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object NMF { | |
def supervised(W: CuMatrix[Float], X: CuMatrix[Float], iters: Int = 200, eps: Float = 1E-6f) = { | |
require(W.rows == X.rows) | |
import W.blas | |
val n = X.rows | |
val m = X.cols | |
val r = W.cols | |
var H = CuMatrix.ones[Float](r, m) | |
val Wones = W.t * CuMatrix.ones[Float](n, 1) * CuMatrix.ones[Float](1, m) | |
for(i <- 0 until iters) { | |
println(i) | |
H = H :*= (W.t * (X :/ (W * H))) :/= Wones | |
max.inPlace(H, eps) | |
System.gc() | |
} | |
H | |
} | |
def main(args: Array[String]) { | |
import jcuda.jcublas._ | |
implicit val handle = new cublasHandle | |
JCublas2.cublasCreate(handle) | |
val in = System.currentTimeMillis() | |
val W = CuMatrix.ones[Float](1024, 108) | |
val H = CuMatrix.ones[Float](108, 10000) | |
val X = W * H | |
val Hhat = supervised(W, X) | |
val Xhat = W * Hhat | |
val out = System.currentTimeMillis() | |
println(max(abs(Xhat.toDense - X.toDense))) | |
println(s"${(out - in)/1000.0} seconds") | |
} | |
} |
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