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 chaiml-llama8b-retune7-29658-v1-mkmlizer
Waiting for job on chaiml-llama8b-retune7-29658-v1-mkmlizer to finish
chaiml-llama8b-retune7-29658-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ██████ ██████ █████ ████ ████ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░░██████ ██████ ░░███ ███░ ░░███ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░███░█████░███ ░███ ███ ░███ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░███░░███ ░███ ░███████ ░███ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░███ ░░░ ░███ ░███░░███ ░███ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░███ ░███ ░███ ░░███ ░███ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ █████ █████ █████ ░░████ █████ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ░░░░░ ░░░░░ ░░░░░ ░░░░ ░░░░░ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Version: 0.29.3 ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ https://mk1.ai ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ The license key for the current software has been verified as ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ belonging to: ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Chai Research Corp. ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ║ ║
chaiml-llama8b-retune7-29658-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
chaiml-llama8b-retune7-29658-v1-mkmlizer: Downloaded to shared memory in 30.219s
chaiml-llama8b-retune7-29658-v1-mkmlizer: Checking if ChaiML/llama8b-retune7-rm-pointwise-datav1-900k-1e-64mckpt-newlinfull-seq512-1 already exists in ChaiML
chaiml-llama8b-retune7-29658-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:t0, folder:/tmp/tmp_nowtqv0, device:0
chaiml-llama8b-retune7-29658-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
chaiml-llama8b-retune7-29658-v1-mkmlizer: quantized model in 19.527s
chaiml-llama8b-retune7-29658-v1-mkmlizer: Processed model ChaiML/llama8b-retune7-rm-pointwise-datav1-900k-1e-64mckpt-newlinfull-seq512-1 in 49.746s
chaiml-llama8b-retune7-29658-v1-mkmlizer: creating bucket guanaco-mkml-models
chaiml-llama8b-retune7-29658-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
chaiml-llama8b-retune7-29658-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1
chaiml-llama8b-retune7-29658-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1/config.json
chaiml-llama8b-retune7-29658-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1/special_tokens_map.json
chaiml-llama8b-retune7-29658-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1/tokenizer_config.json
chaiml-llama8b-retune7-29658-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1/tokenizer.json
chaiml-llama8b-retune7-29658-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/chaiml-llama8b-retune7-29658-v1/flywheel_model.0.safetensors
chaiml-llama8b-retune7-29658-v1-mkmlizer:
Loading 0: 0%| | 0/291 [00:00<?, ?it/s]
Loading 0: 2%|▏ | 5/291 [00:00<00:08, 32.61it/s]
Loading 0: 4%|▍ | 13/291 [00:00<00:05, 52.26it/s]
Loading 0: 7%|▋ | 19/291 [00:00<00:05, 45.51it/s]
Loading 0: 8%|▊ | 24/291 [00:00<00:05, 44.80it/s]
Loading 0: 11%|█ | 31/291 [00:00<00:05, 50.57it/s]
Loading 0: 13%|█▎ | 37/291 [00:00<00:05, 46.07it/s]
Loading 0: 14%|█▍ | 42/291 [00:00<00:05, 45.40it/s]
Loading 0: 17%|█▋ | 49/291 [00:01<00:04, 50.11it/s]
Loading 0: 19%|█▉ | 55/291 [00:01<00:05, 44.87it/s]
Loading 0: 21%|██ | 60/291 [00:01<00:05, 43.91it/s]
Loading 0: 23%|██▎ | 67/291 [00:01<00:04, 48.48it/s]
Loading 0: 25%|██▍ | 72/291 [00:01<00:04, 48.78it/s]
Loading 0: 26%|██▋ | 77/291 [00:01<00:05, 39.62it/s]
Loading 0: 29%|██▊ | 83/291 [00:02<00:07, 29.53it/s]
Loading 0: 30%|██▉ | 87/291 [00:02<00:06, 30.22it/s]
Loading 0: 32%|███▏ | 94/291 [00:02<00:05, 37.01it/s]
Loading 0: 34%|███▍ | 99/291 [00:02<00:04, 39.48it/s]
Loading 0: 36%|███▌ | 104/291 [00:02<00:05, 35.27it/s]
Loading 0: 38%|███▊ | 111/291 [00:02<00:04, 42.66it/s]
Loading 0: 40%|███▉ | 116/291 [00:02<00:04, 43.19it/s]
Loading 0: 42%|████▏ | 121/291 [00:02<00:03, 44.54it/s]
Loading 0: 44%|████▎ | 127/291 [00:03<00:03, 42.29it/s]
Loading 0: 45%|████▌ | 132/291 [00:03<00:03, 42.36it/s]
Loading 0: 48%|████▊ | 139/291 [00:03<00:03, 47.88it/s]
Loading 0: 50%|████▉ | 145/291 [00:03<00:03, 44.08it/s]
Loading 0: 52%|█████▏ | 150/291 [00:03<00:03, 41.88it/s]
Loading 0: 54%|█████▎ | 156/291 [00:03<00:02, 46.21it/s]
Loading 0: 55%|█████▌ | 161/291 [00:03<00:02, 45.79it/s]
Loading 0: 57%|█████▋ | 166/291 [00:03<00:02, 46.11it/s]
Loading 0: 59%|█████▉ | 172/291 [00:04<00:02, 43.18it/s]
Loading 0: 62%|██████▏ | 179/291 [00:04<00:02, 48.24it/s]
Loading 0: 63%|██████▎ | 184/291 [00:04<00:02, 48.18it/s]
Loading 0: 65%|██████▍ | 189/291 [00:04<00:03, 28.08it/s]
Loading 0: 67%|██████▋ | 194/291 [00:04<00:03, 30.92it/s]
Loading 0: 69%|██████▉ | 201/291 [00:04<00:02, 38.60it/s]
Loading 0: 71%|███████ | 206/291 [00:04<00:02, 40.15it/s]
Loading 0: 73%|███████▎ | 211/291 [00:05<00:01, 41.84it/s]
Loading 0: 74%|███████▍ | 216/291 [00:05<00:01, 43.67it/s]
Loading 0: 76%|███████▌ | 221/291 [00:05<00:01, 36.63it/s]
Loading 0: 78%|███████▊ | 228/291 [00:05<00:01, 44.15it/s]
Loading 0: 80%|████████ | 233/291 [00:05<00:01, 44.04it/s]
Loading 0: 82%|████████▏ | 238/291 [00:05<00:01, 43.34it/s]
Loading 0: 84%|████████▍ | 244/291 [00:05<00:01, 42.01it/s]
Loading 0: 86%|████████▌ | 249/291 [00:05<00:00, 42.67it/s]
Loading 0: 88%|████████▊ | 256/291 [00:06<00:00, 48.43it/s]
Loading 0: 90%|█████████ | 262/291 [00:06<00:00, 44.88it/s]
Loading 0: 92%|█████████▏| 267/291 [00:06<00:00, 43.82it/s]
Loading 0: 94%|█████████▍| 274/291 [00:06<00:00, 48.99it/s]
Loading 0: 96%|█████████▌| 280/291 [00:06<00:00, 45.15it/s]
Loading 0: 98%|█████████▊| 285/291 [00:06<00:00, 45.15it/s]
Loading 0: 100%|█████████▉| 290/291 [00:06<00:00, 33.24it/s]
Job chaiml-llama8b-retune7-29658-v1-mkmlizer completed after 73.94s with status: succeeded
Stopping job with name chaiml-llama8b-retune7-29658-v1-mkmlizer
Pipeline stage MKMLizer completed in 74.53s
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 chaiml-llama8b-retune7-29658-v1
Waiting for inference service chaiml-llama8b-retune7-29658-v1 to be ready
Failed to get response for submission chaiml-giyu-disabled-hu_13897_v2: ('http://chaiml-giyu-disabled-hu-13897-v2-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
Inference service chaiml-llama8b-retune7-29658-v1 ready after 130.8127031326294s
Pipeline stage MKMLDeployer completed in 131.36s
run pipeline stage %s
Running pipeline stage StressChecker
Failed to get response for submission chaiml-giyu-disabled-hu_13897_v2: ('http://chaiml-giyu-disabled-hu-13897-v2-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '')
Received healthy response to inference request in 2.9787654876708984s
Received healthy response to inference request in 4.43377161026001s
Received healthy response to inference request in 5.1395227909088135s
Received healthy response to inference request in 3.953979730606079s
Received healthy response to inference request in 4.8145880699157715s
5 requests
0 failed requests
5th percentile: 3.1738083362579346
10th percentile: 3.3688511848449707
20th percentile: 3.758936882019043
30th percentile: 4.049938106536866
40th percentile: 4.241854858398438
50th percentile: 4.43377161026001
60th percentile: 4.5860981941223145
70th percentile: 4.738424777984619
80th percentile: 4.87957501411438
90th percentile: 5.009548902511597
95th percentile: 5.074535846710205
99th percentile: 5.126525402069092
mean time: 4.264125537872315
Pipeline stage StressChecker completed in 23.04s
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 0.72s
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 0.63s
Shutdown handler de-registered
chaiml-llama8b-retune7-_29658_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 0.16s
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 chaiml-llama8b-retune7-29658-v1-profiler
Waiting for inference service chaiml-llama8b-retune7-29658-v1-profiler to be ready
Inference service chaiml-llama8b-retune7-29658-v1-profiler ready after 131.8276391029358s
Pipeline stage MKMLProfilerDeployer completed in 132.57s
run pipeline stage %s
Running pipeline stage MKMLProfilerRunner
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj:/code/chaiverse_profiler_1750788110 --namespace tenant-chaiml-guanaco
kubectl exec -it chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1750788110 && 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 512 --output_tokens 1 --summary /code/chaiverse_profiler_1750788110/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj:/code/chaiverse_profiler_1750788505 --namespace tenant-chaiml-guanaco
kubectl exec -it chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1750788505 && 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 512 --output_tokens 1 --summary /code/chaiverse_profiler_1750788505/summary.json'
%s, retrying in %s seconds...
kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj:/code/chaiverse_profiler_1750788977 --namespace tenant-chaiml-guanaco
kubectl exec -it chaiml-llama8b-retunf1e559e16c8bb2c76cd30f4ae77890d3-deplonhqrj --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1750788977 && 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 512 --output_tokens 1 --summary /code/chaiverse_profiler_1750788977/summary.json'
clean up pipeline due to error=ISVCScriptError('Command failed with error: Defaulted container "kserve-container" out of: kserve-container, queue-proxy\nUnable to use a TTY - input is not a terminal or the right kind of file\n\n 0%| | 0/200 [00:00<?, ?it/s]\n 0%| | 1/200 [00:00<00:58, 3.41it/s]\n 1%| | 2/200 [00:00<00:55, 3.57it/s]\n 2%|▏ | 3/200 [00:03<05:34, 1.70s/it]\n 2%|▏ | 4/200 [00:07<08:00, 2.45s/it]\n 2%|▎ | 5/200 [00:11<09:10, 2.82s/it]\n 3%|▎ | 6/200 [00:11<06:10, 1.91s/it]\n 4%|▎ | 7/200 [00:14<07:53, 2.45s/it]\n 4%|▍ | 8/200 [00:18<08:57, 2.80s/it]\n 4%|▍ | 9/200 [00:21<09:23, 2.95s/it]\n 5%|▌ | 10/200 [00:21<06:43, 2.12s/it]\n 6%|▌ | 11/200 [00:22<04:54, 1.56s/it]\n 6%|▌ | 12/200 [00:25<06:43, 2.15s/it]\n 6%|▋ | 13/200 [00:29<08:03, 2.58s/it]\n 7%|▋ | 14/200 [00:32<08:49, 2.85s/it]\n 8%|▊ | 15/200 [00:36<09:19, 3.02s/it]\n 8%|▊ | 16/200 [00:36<06:36, 2.16s/it]\n 8%|▊ | 17/200 [00:39<07:46, 2.55s/it]\n 9%|▉ | 18/200 [00:39<05:39, 1.87s/it]\n 10%|▉ | 19/200 [00:40<04:12, 1.39s/it]\n 10%|█ | 20/200 [00:43<06:04, 2.02s/it]\n 10%|█ | 21/200 [00:44<04:27, 1.50s/it]\n 11%|█ | 22/200 [00:44<03:22, 1.14s/it]\n 12%|█▏ | 23/200 [00:47<05:31, 1.87s/it]\n 12%|█▏ | 24/200 [00:48<04:05, 1.40s/it]\n 12%|█▎ | 25/200 [00:51<05:51, 2.01s/it]\n 13%|█▎ | 26/200 [00:55<07:02, 2.43s/it]\n 14%|█▎ | 27/200 [00:58<08:01, 2.78s/it]\n 14%|█▍ | 28/200 [01:02<08:30, 2.97s/it]\n 14%|█▍ | 29/200 [01:05<08:53, 3.12s/it]\n 15%|█▌ | 30/200 [01:05<06:24, 2.26s/it]\n 16%|█▌ | 31/200 [01:09<07:27, 2.65s/it]\n 16%|█▌ | 32/200 [01:12<08:04, 2.88s/it]\n 16%|█▋ | 33/200 [01:16<08:31, 3.06s/it]\n 17%|█▋ | 34/200 [01:16<06:09, 2.23s/it]\n 18%|█▊ | 35/200 [01:16<04:32, 1.65s/it]\n 18%|█▊ | 36/200 [01:17<03:23, 1.24s/it]\n 18%|█▊ | 37/200 [01:17<02:35, 1.05it/s]\n 19%|█▉ | 38/200 [01:17<02:03, 1.32it/s]\n 20%|█▉ | 39/200 [01:17<01:39, 1.62it/s]\n 20%|██ | 40/200 [01:21<03:54, 1.46s/it]\n 20%|██ | 41/200 [01:24<05:27, 2.06s/it]\n 21%|██ | 42/200 [01:25<04:00, 1.52s/it]\n 22%|██▏ | 43/200 [01:25<03:01, 1.15s/it]\n 22%|██▏ | 44/200 [01:28<04:51, 1.87s/it]\n 22%|██▎ | 45/200 [01:32<06:02, 2.34s/it]\n 23%|██▎ | 46/200 [01:32<04:18, 1.68s/it]\n 24%|██▎ | 47/200 [01:32<03:13, 1.26s/it]\n 24%|██▍ | 48/200 [01:36<04:54, 1.93s/it]\n 24%|██▍ | 49/200 [01:36<03:38, 1.44s/it]\n 25%|██▌ | 50/200 [01:40<05:21, 2.14s/it]\n 26%|██▌ | 51/200 [01:40<03:48, 1.54s/it]\n 26%|██▌ | 52/200 [01:43<05:13, 2.12s/it]\n 26%|██▋ | 53/200 [01:47<06:16, 2.56s/it]\n 27%|██▋ | 54/200 [01:51<07:02, 2.90s/it]\n 28%|██▊ | 55/200 [01:51<04:59, 2.07s/it]\n 28%|██▊ | 56/200 [01:54<05:58, 2.49s/it]\n 28%|██▊ | 57/200 [01:58<06:46, 2.84s/it]\n 29%|██▉ | 58/200 [02:02<07:13, 3.05s/it]\n 30%|██▉ | 59/200 [02:05<07:29, 3.19s/it]\n 30%|███ | 60/200 [02:09<07:42, 3.30s/it]\n 30%|███ | 61/200 [02:12<07:46, 3.36s/it]\n 31%|███ | 62/200 [02:16<07:50, 3.41s/it]\n 32%|███▏ | 63/200 [02:19<07:49, 3.43s/it]\n 32%|███▏ | 64/200 [02:23<07:46, 3.43s/it]\n 32%|███▎ | 65/200 [02:23<05:29, 2.44s/it]\n 33%|███▎ | 66/200 [02:26<06:07, 2.74s/it]\n 34%|███▎ | 67/200 [02:26<04:25, 2.00s/it]\n 34%|███▍ | 68/200 [02:30<05:27, 2.48s/it]\n 34%|███▍ | 69/200 [02:30<03:52, 1.77s/it]\n 35%|███▌ | 70/200 [02:34<04:59, 2.30s/it]\n 36%|███▌ | 71/200 [02:37<05:39, 2.63s/it]\n 36%|███▌ | 72/200 [02:41<06:09, 2.89s/it]\n 36%|███▋ | 73/200 [02:44<06:30, 3.07s/it]\n 37%|███▋ | 74/200 [02:44<04:35, 2.19s/it]\n 38%|███▊ | 75/200 [02:48<05:28, 2.63s/it]\n 38%|███▊ | 76/200 [02:52<06:06, 2.96s/it]\n 38%|███▊ | 77/200 [02:55<06:22, 3.11s/it]\n 39%|███▉ | 78/200 [02:59<06:31, 3.21s/it]\n 40%|███▉ | 79/200 [03:02<06:38, 3.29s/it]\n 40%|████ | 80/200 [03:05<06:39, 3.33s/it]\n 40%|████ | 81/200 [03:09<06:39, 3.36s/it]\n 41%|████ | 82/200 [03:12<06:42, 3.41s/it]\n 42%|████▏ | 83/200 [03:16<06:39, 3.41s/it]\n 42%|████▏ | 84/200 [03:16<04:41, 2.43s/it]\n 42%|████▎ | 85/200 [03:20<05:21, 2.79s/it]\n 43%|████▎ | 86/200 [03:20<03:47, 2.00s/it]\n 44%|████▎ | 87/200 [03:20<02:47, 1.48s/it]\n 44%|████▍ | 88/200 [03:23<03:51, 2.07s/it]\n 44%|████▍ | 89/200 [03:27<04:37, 2.50s/it]\n 45%|████▌ | 90/200 [03:30<05:08, 2.80s/it]\n 46%|████▌ | 91/200 [03:31<03:38, 2.00s/it]\n 46%|████▌ | 92/200 [03:31<02:40, 1.49s/it]\n 46%|████▋ | 93/200 [03:34<03:43, 2.09s/it]\n 47%|████▋ | 94/200 [03:38<04:20, 2.46s/it]\n 48%|████▊ | 95/200 [03:38<03:09, 1.80s/it]\n 48%|████▊ | 96/200 [03:41<04:00, 2.32s/it]\n 48%|████▊ | 97/200 [03:42<02:55, 1.70s/it]\n 49%|████▉ | 98/200 [03:45<03:48, 2.24s/it]\n 50%|████▉ | 99/200 [03:49<04:22, 2.60s/it]\n 50%|█████ | 100/200 [03:52<04:47, 2.87s/it]\n 50%|█████ | 101/200 [03:56<05:03, 3.07s/it]\n 51%|█████ | 102/200 [03:59<05:12, 3.19s/it]\n 52%|█████▏ | 103/200 [03:59<03:40, 2.27s/it]\n 52%|█████▏ | 104/200 [04:03<04:15, 2.67s/it]\n 52%|█████▎ | 105/200 [04:06<04:33, 2.88s/it]\n 53%|█████▎ | 106/200 [04:10<04:46, 3.05s/it]\n 54%|█████▎ | 107/200 [04:13<04:59, 3.22s/it]\n 54%|█████▍ | 108/200 [04:17<05:00, 3.27s/it]\n 55%|█████▍ | 109/200 [04:17<03:31, 2.33s/it]\n 55%|█████▌ | 110/200 [04:21<04:05, 2.73s/it]\n 56%|█████▌ | 111/200 [04:21<02:53, 1.95s/it]\n 56%|█████▌ | 112/200 [04:21<02:07, 1.45s/it]\n 56%|█████▋ | 113/200 [04:24<02:59, 2.07s/it]\n 57%|█████▋ | 114/200 [04:28<03:33, 2.48s/it]\n 57%|█████▊ | 115/200 [04:31<03:59, 2.81s/it]\n 58%|█████▊ | 116/200 [04:35<04:11, 2.99s/it]\n 58%|█████▊ | 117/200 [04:38<04:20, 3.14s/it]\n 59%|█████▉ | 118/200 [04:42<04:25, 3.24s/it]\n 60%|█████▉ | 119/200 [04:45<04:29, 3.33s/it]\n 60%|██████ | 120/200 [04:49<04:31, 3.40s/it]\n 60%|██████ | 121/200 [04:49<03:11, 2.42s/it]\n 61%|██████ | 122/200 [04:49<02:18, 1.78s/it]\n 62%|██████▏ | 123/200 [04:53<02:59, 2.33s/it]\n 62%|██████▏ | 124/200 [04:57<03:25, 2.70s/it]\n 62%|██████▎ | 125/200 [05:00<03:41, 2.95s/it]\n 63%|██████▎ | 126/200 [05:04<03:50, 3.12s/it]\n 64%|██████▎ | 127/200 [05:07<03:55, 3.22s/it]\n 64%|██████▍ | 128/200 [05:11<03:58, 3.31s/it]\n 64%|██████▍ | 129/200 [05:11<02:47, 2.36s/it]\n 65%|██████▌ | 130/200 [05:14<03:09, 2.70s/it]\n 66%|██████▌ | 131/200 [05:14<02:16, 1.97s/it]\n 66%|██████▌ | 132/200 [05:15<01:39, 1.46s/it]\n 66%|██████▋ | 133/200 [05:15<01:14, 1.11s/it]\n 67%|██████▋ | 134/200 [05:15<00:56, 1.16it/s]\n 68%|██████▊ | 135/200 [05:19<01:45, 1.63s/it]\n 68%|██████▊ | 136/200 [05:22<02:18, 2.17s/it]\n 68%|██████▊ | 137/200 [05:26<02:42, 2.58s/it]\n 69%|██████▉ | 138/200 [05:26<01:57, 1.89s/it]\n 70%|██████▉ | 139/200 [05:29<02:23, 2.35s/it]\n 70%|███████ | 140/200 [05:30<01:43, 1.73s/it]\n 70%|███████ | 141/200 [05:33<02:13, 2.26s/it]\n 71%|███████ | 142/200 [05:33<01:36, 1.67s/it]\n 72%|███████▏ | 143/200 [05:34<01:11, 1.26s/it]\n 72%|███████▏ | 144/200 [05:37<01:46, 1.91s/it]\n 72%|███████▎ | 145/200 [05:37<01:17, 1.41s/it]\n 73%|███████▎ | 146/200 [05:41<01:49, 2.04s/it]\n 74%|███████▎ | 147/200 [05:44<02:10, 2.45s/it]\n 74%|███████▍ | 148/200 [05:48<02:23, 2.75s/it]\n 74%|███████▍ | 149/200 [05:48<01:42, 2.02s/it]\n 75%|███████▌ | 150/200 [05:52<02:03, 2.46s/it]\n 76%|███████▌ | 151/200 [05:55<02:16, 2.79s/it]\n 76%|███████▌ | 152/200 [05:59<02:23, 3.00s/it]\n 76%|███████▋ | 153/200 [06:02<02:26, 3.12s/it]\n 77%|███████▋ | 154/200 [06:02<01:42, 2.22s/it]\n 78%|███████▊ | 155/200 [06:03<01:14, 1.65s/it]\n 78%|███████▊ | 156/200 [06:06<01:38, 2.23s/it]\n 78%|███████▊ | 157/200 [06:06<01:10, 1.64s/it]\n 79%|███████▉ | 158/200 [06:10<01:32, 2.20s/it]\n 80%|███████▉ | 159/200 [06:13<01:45, 2.57s/it]\n 80%|████████ | 160/200 [06:17<01:55, 2.89s/it]\n 80%|████████ | 161/200 [06:20<01:58, 3.04s/it]\n 81%|████████ | 162/200 [06:24<01:59, 3.15s/it]\n 82%|████████▏ | 163/200 [06:24<01:23, 2.24s/it]\n 82%|████████▏ | 164/200 [06:28<01:37, 2.70s/it]\n 82%|████████▎ | 165/200 [06:28<01:07, 1.93s/it]\n 83%|████████▎ | 166/200 [06:28<00:48, 1.43s/it]\n 84%|████████▎ | 167/200 [06:28<00:35, 1.09s/it]\n 84%|████████▍ | 168/200 [06:29<00:27, 1.17it/s]\n 84%|████████▍ | 169/200 [06:29<00:21, 1.45it/s]\n 85%|████████▌ | 170/200 [06:29<00:17, 1.74it/s]\n 86%|████████▌ | 171/200 [06:30<00:14, 2.02it/s]\n 86%|████████▌ | 172/200 [06:30<00:12, 2.22it/s]\n 86%|████████▋ | 173/200 [06:33<00:37, 1.38s/it]\n 87%|████████▋ | 174/200 [06:37<00:51, 1.99s/it]\n 88%|████████▊ | 175/200 [06:40<01:00, 2.41s/it]\n 88%|████████▊ | 176/200 [06:44<01:06, 2.78s/it]\n 88%|████████▊ | 177/200 [06:47<01:08, 2.98s/it]\n 89%|████████▉ | 178/200 [06:47<00:46, 2.12s/it]\n 90%|████████▉ | 179/200 [06:51<00:54, 2.57s/it]\n 90%|█████████ | 180/200 [06:51<00:37, 1.89s/it]\n 90%|█████████ | 181/200 [06:52<00:26, 1.41s/it]\n 91%|█████████ | 182/200 [06:52<00:19, 1.08s/it]\n 92%|█████████▏| 183/200 [06:52<00:14, 1.19it/s]\n 92%|█████████▏| 184/200 [06:53<00:10, 1.47it/s]\n 92%|█████████▎| 185/200 [06:56<00:23, 1.54s/it]\n 93%|█████████▎| 186/200 [06:56<00:16, 1.17s/it]\n 94%|█████████▎| 187/200 [07:00<00:24, 1.86s/it]\n 94%|█████████▍| 188/200 [07:03<00:28, 2.34s/it]\n 94%|█████████▍| 189/200 [07:04<00:18, 1.68s/it]\n 95%|█████████▌| 190/200 [07:04<00:12, 1.27s/it]\n 96%|█████████▌| 191/200 [07:07<00:17, 1.95s/it]\n 96%|█████████▌| 192/200 [07:08<00:11, 1.46s/it]\n 96%|█████████▋| 193/200 [07:11<00:14, 2.08s/it]\n 97%|█████████▋| 194/200 [07:15<00:15, 2.52s/it]\n 98%|█████████▊| 195/200 [07:15<00:09, 1.81s/it]\n 98%|█████████▊| 196/200 [07:19<00:09, 2.36s/it]\n 98%|█████████▊| 197/200 [07:19<00:05, 1.69s/it]\n 99%|█████████▉| 198/200 [07:22<00:04, 2.21s/it]\n100%|█████████▉| 199/200 [07:22<00:01, 1.63s/it]\n100%|██████████| 200/200 [07:26<00:00, 2.18s/it]\n100%|██████████| 200/200 [07:26<00:00, 2.23s/it]\nTraceback (most recent call last):\n File "/code/chaiverse_profiler_1750788977/profiles.py", line 621, in <module>\n cli()\n File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1157, in __call__\n return self.main(*args, **kwargs)\n File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1078, in main\n rv = self.invoke(ctx)\n File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1688, in invoke\n return _process_result(sub_ctx.command.invoke(sub_ctx))\n File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 1434, in invoke\n return ctx.invoke(self.callback, **ctx.params)\n File "/opt/conda/lib/python3.10/site-packages/click/core.py", line 783, in invoke\n return __callback(*args, **kwargs)\n File "/code/chaiverse_profiler_1750788977/profiles.py", line 112, in profile_batches\n profiles = run_batch_profile_with_auto_batch(target, batches, settings, auto_batch, output)\n File "/code/chaiverse_profiler_1750788977/profiles.py", line 163, in run_batch_profile_with_auto_batch\n profiles = run_batch_profile(target, batches, settings, output)\n File "/code/chaiverse_profiler_1750788977/profiles.py", line 277, in run_batch_profile\n analysis_data.write_jsonlines([batch_profile.to_dict()], path)\n File "/code/inference_analysis/data.py", line 64, in write_jsonlines\n f.write(json.dumps(row) + \'\\n\')\n File "/opt/conda/lib/python3.10/json/__init__.py", line 231, in dumps\n return _default_encoder.encode(obj)\n File "/opt/conda/lib/python3.10/json/encoder.py", line 199, in encode\n chunks = self.iterencode(o, _one_shot=True)\n File "/opt/conda/lib/python3.10/json/encoder.py", line 257, in iterencode\n return _iterencode(o, 0)\n File "/opt/conda/lib/python3.10/json/encoder.py", line 179, in default\n raise TypeError(f\'Object of type {o.__class__.__name__} \'\nTypeError: Object of type ResponseStats is not JSON serializable\ncommand terminated with exit code 1\n, output: waiting for startup of endpoint=\'localhost\' route=\'GPT-J-6B-lit-v2\' namespace=\'tenant-chaiml-guanaco\' reward=False url_format=\'{endpoint}.{namespace}.k.chaiverse.com\'\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (0,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\nRequest failed with: (500, \'{"error":"Exception : could not broadcast input array from shape (2,) into shape (1,)"}\')\nRequest failed with: (500, \'{"error":"Exception : negative dimensions are not allowed"}\')\n### Batch size: 1 ###\n\ntotal requests 200\nduration (s): 446.3295199871063\nerrors 78\nmean length: 1.83\n\nthroughput (request / second): 0.448099422161854\nthroughput (character / second): 0.8200219425561928\naverage request duration (s) 2.2315301764011384\n50%ile request duration (s) 3.4340903759002686\n75%ile request duration (s) 3.5071901679039\n90%ile request duration (s) 3.5845992088317873\n95%ile request duration (s) 3.6238793849945066\n\nmean input tokens 2.0\nmean output tokens 1.0\n\n\n')
run pipeline stage %s
Running pipeline stage MKMLProfilerDeleter
Checking if service chaiml-llama8b-retune7-29658-v1-profiler is running
Tearing down inference service chaiml-llama8b-retune7-29658-v1-profiler
Service chaiml-llama8b-retune7-29658-v1-profiler has been torndown
Pipeline stage MKMLProfilerDeleter completed in 2.24s
Shutdown handler de-registered
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
%s, retrying in %s seconds...
Evaluating %s Family Friendly Score with %s threads
clean up pipeline due to error=DeploymentChecksError('None: None')
Shutdown handler de-registered
Shutdown handler registered
run pipeline %s
run pipeline stage %s
Running pipeline stage OfflineFamilyFriendlyScorer
Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 4188.27s
Shutdown handler de-registered
chaiml-llama8b-retune7-_29658_v1 status is now inactive due to auto deactivation removed underperforming models
chaiml-llama8b-retune7-_29658_v1 status is now torndown due to DeploymentManager action