use apple_metal::MetalDevice;
use apple_mpsgraph::{
data_type, BinaryArithmeticOp, Feed, Graph, ReductionAxesOp, TensorData, UnaryArithmeticOp,
};
#[test]
fn unary_arithmetic_and_reduction_execute() {
let device = MetalDevice::system_default().expect("no Metal device available");
let graph = Graph::new().expect("graph");
let input = graph
.placeholder(Some(&[2, 2]), data_type::FLOAT32, Some("input"))
.expect("placeholder");
let squared = graph
.unary_arithmetic(UnaryArithmeticOp::Square, &input, Some("square"))
.expect("square");
let reduced = graph
.reduce_axes(ReductionAxesOp::Sum, &squared, &[1], Some("row_sum"))
.expect("reduce");
let input_data = TensorData::from_f32_slice(&device, &[1.0, 2.0, 3.0, 4.0], &[2, 2])
.expect("tensor data");
let results = graph
.run(&[Feed::new(&input, &input_data)], &[&reduced])
.expect("run");
assert_eq!(results[0].read_f32().expect("read"), vec![5.0, 25.0]);
}
#[test]
fn concat_split_and_topk_execute() {
let device = MetalDevice::system_default().expect("no Metal device available");
let graph = Graph::new().expect("graph");
let input = graph
.placeholder(Some(&[2, 3]), data_type::FLOAT32, Some("input"))
.expect("placeholder");
let squared = graph
.binary_arithmetic(BinaryArithmeticOp::Multiplication, &input, &input, Some("square"))
.expect("square via multiply");
let padded = graph
.pad(&squared, 0, &[0, 1], &[0, 1], 0.0, Some("pad"))
.expect("pad");
let topk = graph.top_k(&input, 2, Some("topk")).expect("topk");
let split = graph.split_num(&padded, 2, 1, Some("split"));
assert_eq!(split.len(), 2);
let input_data = TensorData::from_f32_slice(&device, &[1.0, 3.0, 2.0, 4.0, 6.0, 5.0], &[2, 3])
.expect("tensor data");
let results = graph
.run(
&[Feed::new(&input, &input_data)],
&[&topk.0, &split[0], &split[1]],
)
.expect("run");
assert_eq!(results[0].read_f32().expect("topk values"), vec![3.0, 2.0, 6.0, 5.0]);
assert_eq!(results[1].read_f32().expect("split 0"), vec![0.0, 1.0, 9.0, 0.0, 16.0, 36.0]);
assert_eq!(results[2].read_f32().expect("split 1"), vec![4.0, 0.0, 25.0, 0.0]);
}