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Relax the requirements on CustomOp. (#486)

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* Relax the requirements on CustomOp.

* Simplify the custom-ops when no backward is required.
This commit is contained in:
Laurent Mazare
2023-08-17 11:12:05 +01:00
committed by GitHub
parent d32e8199cd
commit 03be33eea4
8 changed files with 81 additions and 31 deletions
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6
candle-core/tests/custom_op_tests.rs
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@ -39,7 +39,7 @@ fn custom_op1_no_backward() -> Result<()> {
let cpu = &Device::Cpu;
let t = Tensor::arange(0u32, 12u32, cpu)?.to_dtype(DType::F32)?;
let t = (t - 5.)?;
let elu_t = t.custom_op1(Elu { alpha: 1. })?;
let elu_t = t.apply_op1_no_bwd(&Elu { alpha: 1. })?;
assert_eq!(
to_vec1_round(&elu_t, 4)?,
&[-0.9933, -0.9817, -0.9502, -0.8647, -0.6321, 0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0]
@ -96,7 +96,7 @@ impl CustomOp1 for EluWithBackward {
fn bwd(&self, arg: &Tensor, _res: &Tensor, grad_res: &Tensor) -> Result<Option<Tensor>> {
let alpha = self.0.alpha;
let bwd = arg.custom_op1(EluBackward { alpha })?;
let bwd = arg.apply_op1(EluBackward { alpha })?;
Ok(Some(grad_res.mul(&bwd)?))
}
}
@ -105,7 +105,7 @@ impl CustomOp1 for EluWithBackward {
fn custom_op1_with_backward() -> Result<()> {
let cpu = &Device::Cpu;
let t = candle_core::Var::new(&[-2f32, 0f32, 2f32], cpu)?;
let elu_t = t.custom_op1(EluWithBackward::new(2.))?;
let elu_t = t.apply_op1(EluWithBackward::new(2.))?;
assert_eq!(to_vec1_round(&elu_t, 4)?, &[-1.7293, 0.0, 2.0]);
let grads = elu_t.backward()?;