Add some backprop test.

tests/grad_tests.rs

@@ -0,0 +1,19 @@
+use anyhow::{Context, Result};
+use candle::{Device, Tensor};
+
+#[test]
+fn simple_grad() -> Result<()> {
+    let x = Tensor::var(&[3f32, 1., 4.], Device::Cpu)?;
+    let five = Tensor::new(&[5f32, 5., 5.], Device::Cpu)?;
+    let x_times_five = x.mul(&five)?;
+    let x2 = x.mul(&x)?;
+    let y = x2.add(&x_times_five)?.add(&five)?;
+    let grads = y.backward()?;
+    let grad_x = grads.get(&x.id()).context("no grad for x")?;
+    assert_eq!(x.to_vec1::<f32>()?, [3., 1., 4.]);
+    // y = x^2 + 5.x + 5
+    assert_eq!(y.to_vec1::<f32>()?, [29., 11., 41.]);
+    // dy/dx = 2.x + 5
+    assert_eq!(grad_x.to_vec1::<f32>()?, [11., 7., 13.]);
+    Ok(())
+}