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Running pipeline stage MKMLizer
Starting job with name cycy233-nemo-p-v4-c3-v1-mkmlizer
Waiting for job on cycy233-nemo-p-v4-c3-v1-mkmlizer to finish
cycy233-nemo-p-v4-c3-v1-mkmlizer: ╔═════════════════════════════════════════════════════════════════════╗
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ _____ __ __ ║
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cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ /_//_/\_, /|__,__/_//_/\__/\__/_/ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ /___/ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ Version: 0.11.12 ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ Copyright 2023 MK ONE TECHNOLOGIES Inc. ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ https://mk1.ai ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ The license key for the current software has been verified as ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ belonging to: ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ Chai Research Corp. ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ Expiration: 2024-10-15 23:59:59 ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ║ ║
cycy233-nemo-p-v4-c3-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
cycy233-nemo-p-v4-c3-v1-mkmlizer: Downloaded to shared memory in 47.525s
cycy233-nemo-p-v4-c3-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmpthq981zm, device:0
cycy233-nemo-p-v4-c3-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
cycy233-nemo-p-v4-c3-v1-mkmlizer: /opt/conda/lib/python3.10/site-packages/mk1/flywheel/functional/loader.py:55: FutureWarning: You are using `torch.load` with `weights_only=False` (the current default value), which uses the default pickle module implicitly. It is possible to construct malicious pickle data which will execute arbitrary code during unpickling (See https://github.com/pytorch/pytorch/blob/main/SECURITY.md#untrusted-models for more details). In a future release, the default value for `weights_only` will be flipped to `True`. This limits the functions that could be executed during unpickling. Arbitrary objects will no longer be allowed to be loaded via this mode unless they are explicitly allowlisted by the user via `torch.serialization.add_safe_globals`. We recommend you start setting `weights_only=True` for any use case where you don't have full control of the loaded file. Please open an issue on GitHub for any issues related to this experimental feature.
cycy233-nemo-p-v4-c3-v1-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
cycy233-nemo-p-v4-c3-v1-mkmlizer: quantized model in 36.732s
cycy233-nemo-p-v4-c3-v1-mkmlizer: Processed model cycy233/nemo-p-v4-c3 in 84.258s
cycy233-nemo-p-v4-c3-v1-mkmlizer: creating bucket guanaco-mkml-models
cycy233-nemo-p-v4-c3-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
cycy233-nemo-p-v4-c3-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1
cycy233-nemo-p-v4-c3-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1/config.json
cycy233-nemo-p-v4-c3-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1/special_tokens_map.json
cycy233-nemo-p-v4-c3-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1/tokenizer_config.json
cycy233-nemo-p-v4-c3-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1/tokenizer.json
cycy233-nemo-p-v4-c3-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/cycy233-nemo-p-v4-c3-v1/flywheel_model.0.safetensors
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Job cycy233-nemo-p-v4-c3-v1-mkmlizer completed after 143.1s with status: succeeded
Stopping job with name cycy233-nemo-p-v4-c3-v1-mkmlizer
Pipeline stage MKMLizer completed in 143.36s
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Creating inference service cycy233-nemo-p-v4-c3-v1
Waiting for inference service cycy233-nemo-p-v4-c3-v1 to be ready
Inference service cycy233-nemo-p-v4-c3-v1 ready after 230.50827884674072s
Pipeline stage MKMLDeployer completed in 230.75s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.4062366485595703s
Received healthy response to inference request in 1.933955192565918s
Received healthy response to inference request in 2.052368640899658s
Received healthy response to inference request in 1.8804190158843994s
Received healthy response to inference request in 2.0782713890075684s
5 requests
0 failed requests
5th percentile: 1.8911262512207032
10th percentile: 1.9018334865570068
20th percentile: 1.9232479572296142
30th percentile: 1.957637882232666
40th percentile: 2.005003261566162
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70th percentile: 2.073090839385986
80th percentile: 2.143864440917969
90th percentile: 2.2750505447387694
95th percentile: 2.3406435966491697
99th percentile: 2.3931180381774904
mean time: 2.0702501773834228
Pipeline stage StressChecker completed in 10.93s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 2.05s
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cycy233-nemo-p-v4-c3_v1 status is now deployed due to DeploymentManager action
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cycy233-nemo-p-v4-c3_v1 status is now inactive due to auto deactivation removed underperforming models