train_on_batch
Single gradient update or model evaluation over one batch of samples.
Description
Single gradient update or model evaluation over one batch of samples.
Usage
train_on_batch(object, x, y, class_weight = NULL, sample_weight = NULL)
test_on_batch(object, x, y, sample_weight = NULL) Arguments
| Arguments | Description |
|---|---|
| object | Keras model object |
| x | input data, as an array or list of arrays (if the model has multiple inputs). |
| y | labels, as an array. |
| class_weight | named list mapping classes to a weight value, used for scaling the loss function (during training only). |
| sample_weight | sample weights, as an array. |
Value
Scalar training or test loss (if the model has no metrics) or list of scalars (if the model computes other metrics). The property model$metrics_names will give you the display labels for the scalar outputs.
See Also
Other model functions: compile.keras.engine.training.Model(), evaluate.keras.engine.training.Model(), evaluate_generator(), fit.keras.engine.training.Model(), fit_generator(), get_config(), get_layer(), keras_model_sequential(), keras_model(), multi_gpu_model(), pop_layer(), predict.keras.engine.training.Model(), predict_generator(), predict_on_batch(), predict_proba(), summary.keras.engine.training.Model()