initial commit for noa module

This commit is contained in:
Roland Grinis 2021-06-25 22:36:01 +01:00
parent 839b1f2a82
commit adfb541fff
3 changed files with 95 additions and 0 deletions

14
kmath-noa/README.md Normal file
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# Module kmath-noa
This module provides a `kotlin-jvm` frontend for the
[NOA](https://github.com/grinisrit/noa.git)
library together with relevant functionality from
[LibTorch](https://pytorch.org/cppdocs).
Our aim is to create a Bayesian computational platform
which covers a wide set of applications from particle physics
simulations to deep learning and general differentiable programs
written on top of `AutoGrad` & `ATen`.
Currently, the native artifacts support only `GNU` and
`CUDA` for GPU acceleration.

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/*
* Copyright 2018-2021 KMath contributors.
* Use of this source code is governed by the Apache 2.0 license that can be found in the license/LICENSE.txt file.
*/
import de.undercouch.gradle.tasks.download.Download
plugins {
kotlin("jvm")
id("ru.mipt.npm.gradle.common")
id("de.undercouch.download")
}
description = "Wrapper for the Bayesian Computation library NOA on top of LibTorch"
dependencies {
api(project(":kmath-tensors"))
}
val home = System.getProperty("user.home")
val javaHome = System.getProperty("java.home")
val thirdPartyDir = "$home/.konan/third-party/kmath-noa-${project.property("version")}"
val cppBuildDir = "$thirdPartyDir/cpp-build"
val cppSources = projectDir.resolve("src/main/cpp")
val cudaHome: String? = System.getenv("CUDA_HOME")
val cudaDefault = file("/usr/local/cuda").exists()
val cudaFound = cudaHome?.isNotEmpty() ?: false or cudaDefault
val cmakeArchive = "cmake-3.20.5-Linux-x86_64"
val torchArchive = "libtorch"
val cmakeCmd = "$thirdPartyDir/$cmakeArchive/bin/cmake"
val ninjaCmd = "$thirdPartyDir/ninja"
val downloadCMake by tasks.registering(Download::class) {
val tarFile = "$cmakeArchive.tar.gz"
src("https://github.com/Kitware/CMake/releases/download/v3.20.5/$tarFile")
dest(File(thirdPartyDir, tarFile))
overwrite(false)
}
val downloadNinja by tasks.registering(Download::class) {
src("https://github.com/ninja-build/ninja/releases/download/v1.10.2/ninja-linux.zip")
dest(File(thirdPartyDir, "ninja-linux.zip"))
overwrite(false)
}
val downloadTorch by tasks.registering(Download::class) {
val torchVersion = "$torchArchive-shared-with-deps-1.9.0%2B"
val cudaUrl = "https://download.pytorch.org/libtorch/cu111/${torchVersion}cu111.zip"
val cpuUrl = "https://download.pytorch.org/libtorch/cpu/${torchVersion}cpu.zip"
val url = if (cudaFound) cudaUrl else cpuUrl
src(url)
dest(File(thirdPartyDir, "$torchArchive.zip"))
overwrite(false)
}
val extractCMake by tasks.registering(Copy::class) {
dependsOn(downloadCMake)
from(tarTree(resources.gzip(downloadCMake.get().dest)))
into(thirdPartyDir)
}
val extractNinja by tasks.registering(Copy::class) {
dependsOn(downloadNinja)
from(zipTree(downloadNinja.get().dest))
into(thirdPartyDir)
}
val extractTorch by tasks.registering(Copy::class) {
dependsOn(downloadTorch)
from(zipTree(downloadTorch.get().dest))
into(thirdPartyDir)
}

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@ -47,3 +47,8 @@ include(
":examples",
":benchmarks"
)
if(System.getProperty("os.name") == "Linux"){
include(":kmath-noa")
}