Keras Model
A model is a directed acyclic graph of layers.
keras_model(inputs, outputs = NULL)Arguments
| inputs | Input layer |
| outputs | Output layer |
See also
Other model functions: compile,
evaluate.keras.engine.training.Model,
evaluate_generator,
fit_generator, fit,
get_config, get_layer,
keras_model_sequential,
multi_gpu_model, pop_layer,
predict.keras.engine.training.Model,
predict_generator,
predict_on_batch,
predict_proba,
summary.keras.engine.training.Model,
train_on_batch
Examples
# NOT RUN {
library(keras)
# input layer
inputs <- layer_input(shape = c(784))
# outputs compose input + dense layers
predictions <- inputs %>%
layer_dense(units = 64, activation = 'relu') %>%
layer_dense(units = 64, activation = 'relu') %>%
layer_dense(units = 10, activation = 'softmax')
# create and compile model
model <- keras_model(inputs = inputs, outputs = predictions)
model %>% compile(
optimizer = 'rmsprop',
loss = 'categorical_crossentropy',
metrics = c('accuracy')
)
# }