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Add some epsilon tolerance to grad tests so that they work on cuda / mkl. (#213)

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This commit is contained in:
Laurent Mazare
2023-07-21 13:45:14 +02:00
committed by GitHub
parent 410654525f
commit b02229ce92
3 changed files with 30 additions and 8 deletions
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5
candle-core/src/tensor.rs
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@ -482,6 +482,11 @@ impl Tensor {
} }
} }
/// An alias for `to_scalar`.
pub fn to_vec0<S: crate::WithDType>(&self) -> Result<S> {
self.to_scalar::<S>()
}
/// This operation multiplies the input tensor by `mul` then adds `add` and return the result. /// This operation multiplies the input tensor by `mul` then adds `add` and return the result.
/// The input values `mul` and `add` are casted to the appropriate type so some rounding might /// The input values `mul` and `add` are casted to the appropriate type so some rounding might
/// be performed. /// be performed.

16
candle-core/tests/grad_tests.rs
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@ -114,23 +114,23 @@ fn unary_grad(device: &Device) -> Result<()> {
let grads = y.backward()?; let grads = y.backward()?;
let grad_x = grads.get(x).context("no grad for x")?; let grad_x = grads.get(x).context("no grad for x")?;
assert_eq!( assert_eq!(
y.to_vec1::<f32>()?, test_utils::to_vec1_round(&y, 4)?,
[0.14112, 0.84147096, -0.7568025, 0.14943814], [0.1411, 0.8415, -0.7568, 0.1494],
); );
assert_eq!( assert_eq!(
grad_x.to_vec1::<f32>()?, test_utils::to_vec1_round(grad_x, 4)?,
[-0.9899925, 0.5403023, -0.6536436, 0.9887711], [-0.99, 0.5403, -0.6536, 0.9888],
); );
let y = x.cos()?; let y = x.cos()?;
let grads = y.backward()?; let grads = y.backward()?;
let grad_x = grads.get(x).context("no grad for x")?; let grad_x = grads.get(x).context("no grad for x")?;
assert_eq!( assert_eq!(
y.to_vec1::<f32>()?, test_utils::to_vec1_round(&y, 4)?,
[-0.9899925, 0.5403023, -0.6536436, 0.9887711], [-0.99, 0.5403, -0.6536, 0.9888],
); );
assert_eq!( assert_eq!(
grad_x.to_vec1::<f32>()?, test_utils::to_vec1_round(grad_x, 4)?,
[-0.14112, -0.84147096, 0.7568025, -0.14943814], [-0.1411, -0.8415, 0.7568, -0.1494],
); );
let y = x.sqr()?; let y = x.sqr()?;
let grads = y.backward()?; let grads = y.backward()?;

17
candle-core/tests/test_utils.rs
View File

@ -20,6 +20,23 @@ macro_rules! test_device {
}; };
} }
pub fn to_vec1_round(t: &Tensor, digits: i32) -> Result<Vec<f32>> {
let b = 10f32.powi(digits);
let t = t.to_vec1::<f32>()?;
let t = t.iter().map(|t| f32::round(t * b) / b).collect();
Ok(t)
}
pub fn to_vec2_round(t: &Tensor, digits: i32) -> Result<Vec<Vec<f32>>> {
let b = 10f32.powi(digits);
let t = t.to_vec2::<f32>()?;
let t = t
.iter()
.map(|t| t.iter().map(|t| f32::round(t * b) / b).collect())
.collect();
Ok(t)
}
pub fn to_vec3_round(t: Tensor, digits: i32) -> Result<Vec<Vec<Vec<f32>>>> { pub fn to_vec3_round(t: Tensor, digits: i32) -> Result<Vec<Vec<Vec<f32>>>> {
let b = 10f32.powi(digits); let b = 10f32.powi(digits);
let t = t.to_vec3::<f32>()?; let t = t.to_vec3::<f32>()?;