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()