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Add RandomNormal ONNX operator (#2200)

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This commit is contained in:
mokulus
2024-05-21 21:47:32 +02:00
committed by GitHub
parent 9b8537a62f
commit 7ff921c538
2 changed files with 158 additions and 8 deletions
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22
candle-onnx/src/eval.rs
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@ -971,7 +971,7 @@ pub fn simple_eval(
};
values.insert(node.output[0].clone(), output);
}
"RandomUniform" => {
random_type @ ("RandomUniform" | "RandomNormal") => {
let dt: i64 = get_attr_opt(node, "dtype")?.copied().unwrap_or(1); // 1 is float
// type by
// default
@ -979,36 +979,42 @@ pub fn simple_eval(
Ok(dt) => match dtype(dt) {
Some(DType::U8 | DType::U32 | DType::I64) => {
bail!(
"unsupported 'dtype' value {dt:?}, only floats are allowed, for RandomUnifrom {}",
"unsupported 'dtype' value {dt:?}, only floats are allowed, for {random_type} {}",
node.name
)
}
Some(dt) => dt,
None => {
bail!(
"unsupported 'dtype' value {dt:?} for RandomUnifrom {}",
"unsupported 'dtype' value {dt:?} for {random_type} {}",
node.name
)
}
},
Err(_) => {
bail!(
"unsupported 'dtype' value {dt:?} for RandomUniform {}",
"unsupported 'dtype' value {dt:?} for {random_type} {}",
node.name
)
}
};
let low: f32 = get_attr_opt(node, "low")?.copied().unwrap_or(0.0);
let high: f32 = get_attr_opt(node, "high")?.copied().unwrap_or(1.0);
let seed: Option<f32> = get_attr_opt(node, "seed")?.copied();
if seed.is_some() {
bail!("seed for RandomUniform is currently not supported")
bail!("seed for {random_type} is currently not supported")
};
let shape: Vec<usize> = get_attr::<[i64]>(node, "shape")?
.iter()
.map(|x| *x as usize)
.collect();
let output = Tensor::rand(low, high, shape, &Device::Cpu)?.to_dtype(dtype)?;
let output = if random_type == "RandomUniform" {
let low: f32 = get_attr_opt(node, "low")?.copied().unwrap_or(0.0);
let high: f32 = get_attr_opt(node, "high")?.copied().unwrap_or(1.0);
Tensor::rand(low, high, shape, &Device::Cpu)?.to_dtype(dtype)?
} else {
let mean: f32 = get_attr_opt(node, "mean")?.copied().unwrap_or(0.0);
let scale: f32 = get_attr_opt(node, "scale")?.copied().unwrap_or(1.0);
Tensor::randn(mean, scale, shape, &Device::Cpu)?.to_dtype(dtype)?
};
values.insert(node.output[0].clone(), output);
}
op_type => bail!("unsupported op_type {op_type} for op {node:?}"),