Metadata-Version: 2.1
Name: model-wrapper
Version: 0.4.8
Summary: Model wrapper for Pytorch, which can training, predict, evaluate, etc.
Home-page: https://gitee.com/summry/model-wrapper
Author: summy
Author-email: fkfkfk2024@2925.com
License: UNKNOWN
Keywords: Pytorch,Training,AI,Machine learning,Deep learning,torch
Platform: UNKNOWN
Requires-Python: >=3.6
Description-Content-Type: text/markdown

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))


