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This commit is contained in:
Patrick von Platen
2023-08-23 08:42:47 +00:00
parent 34cb9f924f
commit b558d08b85
1 changed files with 6 additions and 7 deletions
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README.md
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@ -82,8 +82,10 @@ use anyhow::Result;
use candle_core::{Device, Tensor};
fn main() -> Result<()> {
let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
let device = Device::Cpu;
let a = Tensor::randn(0f32, 1., (2, 3), &device)?;
let b = Tensor::randn(0f32, 1., (3, 4), &device)?;
let c = a.matmul(&b)?;
println!("{c}");
@ -94,14 +96,11 @@ fn main() -> Result<()> {
`cargo run` should display a tensor of shape `Tensor[[2, 4], f32]`
Having installed `candle` with Cuda support, you can create the tensors on GPU instead as follows:
Having installed `candle` with Cuda support, simply define the `device` to be on GPU:
```diff
- let a = Tensor::randn(0f32, 1., (2, 3), &Device::Cpu)?;
- let b = Tensor::randn(0f32, 1., (3, 4), &Device::Cpu)?;
- let device = Device::Cpu;
+ let device = Device::new_cuda(0)?;
+ let a = Tensor::randn(0f32, 1., (2, 3), &device)?;
+ let b = Tensor::randn(0f32, 1., (3, 4), &device)?;
```
For more advanced examples, please have a look at the following sections.