use std::ops::{AddAssign, DivAssign};
use std::sync::Arc;
use std::{iter, ops::MulAssign};
use crate::vector::kmeans::{KMeansAlgoFloat, compute_partitions};
use arrow_array::ArrowNumericType;
use arrow_array::{
Array, FixedSizeListArray, PrimitiveArray, RecordBatch, UInt32Array,
cast::AsArray,
types::{Float16Type, Float32Type, Float64Type, UInt32Type},
};
use arrow_schema::DataType;
use lance_arrow::{FixedSizeListArrayExt, RecordBatchExt};
use lance_core::{Error, Result};
use lance_linalg::distance::{DistanceType, Dot, L2};
use num_traits::{Float, FromPrimitive, Num};
use tracing::instrument;
use super::{PQ_CODE_COLUMN, transform::Transformer};
#[derive(Clone)]
pub struct ResidualTransform {
centroids: FixedSizeListArray,
part_col: String,
vec_col: String,
}
impl std::fmt::Debug for ResidualTransform {
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
write!(f, "ResidualTransform")
}
}
impl ResidualTransform {
pub fn new(centroids: FixedSizeListArray, part_col: &str, column: &str) -> Self {
Self {
centroids,
part_col: part_col.to_owned(),
vec_col: column.to_owned(),
}
}
}
fn do_compute_residual<T: ArrowNumericType>(
centroids: &FixedSizeListArray,
vectors: &FixedSizeListArray,
distance_type: Option<DistanceType>,
partitions: Option<&UInt32Array>,
) -> Result<FixedSizeListArray>
where
T::Native: Num + Float + L2 + Dot + MulAssign + DivAssign + AddAssign + FromPrimitive,
PrimitiveArray<T>: From<Vec<T::Native>>,
{
let dimension = centroids.value_length() as usize;
let centroids = centroids.values().as_primitive::<T>();
let vectors = vectors.values().as_primitive::<T>();
let part_ids = partitions.cloned().unwrap_or_else(|| {
compute_partitions::<T, KMeansAlgoFloat<T>>(
centroids,
vectors,
dimension,
distance_type.expect("provide either partitions or distance type"),
)
.0
.into()
});
let part_ids = part_ids.values();
let vectors_slice = vectors.values();
let centroids_slice = centroids.values();
let mut residuals = Vec::with_capacity(vectors.len());
for (idx, vector) in vectors_slice.chunks_exact(dimension).enumerate() {
let part_id = part_ids[idx] as usize;
let c = ¢roids_slice[part_id * dimension..(part_id + 1) * dimension];
residuals.extend(iter::zip(vector, c).map(|(v, cent)| *v - *cent));
}
debug_assert_eq!(residuals.len(), vectors.len());
let residual_arr = PrimitiveArray::<T>::from_iter_values(residuals);
debug_assert_eq!(residual_arr.len(), vectors.len());
Ok(FixedSizeListArray::try_new_from_values(
residual_arr,
dimension as i32,
)?)
}
pub(crate) fn compute_residual(
centroids: &FixedSizeListArray,
vectors: &FixedSizeListArray,
distance_type: Option<DistanceType>,
partitions: Option<&UInt32Array>,
) -> Result<FixedSizeListArray> {
if centroids.value_length() != vectors.value_length() {
return Err(Error::index(format!(
"Compute residual vector: centroid and vector length mismatch: centroid: {}, vector: {}",
centroids.value_length(),
vectors.value_length(),
)));
}
match (centroids.value_type(), vectors.value_type()) {
(DataType::Float16, DataType::Float16) => {
do_compute_residual::<Float16Type>(centroids, vectors, distance_type, partitions)
}
(DataType::Float32, DataType::Float32) => {
do_compute_residual::<Float32Type>(centroids, vectors, distance_type, partitions)
}
(DataType::Float64, DataType::Float64) => {
do_compute_residual::<Float64Type>(centroids, vectors, distance_type, partitions)
}
(DataType::Float32, DataType::Int8) => do_compute_residual::<Float32Type>(
centroids,
&vectors.convert_to_floating_point()?,
distance_type,
partitions,
),
_ => Err(Error::index(format!(
"Compute residual vector: centroids and vector type mismatch: centroid: {}, vector: {}",
centroids.value_type(),
vectors.value_type(),
))),
}
}
impl Transformer for ResidualTransform {
#[instrument(name = "ResidualTransform::transform", level = "debug", skip_all)]
fn transform(&self, batch: &RecordBatch) -> Result<RecordBatch> {
if batch.column_by_name(PQ_CODE_COLUMN).is_some() {
return Ok(batch.clone());
}
let part_ids = batch
.column_by_name(&self.part_col)
.ok_or(Error::index(format!(
"Compute residual vector: partition id column not found: {}",
self.part_col
)))?;
let original = batch
.column_by_name(&self.vec_col)
.ok_or(Error::index(format!(
"Compute residual vector: original vector column {} not found in batch {}",
self.vec_col,
batch.schema(),
)))?;
let original_vectors = original
.as_fixed_size_list_opt()
.ok_or(Error::index(format!(
"Compute residual vector: original vector column {} is not fixed size list: {}",
self.vec_col,
original.data_type(),
)))?;
let part_ids_ref = part_ids.as_primitive::<UInt32Type>();
let residual_arr =
compute_residual(&self.centroids, original_vectors, None, Some(part_ids_ref))?;
let batch = if residual_arr.data_type() != original.data_type() {
batch.replace_column_schema_by_name(
&self.vec_col,
residual_arr.data_type().clone(),
Arc::new(residual_arr),
)?
} else {
batch.replace_column_by_name(&self.vec_col, Arc::new(residual_arr))?
};
Ok(batch)
}
}