{"library":"ml-goodput-measurement","type":"library","category":null,"description":"ML Goodput Measurement (ml-goodput-measurement) is a Python library designed to monitor and analyze the efficiency of Machine Learning (ML) workloads. It tracks metrics such as Goodput, Badput, and step time deviation, integrating with Google Cloud Logging, Google Cloud Monitoring, and TensorBoard for data storage, visualization, and alerting. The library is actively maintained, with minor version releases occurring roughly monthly or bi-monthly, and is currently at version 0.0.16.","language":"python","status":"active","version":"0.0.16","tags":["ml","monitoring","goodput","badput","google-cloud","performance","tpu"],"install":[{"cmd":"pip install ml-goodput-measurement","imports":["from ml_goodput_measurement.goodput import GoodputMonitor"]}],"homepage":null,"github":"https://github.com/AI-Hypercomputer/ml-goodput-measurement","docs":null,"changelog":null,"pypi":"https://pypi.org/project/ml-goodput-measurement/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":12.4,"avg_import_s":null,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/ml-goodput-measurement/compatibility"},"provenance":{"verified_status":"import_fail","verified_at":"Fri Jul 03","last_verified":"Fri Jul 03","next_check":"Fri Jul 10","install_tag":null}}