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Valgrind might report some memory still reachable.

This is known. See tensorflow/tensorflow#17739 for detail.

Resources like thread-pool and memory allocator are shared between sessions. Shutting down the session would not shut down shared resources because those resources may be reused for future sessions. I guess you want an API to shut down memory allocator/thread-pool, which doesn't exist AFAIK

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#include <stdio.h>
#include <errno.h>
#include <glob.h>

char *myname;

/* globerr --- print error message for glob() */

int globerr(const char *path, int eerrno)
{

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// gcc -msse3 -O3 sse_4x4.c -l cblas

#include <stdio.h>
#include <stdlib.h>
#include <time.h>
#include <math.h>

#include <mmintrin.h>
#include <xmmintrin.h>

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// gcc -msse3 -O3 sse_2x2.c -l cblas

#include <mmintrin.h>
#include <xmmintrin.h>
#include <pmmintrin.h>
#include <emmintrin.h>

#include <stdio.h>
#include <stdlib.h>

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#include <iostream>
#include <cuda.h>
#include <curand.h>
#include <curand_kernel.h>

using namespace std;

int main() {
    curandGenerator_t genGPU;
    curandCreateGenerator(&genGPU, CURAND_RNG_PSEUDO_MTGP32);

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library(devtools)
library(miniCRAN)
options(repos=c(CRAN="https://cran.rstudio.com"))

pkg <- devtools:::load_pkg_description(".", create = NA)
parsed <- lapply(pkg, devtools:::parse_deps)
tags <- c(parsed$imports$name, parsed$depends$name)

mx_deps <- miniCRAN:::pkgDep(tags, suggests = FALSE, enhances = FALSE)
write.table(

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library(devtools)

pkg <- devtools:::load_pkg_description(".", create = NA)

parsed <- lapply(pkg, parse_deps)

tags <- c(parsed$imports$name, parsed$depends$name)

library(miniCRAN)

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MXNet R installation with GPU support on Windows

Clone the MXNet github repo

git clone --recursive https://github.com/dmlc/mxnet

The --recursive is to clone all the submodules used by MXNet.

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//java -Djava.awt.headless=true

import java.awt.image.BufferedImage;
import java.awt.image.DataBufferByte;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;

public class Main {

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logger <- mx.metric.logger$new()

mx.callback.plot.train.metric <- function(period, logger=NULL) {
  function(iteration, nbatch, env, verbose=TRUE) {
    if (nbatch %% period == 0 && !is.null(env$metric)) {
      N = env$end.round
      result <- env$metric$get(env$train.metric)
      plot(c(0.5,1)~c(0,N), col=NA, ylab = paste0("Train-", result$name),xlab = "")
      logger$train <- c(logger$train, result$value)
      lines(logger$train, lwd = 3, col="red")