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Change more consitently the test.

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This commit is contained in:
Nicolas Patry
2024-01-06 15:20:55 +01:00
parent 2bbd544832
commit 06d186355b
1 changed files with 28 additions and 8 deletions
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36
candle-core/tests/quantized_tests.rs
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@ -543,6 +543,26 @@ fn ggml_matmul_error_test<T: GgmlType>() -> Result<()> {
Ok(()) Ok(())
} }
fn get_small_tensors(
m: usize,
k: usize,
n: usize,
device: &Device,
) -> Result<(Tensor, Tensor, Tensor)> {
let lhs = (0..m * k)
.map(|i| i as f32 / (m * k) as f32)
.collect::<Vec<_>>();
let rhs = (0..n * k)
.map(|i| i as f32 / (n * k) as f32)
.collect::<Vec<_>>();
let lhs = Tensor::from_vec(lhs, (m, k), device)?;
let rhs = Tensor::from_vec(rhs, (n, k), device)?;
let mm = lhs.matmul(&rhs.t()?)?;
Ok((lhs, rhs, mm))
}
/// generates random tensors of size `m x k` and `n x k` and calculates their expected matrix multiplication result. /// generates random tensors of size `m x k` and `n x k` and calculates their expected matrix multiplication result.
fn get_random_tensors( fn get_random_tensors(
m: usize, m: usize,
@ -553,10 +573,10 @@ fn get_random_tensors(
let mut rng = StdRng::seed_from_u64(314159265358979); let mut rng = StdRng::seed_from_u64(314159265358979);
let lhs = (0..m * k) let lhs = (0..m * k)
.map(|i| i as f32 / (m * k) as f32) .map(|_| rng.gen::<f32>() - 0.5)
.collect::<Vec<_>>(); .collect::<Vec<_>>();
let rhs = (0..n * k) let rhs = (0..n * k)
.map(|i| i as f32 / (n * k) as f32) .map(|_| rng.gen::<f32>() - 0.5)
.collect::<Vec<_>>(); .collect::<Vec<_>>();
let lhs = Tensor::from_vec(lhs, (m, k), device)?; let lhs = Tensor::from_vec(lhs, (m, k), device)?;
@ -598,7 +618,7 @@ fn quantized_matmul_q3k() -> Result<()> {
let cpu = &Device::Cpu; let cpu = &Device::Cpu;
let (m, k, n) = (11, 512, 21); let (m, k, n) = (11, 512, 21);
let (lhs, rhs, mm) = get_random_tensors(m, k, n, cpu)?; let (lhs, rhs, mm) = get_small_tensors(m, k, n, cpu)?;
// assert_eq!(mm.dims(), [m, n]); // assert_eq!(mm.dims(), [m, n]);
// let dst = mm.flatten_all()?.to_vec1::<f32>()?; // let dst = mm.flatten_all()?.to_vec1::<f32>()?;
// let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]); // let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]);
@ -613,10 +633,10 @@ fn quantized_matmul_q3k() -> Result<()> {
.to_scalar()?; .to_scalar()?;
let error = error / (m * n) as f32; let error = error / (m * n) as f32;
assert_eq!(qmm.dims(), [m, n]); // assert_eq!(qmm.dims(), [m, n]);
let dst = qmm.flatten_all()?.to_vec1::<f32>()?; // let dst = qmm.flatten_all()?.to_vec1::<f32>()?;
let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]); // let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]);
assert_eq!(dst, [1.029, 1.418, -0.314, 1.495]); // assert_eq!(dst, [1.029, 1.418, -0.314, 1.495]);
assert!( assert!(
error < 0.01, error < 0.01,
@ -634,7 +654,7 @@ fn quantized_matmul_q4k() -> Result<()> {
let cpu = &Device::Cpu; let cpu = &Device::Cpu;
let (m, k, n) = (11, 512, 21); let (m, k, n) = (11, 512, 21);
let (lhs, rhs, mm) = get_random_tensors(m, k, n, cpu)?; let (lhs, rhs, mm) = get_small_tensors(m, k, n, cpu)?;
// assert_eq!(mm.dims(), [m, n]); // assert_eq!(mm.dims(), [m, n]);
// let dst = mm.flatten_all()?.to_vec1::<f32>()?; // let dst = mm.flatten_all()?.to_vec1::<f32>()?;
// let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]); // let dst = round_vector(&[dst[0], dst[m * n / 3], dst[m * n * 2 / 3], dst[m * n - 1]]);