Single gradient update or model evaluation over one batch of samples.
Single gradient update or model evaluation over one batch of samples.
train_on_batch(object, x, y, class_weight = NULL, sample_weight = NULL)
test_on_batch(object, x, y, sample_weight = NULL)Arguments
| 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,
evaluate.keras.engine.training.Model,
evaluate_generator,
fit_generator, fit,
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