mkmlizer: Processed model junhua024/chai_06_full_02108_2024 in 146.374s
junhua024-chai-06-full-59231-v3-mkmlizer: creating bucket guanaco-mkml-models
junhua024-chai-06-full-59231-v3-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
junhua024-chai-06-full-59231-v3-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia
junhua024-chai-06-full-59231-v3-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia/config.json
junhua024-chai-06-full-59231-v3-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia/special_tokens_map.json
junhua024-chai-06-full-59231-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia/tokenizer_config.json
junhua024-chai-06-full-59231-v3-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia/tokenizer.json
junhua024-chai-06-full-59231-v3-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/junhua024-chai-06-full-59231-v3/nvidia/flywheel_model.0.safetensors
junhua024-chai-06-full-59231-v3-mkmlizer: 
Loading 0:   0%|          | 0/363 [00:00<?, ?it/s]
Loading 0:   1%|          | 2/363 [00:00<00:24, 14.98it/s]
Loading 0:   1%|▏         | 5/363 [00:00<00:20, 17.41it/s]
Loading 0:   3%|▎         | 11/363 [00:00<00:11, 31.65it/s]
Loading 0:   4%|▍         | 15/363 [00:00<00:10, 33.89it/s]
Loading 0:   5%|▌         | 19/363 [00:00<00:12, 28.03it/s]
Loading 0:   6%|▋         | 23/363 [00:00<00:12, 27.88it/s]
Loading 0:   8%|▊         | 29/363 [00:00<00:09, 35.47it/s]
Loading 0:   9%|▉         | 34/363 [00:01<00:09, 32.91it/s]
Loading 0:  10%|█         | 38/363 [00:01<00:09, 32.90it/s]
Loading 0:  12%|█▏        | 42/363 [00:01<00:10, 30.78it/s]
Loading 0:  13%|█▎        | 49/363 [00:01<00:07, 39.67it/s]
Loading 0:  15%|█▍        | 54/363 [00:01<00:10, 28.28it/s]
Loading 0:  16%|█▋        | 59/363 [00:01<00:10, 30.28it/s]
Loading 0:  18%|█▊        | 65/363 [00:02<00:09, 30.92it/s]
Loading 0:  19%|█▉        | 69/363 [00:02<00:09, 29.78it/s]
Loading 0:  20%|██        | 74/363 [00:02<00:08, 32.69it/s]
Loading 0:  21%|██▏       | 78/363 [00:02<00:08, 33.28it/s]
Loading 0:  23%|██▎       | 82/363 [00:02<00:09, 28.57it/s]
Loading 0:  24%|██▎       | 86/363 [00:02<00:09, 30.37it/s]
Loading 0:  25%|██▌       | 91/363 [00:02<00:08, 31.33it/s]
Loading 0:  27%|██▋       | 97/363 [00:03<00:08, 31.70it/s]
Loading 0:  28%|██▊       | 101/363 [00:03<00:08, 31.59it/s]
Loading 0:  29%|██▉       | 105/363 [00:03<00:08, 28.98it/s]
Loading 0:  31%|███       | 111/363 [00:03<00:07, 35.42it/s]
Loading 0:  32%|███▏      | 115/363 [00:03<00:08, 29.37it/s]
Loading 0:  33%|███▎      | 119/363 [00:03<00:07, 30.52it/s]
Loading 0:  34%|███▍      | 123/363 [00:04<00:08, 29.63it/s]
Loading 0:  35%|███▌      | 128/363 [00:04<00:08, 28.05it/s]
Loading 0:  36%|███▌      | 131/363 [00:04<00:08, 25.95it/s]
Loading 0:  38%|███▊      | 137/363 [00:04<00:07, 31.95it/s]
Loading 0:  39%|███▉      | 141/363 [00:04<00:06, 32.03it/s]
Loading 0:  40%|███▉      | 145/363 [00:04<00:07, 27.60it/s]
Loading 0:  41%|████      | 149/363 [00:04<00:07, 27.47it/s]
Loading 0:  43%|████▎     | 155/363 [00:05<00:06, 33.58it/s]
Loading 0:  44%|████▍     | 160/363 [00:05<00:06, 31.42it/s]
Loading 0:  45%|████▌     | 164/363 [00:05<00:06, 31.40it/s]
Loading 0:  46%|████▋     | 168/363 [00:05<00:06, 29.69it/s]
Loading 0:  48%|████▊     | 174/363 [00:05<00:05, 36.29it/s]
Loading 0:  49%|████▉     | 178/363 [00:05<00:06, 30.21it/s]
Loading 0:  50%|█████     | 182/363 [00:05<00:05, 30.55it/s]
Loading 0:  51%|█████     | 186/363 [00:06<00:06, 29.30it/s]
Loading 0:  53%|█████▎    | 191/363 [00:06<00:06, 28.42it/s]
Loading 0:  53%|█████▎    | 194/363 [00:06<00:06, 26.45it/s]
Loading 0:  55%|█████▌    | 200/363 [00:06<00:04, 32.76it/s]
Loading 0:  56%|█████▌    | 204/363 [00:06<00:04, 33.27it/s]
Loading 0:  57%|█████▋    | 208/363 [00:06<00:05, 28.45it/s]
Loading 0:  58%|█████▊    | 212/363 [00:06<00:05, 27.88it/s]
Loading 0:  60%|██████    | 218/363 [00:07<00:04, 33.88it/s]
Loading 0:  61%|██████▏   | 223/363 [00:07<00:04, 31.54it/s]
Loading 0:  63%|██████▎   | 227/363 [00:07<00:04, 31.56it/s]
Loading 0:  64%|██████▎   | 231/363 [00:07<00:04, 29.40it/s]
Loading 0:  65%|██████▌   | 237/363 [00:07<00:03, 36.20it/s]
Loading 0:  66%|██████▋   | 241/363 [00:07<00:04, 30.27it/s]
Loading 0:  67%|██████▋   | 245/363 [00:07<00:03, 31.28it/s]
Loading 0:  69%|██████▊   | 249/363 [00:08<00:03, 30.59it/s]
Loading 0:  70%|██████▉   | 254/363 [00:08<00:03, 29.24it/s]
Loading 0:  71%|███████   | 258/363 [00:08<00:03, 28.91it/s]
Loading 0:  72%|███████▏  | 263/363 [00:08<00:03, 32.53it/s]
Loading 0:  74%|███████▎  | 267/363 [00:08<00:02, 33.39it/s]
Loading 0:  75%|███████▍  | 271/363 [00:08<00:03, 28.51it/s]
Loading 0:  76%|███████▌  | 275/363 [00:09<00:03, 28.00it/s]
Loading 0:  77%|███████▋  | 281/363 [00:09<00:02, 33.97it/s]
Loading 0:  79%|███████▉  | 286/363 [00:09<00:02, 31.90it/s]
Loading 0:  80%|███████▉  | 290/363 [00:09<00:02, 32.15it/s]
Loading 0:  81%|████████  | 294/363 [00:09<00:02, 30.05it/s]
Loading 0:  83%|████████▎ | 300/363 [00:09<00:01, 36.39it/s]
Loading 0:  84%|████████▎ | 304/363 [00:09<00:01, 30.77it/s]
Loading 0:  85%|████████▍ | 308/363 [00:09<00:01, 31.67it/s]
Loading 0:  86%|████████▌ | 312/363 [00:10<00:01, 30.27it/s]
Loading 0:  87%|████████▋ | 316/363 [00:10<00:01, 31.89it/s]
Loading 0:  88%|████████▊ | 320/363 [00:10<00:01, 25.37it/s]
Loading 0:  90%|████████▉ | 326/363 [00:10<00:01, 31.80it/s]
Loading 0:  91%|█████████ | 330/363 [00:10<00:01, 32.52it/s]
Loading 0:  92%|█████████▏| 334/363 [00:10<00:01, 27.89it/s]
Loading 0:  93%|█████████▎| 338/363 [00:11<00:00, 27.45it/s]
Loading 0:  95%|█████████▍| 344/363 [00:11<00:00, 33.02it/s]
Loading 0:  96%|█████████▌| 349/363 [00:11<00:00, 22.45it/s]
Loading 0:  97%|█████████▋| 352/363 [00:11<00:00, 19.60it/s]
Loading 0:  98%|█████████▊| 357/363 [00:11<00:00, 23.53it/s]
                                                            
Job junhua024-chai-06-full-59231-v3-mkmlizer completed after 171.05s with status: succeeded
Stopping job with name junhua024-chai-06-full-59231-v3-mkmlizer
Pipeline stage MKMLizer completed in 171.70s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.54s
run pipeline stage %s
Running pipeline stage MKMLDeployer
Creating inference service junhua024-chai-06-full-59231-v3
Waiting for inference service junhua024-chai-06-full-59231-v3 to be ready
Inference service junhua024-chai-06-full-59231-v3 ready after 291.3644871711731s
Pipeline stage MKMLDeployer completed in 291.96s
run pipeline stage %s
Running pipeline stage StressChecker
Received healthy response to inference request in 3.853058099746704s
Received healthy response to inference request in 4.308348178863525s
Received healthy response to inference request in 2.805807113647461s
Received healthy response to inference request in 6.904388904571533s
Received healthy response to inference request in 1.8698439598083496s
5 requests
0 failed requests
5th percentile: 2.057036590576172
10th percentile: 2.244229221343994
20th percentile: 2.6186144828796385
30th percentile: 3.0152573108673097
40th percentile: 3.434157705307007
50th percentile: 3.853058099746704
60th percentile: 4.035174131393433
70th percentile: 4.217290163040161
80th percentile: 4.827556324005127
90th percentile: 5.865972614288331
95th percentile: 6.3851807594299315
99th percentile: 6.800547275543213
mean time: 3.9482892513275147
%s, retrying in %s seconds...
Received healthy response to inference request in 7.083204746246338s
Received healthy response to inference request in 2.0706019401550293s
Received healthy response to inference request in 6.5830090045928955s
Received healthy response to inference request in 2.3587498664855957s
Received healthy response to inference request in 1.7157387733459473s
5 requests
0 failed requests
5th percentile: 1.7867114067077636
10th percentile: 1.85768404006958
20th percentile: 1.999629306793213
30th percentile: 2.1282315254211426
40th percentile: 2.243490695953369
50th percentile: 2.3587498664855957
60th percentile: 4.048453521728515
70th percentile: 5.738157176971435
80th percentile: 6.683048152923584
90th percentile: 6.883126449584961
95th percentile: 6.983165597915649
99th percentile: 7.0631969165802
mean time: 3.962260866165161
%s, retrying in %s seconds...
Received healthy response to inference request in 11.966540575027466s
Received healthy response to inference request in 1.568955421447754s
Received healthy response to inference request in 1.6499857902526855s
Received healthy response to inference request in 1.890458583831787s
Received healthy response to inference request in 1.7321572303771973s
5 requests
0 failed requests
5th percentile: 1.5851614952087403
10th percentile: 1.6013675689697267
20th percentile: 1.6337797164916992
30th percentile: 1.666420078277588
40th percentile: 1.6992886543273926
50th percentile: 1.7321572303771973
60th percentile: 1.7954777717590331
70th percentile: 1.8587983131408692
80th percentile: 3.9056749820709245
90th percentile: 7.936107778549196
95th percentile: 9.95132417678833
99th percentile: 11.563497295379639
mean time: 3.761619520187378
Pipeline stage StressChecker completed in 63.33s
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 1.13s
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 0.79s
Shutdown handler de-registered
junhua024-chai-06-full-_59231_v3 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 0.17s
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 junhua024-chai-06-full-59231-v3-profiler
Waiting for inference service junhua024-chai-06-full-59231-v3-profiler to be ready
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 4777.52s
Shutdown handler de-registered
junhua024-chai-06-full-_59231_v3 status is now inactive due to auto deactivation removed underperforming models
junhua024-chai-06-full-_59231_v3 status is now torndown due to DeploymentManager action
junhua024-chai-06-full-_59231_v3 status is now torndown due to DeploymentManager action