Skip to main content

Opinionated machine learning organization and configuration

Project description

microcosm-sagemaker

Opinionated machine learning with SageMaker

Usage

For best practices, see cookiecutter-microcosm-sagemaker.

Profiling

Make sure pyinstrument is installed, either using pip install pyinstrument or by installing microcosm-sagemaker with profiling extra dependencies:

pip install -e '.[profiling]'

To enable profiling of the app, use the --profile flag with runserver:

runserver --profile

The service will log that it is in profiling mode and announce the directory to which it is exporting. Each call to the endpoint will be profiled and its results with be stored in a time-tagged html file in the profiling directory.

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

microcosm-sagemaker-0.5.0.tar.gz (21.4 kB view details)

Uploaded Source

File details

Details for the file microcosm-sagemaker-0.5.0.tar.gz.

File metadata

  • Download URL: microcosm-sagemaker-0.5.0.tar.gz
  • Upload date:
  • Size: 21.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/41.0.1 requests-toolbelt/0.8.0 tqdm/4.32.1 CPython/3.7.3

File hashes

Hashes for microcosm-sagemaker-0.5.0.tar.gz
Algorithm Hash digest
SHA256 b784d0d824f2dfb5d141f231720d172e42ec93c56ae3649eefcb5efbade0d701
MD5 68bc525f053c0780b454b354d99a6fb4
BLAKE2b-256 b8577f9bb33062e9f5dfb93c702d6ce367f2142c5d06b0f0a08a5a97315bc5fc

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page