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Running pipeline stage MKMLizer
Starting job with name jic062-instruct-v19-con-v1-mkmlizer
Waiting for job on jic062-instruct-v19-con-v1-mkmlizer to finish
Failed to get response for submission zonemercy-lexical-nemo-_1518_v26: ('http://zonemercy-lexical-nemo-1518-v26-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
jic062-instruct-v19-con-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
jic062-instruct-v19-con-v1-mkmlizer: ║ _____ __ __ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ / _/ /_ ___ __/ / ___ ___ / / ║
jic062-instruct-v19-con-v1-mkmlizer: ║ / _/ / // / |/|/ / _ \/ -_) -_) / ║
jic062-instruct-v19-con-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ /___/ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ Version: 0.10.1 ║
jic062-instruct-v19-con-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
jic062-instruct-v19-con-v1-mkmlizer: ║ https://mk1.ai ║
jic062-instruct-v19-con-v1-mkmlizer: ║ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ The license key for the current software has been verified as ║
jic062-instruct-v19-con-v1-mkmlizer: ║ belonging to: ║
jic062-instruct-v19-con-v1-mkmlizer: ║ ║
jic062-instruct-v19-con-v1-mkmlizer: ║ Chai Research Corp. ║
jic062-instruct-v19-con-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
jic062-instruct-v19-con-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
jic062-instruct-v19-con-v1-mkmlizer: ║ ║
jic062-instruct-v19-con-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
Failed to get response for submission zonemercy-lexical-nemo-_1518_v26: ('http://zonemercy-lexical-nemo-1518-v26-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-lexical-nemo-_1518_v27: ('http://zonemercy-lexical-nemo-1518-v27-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
jic062-instruct-v19-con-v1-mkmlizer: Downloaded to shared memory in 35.017s
jic062-instruct-v19-con-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpsharzeb8, device:0
jic062-instruct-v19-con-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
Failed to get response for submission zonemercy-lexical-nemo-_1518_v26: ('http://zonemercy-lexical-nemo-1518-v26-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
jic062-instruct-v19-con-v1-mkmlizer: quantized model in 26.702s
jic062-instruct-v19-con-v1-mkmlizer: Processed model jic062/instruct-v19-con in 61.720s
jic062-instruct-v19-con-v1-mkmlizer: creating bucket guanaco-mkml-models
jic062-instruct-v19-con-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
jic062-instruct-v19-con-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/jic062-instruct-v19-con-v1
jic062-instruct-v19-con-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/jic062-instruct-v19-con-v1/config.json
jic062-instruct-v19-con-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/jic062-instruct-v19-con-v1/special_tokens_map.json
jic062-instruct-v19-con-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/jic062-instruct-v19-con-v1/tokenizer_config.json
jic062-instruct-v19-con-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/jic062-instruct-v19-con-v1/tokenizer.json
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jic062-instruct-v19-con-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/jic062-instruct-v19-con-v1/flywheel_model.0.safetensors
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Job jic062-instruct-v19-con-v1-mkmlizer completed after 84.53s with status: succeeded
Stopping job with name jic062-instruct-v19-con-v1-mkmlizer
Pipeline stage MKMLizer completed in 85.90s
run pipeline stage %s
Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.20s
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Running pipeline stage MKMLDeployer
Creating inference service jic062-instruct-v19-con-v1
Waiting for inference service jic062-instruct-v19-con-v1 to be ready
Failed to get response for submission mistralai-mixtral-8x7b_3473_v131: ('http://mistralai-mixtral-8x7b-3473-v131-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:43198->127.0.0.1:8080: read: connection reset by peer\n')
Failed to get response for submission zonemercy-lexical-nemo-_1518_v26: ('http://zonemercy-lexical-nemo-1518-v26-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v8: ('http://zonemercy-base-story-v1-v8-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v8: ('http://zonemercy-base-story-v1-v8-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v8: ('http://zonemercy-base-story-v1-v8-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', 'read tcp 127.0.0.1:53168->127.0.0.1:8080: read: connection reset by peer\n')
Failed to get response for submission zonemercy-lexical-nemo-_1518_v27: ('http://zonemercy-lexical-nemo-1518-v27-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Failed to get response for submission zonemercy-base-story-v1_v8: ('http://zonemercy-base-story-v1-v8-predictor.tenant-chaiml-guanaco.k.chaiverse.com/v1/models/GPT-J-6B-lit-v2:predict', '{"error":"ValueError : [TypeError(\\"\'numpy.int64\' object is not iterable\\"), TypeError(\'vars() argument must have __dict__ attribute\')]"}')
Inference service jic062-instruct-v19-con-v1 ready after 150.52442502975464s
Pipeline stage MKMLDeployer completed in 151.01s
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Received healthy response to inference request in 2.374983787536621s
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Received healthy response to inference request in 1.5469419956207275s
Received healthy response to inference request in 1.4963862895965576s
Received healthy response to inference request in 2.51005220413208s
Received healthy response to inference request in 1.819288730621338s
5 requests
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5th percentile: 1.5064974308013916
10th percentile: 1.5166085720062257
20th percentile: 1.5368308544158935
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mean time: 1.9495306015014648
Pipeline stage StressChecker completed in 10.53s
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Inference service jic062-instruct-v19-con-v1-profiler ready after 150.39093136787415s
Pipeline stage MKMLProfilerDeployer completed in 150.95s
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kubectl cp /code/guanaco/guanaco_inference_services/src/inference_scripts tenant-chaiml-guanaco/jic062-instruct-v19-con-v1-profiler-predictor-00001-deployzfzcs:/code/chaiverse_profiler_1725639487 --namespace tenant-chaiml-guanaco
kubectl exec -it jic062-instruct-v19-con-v1-profiler-predictor-00001-deployzfzcs --namespace tenant-chaiml-guanaco -- sh -c 'cd /code/chaiverse_profiler_1725639487 && python profiles.py profile --best_of_n 16 --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 64 --summary /code/chaiverse_profiler_1725639487/summary.json'
kubectl exec -it jic062-instruct-v19-con-v1-profiler-predictor-00001-deployzfzcs --namespace tenant-chaiml-guanaco -- bash -c 'cat /code/chaiverse_profiler_1725639487/summary.json'
Pipeline stage MKMLProfilerRunner completed in 804.47s
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