keras (version 2.13.0)

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)

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.

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.

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()