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# netReg: graph-regularized linear regression models.
#
# Copyright (C) 2015 - 2019 Simon Dirmeier
#
# This file is part of netReg.
#
# netReg is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# netReg is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with netReg. If not, see <http://www.gnu.org/licenses/>.
#' @noRd
#' @import tensorflow
fit <- function(objective, alpha, beta,
maxit = 1000, learning.rate = 0.01, thresh = 1e-4) {
optimizer <- adam(learning.rate)
train <- optimizer$minimize(objective)
with(session() %as% sess, {
sess$run(init_variables())
target.old <- Inf
for (step in seq(maxit))
{
sess$run(train)
if (step %% 25 == 0) {
target <- sess$run(objective)
if (sum(abs(target - target.old)) < thresh) {
break
}
target.old <- target
}
}
alpha <- sess$run(alpha)
beta <- sess$run(beta)
})
list(beta = beta, alpha = alpha)
}
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