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Running pipeline stage MKMLizer
Starting job with name leosheng-no-repeat-write-v1-mkmlizer
Waiting for job on leosheng-no-repeat-write-v1-mkmlizer to finish
leosheng-no-repeat-write-v1-mkmlizer: Downloaded to shared memory in 32.236s
leosheng-no-repeat-write-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp47vep5f4, device:0
leosheng-no-repeat-write-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
leosheng-no-repeat-write-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.
leosheng-no-repeat-write-v1-mkmlizer: tensors = torch.load(model_shard_filename, map_location=torch.device(self.device), mmap=True)
leosheng-no-repeat-write-v1-mkmlizer: quantized model in 27.481s
leosheng-no-repeat-write-v1-mkmlizer: Processed model leosheng/no-repeat-write in 59.717s
leosheng-no-repeat-write-v1-mkmlizer: creating bucket guanaco-mkml-models
leosheng-no-repeat-write-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
leosheng-no-repeat-write-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/leosheng-no-repeat-write-v1
leosheng-no-repeat-write-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/leosheng-no-repeat-write-v1/config.json
leosheng-no-repeat-write-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/leosheng-no-repeat-write-v1/special_tokens_map.json
leosheng-no-repeat-write-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/leosheng-no-repeat-write-v1/tokenizer_config.json
leosheng-no-repeat-write-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/leosheng-no-repeat-write-v1/tokenizer.json
leosheng-no-repeat-write-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/leosheng-no-repeat-write-v1/flywheel_model.0.safetensors
leosheng-no-repeat-write-v1-mkmlizer:
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Job leosheng-no-repeat-write-v1-mkmlizer completed after 93.31s with status: succeeded
Stopping job with name leosheng-no-repeat-write-v1-mkmlizer
Pipeline stage MKMLizer completed in 93.77s
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Pipeline stage MKMLTemplater completed in 0.15s
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Running pipeline stage MKMLDeployer
Creating inference service leosheng-no-repeat-write-v1
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Inference service leosheng-no-repeat-write-v1 ready after 150.6889202594757s
Pipeline stage MKMLDeployer completed in 151.27s
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Running pipeline stage StressChecker
Received healthy response to inference request in 1.5347225666046143s
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Received healthy response to inference request in 1.7071928977966309s
Received healthy response to inference request in 1.5518643856048584s
Received healthy response to inference request in 2.197922706604004s
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mean time: 1.7407540798187255
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