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[pytorch-vulkan] aten::.rand_like #108086

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[pytorch-vulkan] aten::.rand_like #108086

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21 changes: 18 additions & 3 deletions aten/src/ATen/native/vulkan/ops/Random.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,9 @@ using namespace api::utils;

Tensor& uniform_(
Tensor& self,
double from,
double to,
c10::optional<at::Generator> /* not implemented */) {
const double from,
const double to,
const c10::optional<at::Generator> /* not implemented */) {
TORCH_CHECK(
self.is_vulkan(),
"Vulkan: In-place operator is only supported on Vulkan tensors.");
Expand Down Expand Up @@ -57,10 +57,25 @@ Tensor& uniform_(
return self;
}

Tensor rand_like(
const at::Tensor& input_arg,
const c10::optional<c10::ScalarType> /* not implemented */,
const c10::optional<c10::Layout> /* not implemented */,
const c10::optional<c10::Device> /* not implemented */,
const c10::optional<bool> /* not implemented */,
const c10::optional<c10::MemoryFormat> /* not implemented */) {
// Returns a tensor with the same size as input that is filled with random
// numbers from a uniform distribution on the interval [0,1). To match the CPU
// implementation, we simplify the range to [0,1] and tolerate the small
// chance of 1 being sampled.
return input_arg.clone().detach().uniform_(0.0, 1.0);
}

#ifdef USE_VULKAN_API

TORCH_LIBRARY_IMPL(aten, Vulkan, m) {
m.impl(TORCH_SELECTIVE_NAME("aten::uniform_"), TORCH_FN(uniform_));
m.impl(TORCH_SELECTIVE_NAME("aten::rand_like"), TORCH_FN(rand_like));
}

#endif /* USE_VULKAN_API */
Expand Down
31 changes: 22 additions & 9 deletions aten/src/ATen/test/vulkan_api_test.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -3921,16 +3921,9 @@ TEST_F(VulkanAPITest, sum_dim_keepdim_4d) {
test_sum_dim({9, 5, 7, 11}, {-2, -3, -4}, true);
}

TEST_F(VulkanAPITest, uniform) {
float a_min = -8.2f;
float a_max = -1.4f;

auto a_vulkan =
at::rand({8, 7, 12, 10}, at::device(at::kCPU).dtype(at::kFloat)).vulkan();
a_vulkan.uniform_(a_min, a_max);
void test_uniform(at::Tensor a_vulkan, const float a_min, const float a_max) {
auto a_cpu = a_vulkan.cpu();

ASSERT_TRUE(a_cpu.max().item<float>() < a_max);
ASSERT_TRUE(a_cpu.max().item<float>() <= a_max);
ASSERT_TRUE(a_cpu.min().item<float>() >= a_min);

// Verify range, also perform a loose check with on histogram distribution.
Expand All @@ -3956,6 +3949,26 @@ TEST_F(VulkanAPITest, uniform) {
(expected_per_bin * 0.05));
}

TEST_F(VulkanAPITest, uniform) {
float a_min = -8.2f;
float a_max = -1.4f;
auto a_vulkan =
at::rand({8, 7, 12, 10}, at::device(at::kCPU).dtype(at::kFloat)).vulkan();
a_vulkan.uniform_(a_min, a_max);
test_uniform(a_vulkan, a_min, a_max);
}

TEST_F(VulkanAPITest, rand_like) {
float a_min = 0.0f;
float a_max = 1.0f;
auto a_vulkan =
at::zeros({8, 7, 12, 10}, at::device(at::kCPU).dtype(at::kFloat)).vulkan();
const auto out_vulkan = at::rand_like(a_vulkan);
// verify that the input are still all zeros (not in-place)
ASSERT_TRUE(at::mean(a_vulkan.cpu()).item<float>() == 0.0);
test_uniform(out_vulkan, a_min, a_max);
}

void test_t(const at::IntArrayRef input_shape) {
const auto in_cpu = at::rand(input_shape, at::device(at::kCPU).dtype(at::kFloat));
const auto out_cpu = at::t(in_cpu);
Expand Down