forked from kscience/kmath
dependencies fixed
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@ -12,15 +12,14 @@ differentiable program written on top of
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## Installation
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Currently, to build native artifacts, we support only
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To install the library, you can simply publish to the local
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Maven repository:
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```
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./gradlew -q :kmath-noa:publishToMavenLocal
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```
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This will fetch and build native artifacts as well.
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Currently, we support only
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the [GNU](https://gcc.gnu.org/) toolchain. For `GPU` kernels, we require a compatible
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[CUDA](https://docs.nvidia.com/cuda/cuda-installation-guide-linux/index.html)
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installation. If you are on Windows, we recommend setting up
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everything on [WSL](https://docs.nvidia.com/cuda/wsl-user-guide/index.html).
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To install the library, simply publish the modules `kmath-tensors`
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and `kmath-noa` locally:
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```
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./gradlew -q :kmath-tensors:publishToMavenLocal :kmath-noa:publishToMavenLocal
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```
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@ -15,7 +15,7 @@ plugins {
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description = "Wrapper for the Bayesian Computation library NOA on top of LibTorch"
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dependencies {
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api(project(":kmath-tensors"))
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implementation(project(":kmath-tensors"))
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}
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val home: String = System.getProperty("user.home")
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@ -185,8 +185,8 @@ val buildCpp by tasks.registering {
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tasks {
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withType<Test>{
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systemProperty("java.library.path",
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//"$cppBuildDir/kmath"
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"$home/devspace/noa/cmake-build-release/kmath")
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"$cppBuildDir/kmath")
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//"$home/devspace/noa/cmake-build-release/kmath")
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}
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}
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@ -9,7 +9,7 @@ kotlin.sourceSets {
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commonMain {
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dependencies {
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api(project(":kmath-core"))
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api(project(":kmath-stat"))
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implementation(project(":kmath-stat"))
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}
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}
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}
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