Callback that streams epoch results to a csv file.
Supports all values that can be represented as a string, including 1D iterables such as np.ndarray.
CSVLogger(filename, separator = ",", append = FALSE)
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, |
Taylor B. Arnold, taylor.arnold@acm.org
Chollet, Francois. 2015. Keras: Deep Learning library for Theano and TensorFlow.
Other callbacks: EarlyStopping,
ModelCheckpoint,
ReduceLROnPlateau,
TensorBoard
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)
}Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.