simpleml.models.classifiers.keras.model
¶
Uses Keras’s API to create a model classifier
Module Contents¶
Classes¶
Main model class needs to be initialize-able in order to play nice with |
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Wrapper class and callable generator to be used instead of unavailable dependencies |
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class
simpleml.models.classifiers.keras.model.
KerasModelClassifier
(use_training_generator=False, training_generator_params=None, use_validation_generator=False, validation_generator_params=None, use_sequence_object=False, **kwargs)[source]¶ Bases:
simpleml.models.classifiers.keras.base_keras_classifier.KerasClassifier
Main model class needs to be initialize-able in order to play nice with database persistence and loading. This class is the in between that defines the expected methods for each extended library.
Examples: Scikit-learn estimators –> SklearnModel(LibraryModel): … Keras estimators –> KerasModel(LibraryModel): … PyTorch … …
Pass default save method as Keras’s persistence pattern
- Parameters
use_training_generator (Bool) – Whether to propagate use of a generator object when training – does not allow for using a generator in production – only fit_generator
use_validation_generator (Bool) – Whether to ALSO use a generator for validation data while training. Does nothing if use_training_generator is false
training_generator_params – parameters to pass to the generator method for train split - normal fit(_generator) params should be passed as params={}
validation_generator_params – parameters to pass to the generator method for validation split - normal fit(_generator) params should be passed as params={}
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class
simpleml.models.classifiers.keras.model.
WrappedKerasModelClassifier
[source]¶ Bases:
simpleml.imports.Model
,simpleml.models.classifiers.external_models.ClassificationExternalModelMixin
Wrapper class and callable generator to be used instead of unavailable dependencies Errors on reference when not available instead of on import