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Abstract the gradient storage.
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@ -6,7 +6,7 @@ fn simple_grad() -> Result<()> {
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let x = Tensor::var(&[3f32, 1., 4.], Device::Cpu)?;
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let y = (((&x * &x)? + &x * 5f64)? + 4f64)?;
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let grads = y.backward()?;
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let grad_x = grads.get(&x.id()).context("no grad for x")?;
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let grad_x = grads.get(&x).context("no grad for x")?;
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assert_eq!(x.to_vec1::<f32>()?, [3., 1., 4.]);
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// y = x^2 + 5.x + 4
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assert_eq!(y.to_vec1::<f32>()?, [28., 10., 40.]);
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