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use anyhow::Result;
use candle::{Device, Tensor};
fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let ids = Tensor::new(&[0u32, 2u32, 1u32], &device)?;
let t = Tensor::new(&[[0f32, 1f32], [2f32, 3f32], [4f32, 5f32]], &device)?;
let hs = Tensor::embedding(&ids, &t)?;
println!("> {:?}", hs.to_vec2::<f32>());
let x = Tensor::new(&[3f32, 1., 4., 1., 5.], &device)?;
println!("{:?}", x.to_vec1::<f32>()?);
let y = Tensor::new(&[2f32, 7., 1., 8., 2.], &device)?;
let z = (y + x * 3.)?;
println!("{:?}", z.to_vec1::<f32>()?);
println!("{:?}", z.sqrt()?.to_vec1::<f32>()?);
let x = Tensor::new(&[[11f32, 22.], [33., 44.], [55., 66.], [77., 78.]], &device)?;
let y = Tensor::new(&[[1f32, 2., 3.], [4., 5., 6.]], &device)?;
println!("{:?}", y.to_vec2::<f32>()?);
let z = x.matmul(&y)?;
println!("{:?}", z.to_vec2::<f32>()?);
let x = Tensor::new(
&[[11f32, 22.], [33., 44.], [55., 66.], [77., 78.]],
&Device::Cpu,
)?;
let y = Tensor::new(&[[1f32, 2., 3.], [4., 5., 6.]], &Device::Cpu)?;
println!("{:?}", y.to_vec2::<f32>()?);
let z = x.matmul(&y)?;
println!("{:?}", z.to_vec2::<f32>()?);
Ok(())
}
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