Nothing
context("utils-data-sampler")
test_that("sampler's length", {
x <- torch_randn(1000, 10)
y <- torch_randn(1000)
data <- tensor_dataset(x, y)
sampler <- SequentialSampler(data)
expect_length(sampler, 1000)
sampler <- RandomSampler(data, num_samples = 10)
expect_length(sampler, 10)
sampler <- RandomSampler(data)
expect_length(sampler, 1000)
batch <- BatchSampler(sampler = sampler, batch_size = 32, drop_last = TRUE)
expect_length(batch, 1000 %/% 32)
batch <- BatchSampler(sampler = sampler, batch_size = 32, drop_last = FALSE)
expect_length(batch, 1000 %/% 32 + 1)
batch <- BatchSampler(sampler = sampler, batch_size = 100, drop_last = FALSE)
expect_length(batch, 10)
batch <- BatchSampler(sampler = sampler, batch_size = 1000, drop_last = FALSE)
expect_length(batch, 1)
batch <- BatchSampler(sampler = sampler, batch_size = 1001, drop_last = FALSE)
expect_length(batch, 1)
batch <- BatchSampler(sampler = sampler, batch_size = 1001, drop_last = TRUE)
expect_length(batch, 0)
})
test_that("Random sampler, replacement = TRUE", {
x <- torch_randn(2, 10)
y <- torch_randn(2)
data <- tensor_dataset(x, y)
x <- RandomSampler(data, replacement = TRUE)
it <- x$.iter()
for (i in 1:length(x)) {
k <- it()
expect_true(k <= 2 && k >= 1)
}
expect_equal(it(), coro::exhausted())
})
test_that("Batch sampler", {
x <- torch_randn(100, 10)
y <- torch_randn(2)
data <- tensor_dataset(x, y)
r <- RandomSampler(data, replacement = FALSE)
x <- BatchSampler(r, 32, TRUE)
it <- x$.iter()
expect_length(it(), 32)
expect_length(it(), 32)
expect_length(it(), 32)
expect_equal(it(), coro::exhausted())
})
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