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library(keras)
library(densenet)
input_img <- layer_input(shape = c(28, 28, 1))
model <- application_densenet(input_tensor = input_img, classes = 10L)
model %>% compile(
optimizer = "adam",
loss = "categorical_crossentropy",
metrics = "accuracy"
@dfalbel
dfalbel / run.R
Created March 20, 2017 15:04
parallel_sort
Rcpp::sourceCpp('t.cpp')
x <- runif(1000000)
m <- microbenchmark::microbenchmark(
psort(x),
csort(x),
sort(x)
)
x <- 1000000:1
@dfalbel
dfalbel / README.md
Created December 8, 2015 12:27
fresh block