predict.keras.engine.training.Model: Generate predictions from a Keras model

In keras: R Interface to 'Keras'

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

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(), keras_model_sequential(), multi_gpu_model(), pop_layer(), predict_generator(), predict_on_batch(), predict_proba(), summary.keras.engine.training.Model(), train_on_batch()

keras documentation built on May 29, 2024, 3:20 a.m.