CSVLogger: Callback that streams epoch results to a csv file.

In kerasR: R Interface to the Keras Deep Learning Library

Callback that streams epoch results to a csv file.

Description

Supports all values that can be represented as a string, including 1D iterables such as np.ndarray.

Usage

CSVLogger(filename, separator = ",", append = FALSE)

Arguments

filename	filename of the csv file, e.g. 'run/log.csv'.
separator	string used to separate elements in the csv file.
append	True: append if file exists (useful for continuing training). False: overwrite existing file,

Author(s)

Taylor B. Arnold, [e-mail]

References

Chollet, Francois. 2015. Keras: Deep Learning library for Theano and TensorFlow.

See Also

Other callbacks: EarlyStopping, ModelCheckpoint, ReduceLROnPlateau, TensorBoard

Examples

if(keras_available()) {
  X_train <- matrix(rnorm(100 * 10), nrow = 100)
  Y_train <- to_categorical(matrix(sample(0:2, 100, TRUE), ncol = 1), 3)

  mod <- Sequential()
  mod$add(Dense(units = 50, input_shape = dim(X_train)[2]))
  mod$add(Activation("relu"))
  mod$add(Dense(units = 3))
  mod$add(Activation("softmax"))
  keras_compile(mod,  loss = 'categorical_crossentropy', optimizer = RMSprop())

  callbacks <- list(CSVLogger(tempfile()),
                    EarlyStopping(),
                    ReduceLROnPlateau(),
                    TensorBoard(tempfile()))

  keras_fit(mod, X_train, Y_train, batch_size = 32, epochs = 5,
            verbose = 0, callbacks = callbacks, validation_split = 0.2)
}

kerasR documentation built on Aug. 17, 2022, 5:06 p.m.