use std::collections::HashMap;
use half::bf16;
use half::f16;
use crate::model::{DataType, TensorData};
use crate::runtime::tensor::Tensor;
pub struct Runtime {
tensors: HashMap<String, Tensor>,
}
fn bytes_to_f32_slice(td: &TensorData) -> Option<Vec<f32>> {
let count = td.element_count();
match td.dtype {
DataType::F32 => {
let byte_len = count * 4;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(4).enumerate() {
out[i] = f32::from_le_bytes([chunk[0], chunk[1], chunk[2], chunk[3]]);
}
Some(out)
}
DataType::F16 => {
let byte_len = count * 2;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(2).enumerate() {
let bits = u16::from_le_bytes([chunk[0], chunk[1]]);
out[i] = f16::from_bits(bits).to_f32();
}
Some(out)
}
DataType::BF16 => {
let byte_len = count * 2;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(2).enumerate() {
let bits = u16::from_le_bytes([chunk[0], chunk[1]]);
out[i] = bf16::from_bits(bits).to_f32();
}
Some(out)
}
DataType::I64 => {
let byte_len = count * 8;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(8).enumerate() {
out[i] = i64::from_le_bytes([
chunk[0], chunk[1], chunk[2], chunk[3], chunk[4], chunk[5], chunk[6], chunk[7],
]) as f32;
}
Some(out)
}
DataType::I32 => {
let byte_len = count * 4;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(4).enumerate() {
out[i] = i32::from_le_bytes([chunk[0], chunk[1], chunk[2], chunk[3]]) as f32;
}
Some(out)
}
DataType::I16 => {
let byte_len = count * 2;
if td.data.len() < byte_len {
return None;
}
let mut out = vec![0.0f32; count];
for (i, chunk) in td.data[..byte_len].chunks_exact(2).enumerate() {
out[i] = i16::from_le_bytes([chunk[0], chunk[1]]) as f32;
}
Some(out)
}
DataType::I8 => {
if td.data.len() < count {
return None;
}
let mut out = vec![0.0f32; count];
for (i, &b) in td.data[..count].iter().enumerate() {
out[i] = b as i8 as f32;
}
Some(out)
}
DataType::U8 => {
if td.data.len() < count {
return None;
}
let mut out = vec![0.0f32; count];
for (i, &b) in td.data[..count].iter().enumerate() {
out[i] = b as f32;
}
Some(out)
}
DataType::Bool => {
if td.data.len() < count {
return None;
}
let mut out = vec![0.0f32; count];
for (i, &b) in td.data[..count].iter().enumerate() {
out[i] = if b != 0 { 1.0 } else { 0.0 };
}
Some(out)
}
DataType::Q4_0 | DataType::Q5_0 | DataType::Q8_0 | DataType::Q4_K | DataType::Q6_K => None,
}
}
impl Runtime {
pub fn from_raw(raw: &HashMap<String, TensorData>) -> Self {
let mut tensors = HashMap::new();
for (name, td) in raw {
let fdata =
bytes_to_f32_slice(td).or_else(|| crate::parsers::gguf::dequantize_gguf_tensor(td));
if let Some(data) = fdata {
tensors.insert(name.clone(), Tensor::from_vec(data, td.shape.clone()));
}
}
Self { tensors }
}
pub fn get(&self, name: &str) -> Option<&Tensor> {
self.tensors.get(name)
}
pub fn tensor_names(&self) -> Vec<&String> {
let mut names: Vec<&String> = self.tensors.keys().collect();
names.sort();
names
}
}
#[cfg(test)]
mod tests {
use std::collections::HashMap;
use half::f16;
use crate::model::{DataType, TensorData};
use crate::runtime::serve::Runtime;
#[test]
fn runtime_dequantizes_q8_0_on_the_fly() {
let mut block = Vec::with_capacity(34);
block.extend_from_slice(&f16::from_f32(2.0).to_bits().to_le_bytes());
for j in 0..32 {
block.push(if j == 0 { 5i8 as u8 } else { 0 });
}
let raw = HashMap::from([(
"w".to_string(),
TensorData {
shape: vec![32],
dtype: DataType::Q8_0,
data: block,
},
)]);
let rt = Runtime::from_raw(&raw);
let t = rt.get("w").expect("tensor loaded");
assert_eq!(t.data.len(), 32);
assert!(
(t.data[0] - 10.0).abs() < 1e-5,
"first element: {}",
t.data[0]
);
assert!(
t.data[1..].iter().all(|&v| v.abs() < 1e-6),
"rest should be zero"
);
}
#[test]
fn runtime_dequantizes_q4_0_on_the_fly() {
let mut block = Vec::with_capacity(18);
block.extend_from_slice(&f16::from_f32(1.0).to_bits().to_le_bytes());
block.extend(vec![0x88u8; 16]);
let raw = HashMap::from([(
"w".to_string(),
TensorData {
shape: vec![32],
dtype: DataType::Q4_0,
data: block,
},
)]);
let rt = Runtime::from_raw(&raw);
let t = rt.get("w").expect("tensor loaded");
assert_eq!(t.data.len(), 32);
}
}