Skip to main content

Model wrapper for Pytorch, which can training, predict, evaluate, etc.

Project description

Usage Sample ''''''''''''

.. code:: python

    from model_wrapper import SplitClassifyModelWrapper

    classes = ['class1', 'class2', 'class3'...]
    X = [[...], [...],]
    y = [0, 0, 1, 2, 1...]

    model = ...
    wrapper = SplitClassifyModelWrapper(model, classes=classes)
    wrapper.train(X, y, val_size=0.2)

    X_test = [[...], [...],]
    y_test = [0, 1, 1, 2, 1...]
    result = wrapper.evaluate(X_test, y_test)
    # 0.953125

    result = wrapper.predict(X_test)
    # [0, 1]

    result = wrapper.predict_classes(X_test)
    # ['class1', 'class2']

    result = wrapper.predict_proba(X_test)
    # ([0, 1], array([0.99439645, 0.99190724], dtype=float32))

    result = wrapper.predict_classes_proba(X_test)
    # (['class1', 'class2'], array([0.99439645, 0.99190724], dtype=float32))

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

model-wrapper-0.4.5.tar.gz (16.1 kB view details)

Uploaded Source

File details

Details for the file model-wrapper-0.4.5.tar.gz.

File metadata

  • Download URL: model-wrapper-0.4.5.tar.gz
  • Upload date:
  • Size: 16.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/5.0.0 CPython/3.9.18

File hashes

Hashes for model-wrapper-0.4.5.tar.gz
Algorithm Hash digest
SHA256 a521534813004645e6e5fd4c320780db5ea3447dba1a75817173283e5219206f
MD5 edfc5924b54a29e9a2d94ac92281c477
BLAKE2b-256 1605ea9017c5aad203e21e6e37d63730a3a1caa411c968c6c02626b8fb5a9d67

See more details on using hashes here.

Supported by

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