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fix: pow(0, y) gradient bug in cranelift and enzyme backends #139

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Merged
martinjrobins merged 4 commits into from
Jun 8, 2026
Merged

fix: pow(0, y) gradient bug in cranelift and enzyme backends #139

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980177d
version 0.12.0
martinjrobins May 30, 2026
a0412ab
fix: typo in dpow_f64
martinjrobins Jun 6, 2026
e5ae0b0
fix: x==0 guard for pow
martinjrobins Jun 6, 2026
8d98ba5
fix: pow(0, y) gradient bug in Enzyme, add test
martinjrobins Jun 8, 2026
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2 changes: 1 addition & 1 deletion diffsl/Cargo.toml
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
[package]
name = "diffsl"
version = "0.11.11"
version = "0.12.0"
edition.workspace = true
license.workspace = true
authors.workspace = true
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2 changes: 1 addition & 1 deletion diffsl/Enzyme
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Submodule Enzyme updated 216 files
2 changes: 1 addition & 1 deletion diffsl/src/execution/compiler.rs
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Expand Up @@ -2875,7 +2875,7 @@ mod tests {
state_and_const_grad2: "r_i { 3 * y, 2 * y }" expect "r" vec![3., 2.] ; vec![5.] ; vec![0., 0.] ; vec![0.],
state_and_const_grad3: "r_i { 2 * p, 3 }" expect "r" vec![2., 0.] ; vec![2.] ; vec![2., 0.] ; vec![2.],
state_and_const_grad4: "r_i { 3 * p, 2 * p }" expect "r" vec![3., 2.] ; vec![5.] ; vec![3., 2.] ; vec![5.],

pow_zero_grad: "r { pow(y - p, p) }" expect "r" vec![0.] ; vec![0.] ; vec![-1.] ; vec![-1.],
}

macro_rules! tensor_test_big_state {
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14 changes: 12 additions & 2 deletions diffsl/src/execution/functions.rs
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Expand Up @@ -315,7 +315,12 @@ extern "C" fn pow_f64(x: f64, y: f64) -> f64 {
x.powf(y)
}
extern "C" fn dpow_f64(x: f64, dx: f64, y: f64, dy: f64) -> f64 {
x.powf(y - 1.0) * (y * dx + x * dx.ln() * dy)
let d_dy = if x == 0.0 {
0.0 // lim x→0+ x^y * ln(x) = 0 for y > 0, avoids NaN from 0 * (-inf)
} else {
x * x.ln() * dy
};
x.powf(y - 1.0) * (y * dx + d_dy)
}

extern "C" fn min_f64(x: f64, y: f64) -> f64 {
Expand Down Expand Up @@ -465,7 +470,12 @@ extern "C" fn pow_f32(x: f32, y: f32) -> f32 {
x.powf(y)
}
extern "C" fn dpow_f32(x: f32, dx: f32, y: f32, dy: f32) -> f32 {
x.powf(y - 1.0) * (y * dx + x * dx.ln() * dy)
let d_dy = if x == 0.0 {
0.0 // lim x→0+ x^y * ln(x) = 0 for y > 0, avoids NaN from 0 * (-inf)
} else {
x * x.ln() * dy
};
x.powf(y - 1.0) * (y * dx + d_dy)
}

extern "C" fn min_f32(x: f32, y: f32) -> f32 {
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