Nothing
library(gpuR)
context("CPU gpuMatrix Row and Column Methods")
# set option to use CPU instead of GPU
options(gpuR.default.device.type = "cpu")
# set seed
set.seed(123)
ORDER_X <- 4
ORDER_Y <- 5
# Base R objects
A <- matrix(rnorm(ORDER_X*ORDER_Y), nrow=ORDER_X, ncol=ORDER_Y)
B <- matrix(rnorm(ORDER_X*ORDER_Y), nrow=ORDER_X, ncol=ORDER_Y)
R <- rowSums(A)
C <- colSums(A)
RM <- rowMeans(A)
CM <- colMeans(A)
test_that("CPU gpuMatrix Single Precision Column Sums",
{
has_cpu_skip()
fgpuX <- gpuMatrix(A, type="float")
gpuC <- colSums(fgpuX)
expect_is(gpuC, "fgpuVector")
expect_equal(gpuC[], C, tolerance=1e-06,
info="float colSums not equivalent")
})
test_that("CPU gpuMatrix Double Precision Column Sums",
{
has_cpu_skip()
dgpuX <- gpuMatrix(A, type="double")
gpuC <- colSums(dgpuX)
expect_is(gpuC, "dgpuVector")
expect_equal(gpuC[], C, tolerance=.Machine$double.eps ^ 0.5,
info="double colSums not equivalent")
})
test_that("CPU gpuMatrix Single Precision Row Sums",
{
has_cpu_skip()
fgpuX <- gpuMatrix(A, type="float")
gpuC <- rowSums(fgpuX)
expect_is(gpuC, "fgpuVector")
expect_equal(gpuC[], R, tolerance=1e-06,
info="float rowSums not equivalent")
})
test_that("CPU gpuMatrix Double Precision Row Sums",
{
has_cpu_skip()
dgpuX <- gpuMatrix(A, type="double")
gpuC <- rowSums(dgpuX)
expect_is(gpuC, "dgpuVector")
expect_equal(gpuC[], R, tolerance=.Machine$double.eps ^ 0.5,
info="double colSums not equivalent")
})
test_that("CPU gpuMatrix Single Precision Column Means",
{
has_cpu_skip()
fgpuX <- gpuMatrix(A, type="float")
gpuC <- colMeans(fgpuX)
expect_is(gpuC, "fgpuVector")
expect_equal(gpuC[], CM, tolerance=1e-06,
info="float colMeans not equivalent")
})
test_that("CPU gpuMatrix Double Precision Column Means",
{
has_cpu_skip()
dgpuX <- gpuMatrix(A, type="double")
gpuC <- colMeans(dgpuX)
expect_is(gpuC, "dgpuVector")
expect_equal(gpuC[], CM, tolerance=.Machine$double.eps ^ 0.5,
info="double colMeans not equivalent")
})
test_that("CPU gpuMatrix Single Precision Row Means",
{
has_cpu_skip()
fgpuX <- gpuMatrix(A, type="float")
gpuC <- rowMeans(fgpuX)
expect_is(gpuC, "fgpuVector")
expect_equal(gpuC[], RM, tolerance=1e-06,
info="float rowMeans not equivalent")
})
test_that("CPU gpuMatrix Double Precision Row Means",
{
has_cpu_skip()
dgpuX <- gpuMatrix(A, type="double")
gpuC <- rowMeans(dgpuX)
expect_is(gpuC, "dgpuVector")
expect_equal(gpuC[], RM, tolerance=.Machine$double.eps ^ 0.5,
info="double rowMeans not equivalent")
})
#cbind/rbind tests
test_that("CPU gpuMatrix Single Precision cbind",
{
has_cpu_skip()
C_bind <- cbind(A, B)
C_scalar <- cbind(1, A)
C_scalar2 <- cbind(A,1)
gpuA <- gpuMatrix(A, type="float")
gpuB <- gpuMatrix(B, type="float")
gpuC <- cbind(gpuA, gpuB)
expect_is(gpuC, "fgpuMatrix")
expect_equal(gpuC[], C_bind, tolerance=1e-06,
info="float cbind not equivalent")
gpu_scalar <- cbind(1, gpuA)
gpu_scalar2 <- cbind(gpuA, 1)
expect_equal(gpu_scalar[], C_scalar, tolerance=1e-06,
info="float scalar cbind not equivalent")
expect_equal(gpu_scalar2[], C_scalar2, tolerance=1e-06,
info="float scalar cbind not equivalent")
})
test_that("CPU gpuMatrix Double Precision cbind",
{
has_cpu_skip()
C_bind <- cbind(A, B)
C_scalar <- cbind(1, A)
C_scalar2 <- cbind(A,1)
gpuA <- gpuMatrix(A, type="double")
gpuB <- gpuMatrix(B, type="double")
gpuC <- cbind(gpuA, gpuB)
expect_is(gpuC, "dgpuMatrix")
expect_equal(gpuC[], C_bind, tolerance=.Machine$double.eps^0.5,
info="double cbind not equivalent")
gpu_scalar <- cbind(1, gpuA)
gpu_scalar2 <- cbind(gpuA, 1)
expect_equal(gpu_scalar[], C_scalar, tolerance=.Machine$double.eps^0.5,
info="double scalar cbind not equivalent")
expect_equal(gpu_scalar2[], C_scalar2, tolerance=.Machine$double.eps^0.5,
info="double scalar cbind not equivalent")
})
test_that("CPU gpuMatrix Single Precision rbind",
{
has_cpu_skip()
C_bind <- rbind(A, B)
C_scalar <- rbind(1, A)
C_scalar2 <- rbind(A,1)
gpuA <- gpuMatrix(A, type="float")
gpuB <- gpuMatrix(B, type="float")
gpuC <- rbind(gpuA, gpuB)
expect_is(gpuC, "fgpuMatrix")
expect_equal(gpuC[], C_bind, tolerance=1e-06,
info="float rbind not equivalent")
gpu_scalar <- rbind(1, gpuA)
gpu_scalar2 <- rbind(gpuA, 1)
expect_equal(gpu_scalar[], C_scalar, tolerance=1e-06,
info="float scalar rbind not equivalent")
expect_equal(gpu_scalar2[], C_scalar2, tolerance=1e-06,
info="float scalar rbind not equivalent")
})
test_that("CPU gpuMatrix Double Precision rbind",
{
has_cpu_skip()
C_bind <- rbind(A, B)
C_scalar <- rbind(1, A)
C_scalar2 <- rbind(A,1)
gpuA <- gpuMatrix(A, type="double")
gpuB <- gpuMatrix(B, type="double")
gpuC <- rbind(gpuA, gpuB)
expect_is(gpuC, "dgpuMatrix")
expect_equal(gpuC[], C_bind, tolerance=.Machine$double.eps^0.5,
info="double rbind not equivalent")
gpu_scalar <- rbind(1, gpuA)
gpu_scalar2 <- rbind(gpuA, 1)
expect_equal(gpu_scalar[], C_scalar, tolerance=.Machine$double.eps^0.5,
info="double scalar rbind not equivalent")
expect_equal(gpu_scalar2[], C_scalar2, tolerance=.Machine$double.eps^0.5,
info="double scalar rbind not equivalent")
})
options(gpuR.default.device.type = "gpu")
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