burn-cubecl 0.22.0-pre.4

use super::init_matmul_output;
use crate::{kernel::quantization::dequantize, tensor::CubeTensor};
use burn_backend::cubecl::dtype_to_storage_type;
use burn_backend::{DType, TensorMetadata};
use burn_std::{MatmulTransformAnalysis, MatmulTransformPolicy};
use cubek::{
    matmul::{
        definition::{MatmulElems, MatmulGlobalElems, MatmulSetupError},
        strategy::Strategy,
    },
    std::InputBinding,
};

#[cfg(feature = "autotune")]
use super::matmul_autotune;

/// The strategy to be used when launching a matmul kernel.
pub enum MatmulStrategy {
    #[cfg(feature = "autotune")]
    /// Using autotune to choose the best kernel based on runtime information.
    Autotune,
    /// Cube implementation of matmul.
    Cube,
}

impl Default for MatmulStrategy {
    fn default() -> Self {
        // if autotune is enabled, default to autotune
        #[cfg(feature = "autotune")]
        return MatmulStrategy::Autotune;

        #[cfg(not(feature = "autotune"))]
        MatmulStrategy::Cube
    }
}

fn is_two_level(tensor: &CubeTensor) -> bool {
    match tensor.dtype {
        DType::QFloat(scheme) => burn_backend::quantization::global_scale_dtype(&scheme).is_some(),
        _ => false,
    }
}

fn maybe_dequantize(tensor: CubeTensor, dtype: DType) -> CubeTensor {
    if is_two_level(&tensor) {
        dequantize(tensor, dtype)
    } else {
        tensor
    }
}

/// Launch a matmul kernel using the given strategy.
pub fn matmul(
    lhs: CubeTensor,
    rhs: CubeTensor,
    out: Option<CubeTensor>,
    strategy: MatmulStrategy,
    out_dtype: DType,
) -> Result<CubeTensor, MatmulSetupError> {
    let out = out.unwrap_or_else(|| init_matmul_output(&lhs, &rhs, out_dtype));

    // No quantized matmul kernel applies a per-tensor scale, and the autotune candidates panic on
    // the level rather than decline it, taking the whole tuning run down with them.
    let mut lhs = maybe_dequantize(lhs, out_dtype);
    let rhs = maybe_dequantize(rhs, out_dtype);

    // A broadcast-rhs batched matmul that would tile poorly is folded into a
    // single matmul: `[.., b, m, k] @ [.., 1, k, n]` runs as `[.., 1, b*m, k]`
    // instead of `b` matmuls that each re-read the whole rhs. Pure metadata —
    // the launch operands share the handles, the returned tensor keeps the
    // broadcast shape.
    let mut out_launch = out.clone();
    if lhs.qparams.is_none() {
        let analysis = MatmulTransformAnalysis::from_metadata(&lhs.meta, &rhs.meta, &out.meta);
        let action = MatmulTransformPolicy::default().action(&analysis);
        action.apply(&mut lhs.meta);
        action.apply(&mut out_launch.meta);
    }

    match strategy {
        MatmulStrategy::Cube => {
            launch_matmul(&Strategy::default(), lhs, rhs, out_launch)?;
            Ok(out)
        }
        #[cfg(feature = "autotune")]
        MatmulStrategy::Autotune => {
            matmul_autotune(lhs, rhs, Some(out_launch), out_dtype);
            Ok(out)
        }
    }
}

pub(crate) fn launch_matmul_naive<S: Clone + Into<Strategy>>(
    strategy: &S,
    mut lhs: CubeTensor,
    mut rhs: CubeTensor,
    out: CubeTensor,
) -> Result<(), MatmulSetupError> {
    // Naive has very specific layout requirements for block scaled tensors, so we need to manually
    // dequantize if it fails to launch normally. This is because naive is assumed to always work.
    if lhs.qparams.is_some() || rhs.qparams.is_some() {
        match launch_matmul(strategy, lhs.clone(), rhs.clone(), out.clone()) {
            Err(_) => {
                if lhs.qparams.is_some() {
                    lhs = dequantize(lhs, out.dtype);
                }
                if rhs.qparams.is_some() {
                    rhs = dequantize(rhs, out.dtype);
                }
                launch_matmul(strategy, lhs, rhs, out)
            }
            Ok(_) => Ok(()),
        }
    } else {
        launch_matmul(strategy, lhs, rhs, out)
    }
}

pub(crate) fn launch_matmul<S: Clone + Into<Strategy>>(
    strategy: &S,
    lhs: CubeTensor,
    mut rhs: CubeTensor,
    out: CubeTensor,
) -> Result<(), MatmulSetupError> {
    let strategy: Strategy = strategy.clone().into();
    let client = &out.client;

    let lhs_quant_handles = lhs.quantized_handles();
    let out_dtype: DType = out.dtype;

    let (lhs_dtype, lhs_handle) = match lhs_quant_handles {
        None => {
            let lhs_dtype = lhs.dtype;
            (
                lhs_dtype,
                InputBinding::new(lhs.binding(), dtype_to_storage_type(lhs_dtype)),
            )
        }
        Some((data, scale)) => {
            let scheme = lhs.scheme();
            let data_dtype = data.dtype;
            let scale_dtype = scale.dtype;
            (
                out_dtype,
                InputBinding::quantized(
                    data.binding(),
                    scale.binding(),
                    lhs.meta.shape().clone(),
                    scheme,
                    dtype_to_storage_type(data_dtype),
                    dtype_to_storage_type(scale_dtype),
                ),
            )
        }
    };

    let rhs_quant_handles = rhs.quantized_handles();

    let (rhs_dtype, rhs_handle) = match rhs_quant_handles {
        None => (
            lhs_dtype,
            InputBinding::new(rhs.binding(), dtype_to_storage_type(lhs_dtype)),
        ),
        Some((data, scale)) => {
            // Extremely hacky fix to ensure naive can run in every case
            if matches!(
                strategy,
                Strategy::MultiLevel(cubek::matmul::multi_level::Strategy::Naive)
            ) && rhs.scheme().block_size().is_some()
            {
                rhs = dequantize(rhs.clone(), lhs_dtype);
                let rhs_dtype = rhs.dtype;
                (
                    lhs_dtype,
                    InputBinding::new(rhs.binding(), dtype_to_storage_type(rhs_dtype)),
                )
            } else {
                let scheme = rhs.scheme();
                let data_dtype = data.dtype;
                let scale_dtype = scale.dtype;
                (
                    out_dtype,
                    InputBinding::quantized(
                        data.binding(),
                        scale.binding(),
                        rhs.meta.shape().clone(),
                        scheme,
                        dtype_to_storage_type(data_dtype),
                        dtype_to_storage_type(scale_dtype),
                    ),
                )
            }
        }
    };

    let mut dtypes = MatmulElems::from_globals(&MatmulGlobalElems {
        lhs: dtype_to_storage_type(lhs_dtype),
        rhs: dtype_to_storage_type(rhs_dtype),
        out: dtype_to_storage_type(out_dtype),
    });

    cubek::matmul::launch::launch_ref(
        &strategy,
        client,
        lhs_handle,
        rhs_handle,
        out.clone().binding(),
        &mut dtypes,
    )?;

    Ok(())
}