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)
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. |
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.
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()
Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.