R/model.R

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()