predict.keras.engine.training.Model
Generate predictions from a Keras model
Description
Generates output predictions for the input samples, processing the samples in a batched way.
Usage
## S3 method for class 'keras.engine.training.Model'
predict(
object,
x,
batch_size = NULL,
verbose = "auto",
steps = NULL,
callbacks = NULL,
...
) Arguments
| Arguments | Description |
|---|---|
| object | Keras model |
| x | Input data (vector, matrix, or array). You can also pass a tfdataset or a generator returning a list with (inputs, targets) or (inputs, targets, sample_weights). |
| batch_size | Integer. If unspecified, it will default to 32. |
| verbose | Verbosity mode, 0, 1, 2, or “auto”. “auto” defaults to 1 for for most cases and defaults to verbose=2 when used with ParameterServerStrategy or with interactive logging disabled. |
| steps | Total number of steps (batches of samples) before declaring the evaluation round finished. Ignored with the default value of NULL. |
| callbacks | List of callbacks to apply during prediction. |
| … | Unused |
Value
vector, matrix, or array of predictions
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_generator(), predict_on_batch(), predict_proba(), summary.keras.engine.training.Model(), train_on_batch()