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Also run the backprop tests on cuda.

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This commit is contained in:
laurent
2023-06-28 08:15:03 +01:00
parent a457020d50
commit 395c84e80a
3 changed files with 10 additions and 8 deletions
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16
candle-core/tests/grad_tests.rs
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@ -1,9 +1,9 @@
use anyhow::{Context, Result};
use candle::{Device, Shape, Tensor};
mod test_utils;
#[test]
fn simple_grad() -> Result<()> {
let x = Tensor::var(&[3f32, 1., 4.], &Device::Cpu)?;
fn simple_grad(device: &Device) -> Result<()> {
let x = Tensor::var(&[3f32, 1., 4.], device)?;
let y = (((&x * &x)? + &x * 5f64)? + 4f64)?;
let grads = y.backward()?;
let grad_x = grads.get(&x).context("no grad for x")?;
@ -15,12 +15,11 @@ fn simple_grad() -> Result<()> {
Ok(())
}
#[test]
fn matmul_grad() -> Result<()> {
fn matmul_grad(device: &Device) -> Result<()> {
let data: Vec<_> = (0..12).map(|i| i as f32).collect();
let x = Tensor::var_from_slice(&data, (2, 2, 3), &Device::Cpu)?;
let x = Tensor::var_from_slice(&data, (2, 2, 3), device)?;
let data: Vec<_> = (0..12).map(|i| i as f32).collect();
let y = Tensor::var_from_slice(&data, (2, 3, 2), &Device::Cpu)?;
let y = Tensor::var_from_slice(&data, (2, 3, 2), device)?;
let c = x.matmul(&y)?;
let grads = c.backward()?;
@ -38,3 +37,6 @@ fn matmul_grad() -> Result<()> {
);
Ok(())
}
test_device!(simple_grad, simple_grad_cpu, simple_grad_gpu);
test_device!(matmul_grad, matmul_grad_cpu, matmul_grad_gpu);