Cuda acceleration for quantized model. (#1754)

* Boilerplate for the quantized cuda support.

* More basic cuda support.

* More cuda quantization (quantize on cpu for now).

* Add the dequantization bit.

* Start adding some dedicated cuda kernels from llama.cpp.

* Move the kernel code.

* Start interfacing with the kernel.

* Tweak the kernel launch params.

* Bugfix for quantized metal.

* Fix some clippy lints.

* Tweak the launch parameters.

* Tweak cuda basics to perform a quantized matmul.

* Perform the dequantization on the cpu + use cublas for matmul.

* Add the dequantization kernel.

* Test the qmatmul.

* More kernels.

* Matmul-vec kernel.

* Add a couple kernels.

* More dequantization kernels.
This commit is contained in:
Laurent Mazare 2024-02-25 18:11:47 +01:00 committed by GitHub
parent 8d04f70f4d
commit 2f22afd80e
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
11 changed files with 1996 additions and 69 deletions

View File

@ -5,25 +5,32 @@ extern crate accelerate_src;
extern crate intel_mkl_src;
use anyhow::Result;
use candle_core::{Device, Tensor};
use candle_core::{Device, Module, Tensor};
use candle_core::quantized::{QMatMul, QTensor};
fn main() -> Result<()> {
let device = Device::new_cuda(0)?;
let in_t = Tensor::rand(-1f32, 1f32, (1, 3, 12, 7), &device)?;
let k_t = Tensor::rand(-1f32, 1f32, (6, 3, 1, 1), &device)?;
let out_t = in_t.conv2d(&k_t, 0, 1, 1, 1)?;
println!("{out_t}");
let in_t = in_t.to_device(&Device::Cpu)?;
let k_t = k_t.to_device(&Device::Cpu)?;
let out_t2 = in_t.conv2d(&k_t, 0, 1, 1, 1)?;
let diff = (out_t.to_device(&Device::Cpu)? - out_t2)?
.sqr()?
.sum_all()?;
println!("{diff}");
let q = Tensor::randn(0f32, 1.0, (72, 32), &device)?;
let q_cpu = q.to_device(&Device::Cpu)?;
let q = QTensor::quantize(&q, candle_core::quantized::GgmlDType::Q4_0)?;
let q = QMatMul::from_qtensor(q)?;
let x = Tensor::randn(0f32, 1.0, (5, 32), &device)?;
let res_q_cuda = q.forward(&x)?;
println!("{res_q_cuda}");
let t = Tensor::randn(0f32, 1f32, (2, 4, 96, 96), &device)?;
let w = Tensor::randn(0f32, 1f32, (320, 4, 3, 3), &device)?;
let res = t.conv2d(&w, 1, 1, 1, 1)?;
println!("{res:?}");
let q_cpu = QTensor::quantize(&q_cpu, candle_core::quantized::GgmlDType::Q4_0)?;
let q_cpu_tensor = q_cpu.dequantize(&Device::Cpu)?;
let q_cpu = QMatMul::from_qtensor(q_cpu)?;
let x_cpu = x.to_device(&Device::Cpu)?;
let res_q_cpu = q_cpu.forward(&x_cpu)?;
println!("{res_q_cpu}");
let res_mm = x_cpu.matmul(&q_cpu_tensor.t()?)?;
let diff = (res_mm - res_q_cuda.to_device(&Device::Cpu))?
.abs()?
.flatten_all()?
.max(0)?;
println!("{diff}");
Ok(())
}

View File

@ -827,9 +827,9 @@ impl BackendStorage for MetalStorage {
layout.start_offset() * self.dtype.size_in_bytes(),
),
&t.buffer,
(&t_l.stride(), t_l.start_offset() * t.dtype.size_in_bytes()),
(t_l.stride(), t_l.start_offset() * t.dtype.size_in_bytes()),
&f.buffer,
(&f_l.stride(), f_l.start_offset() * f.dtype.size_in_bytes()),
(f_l.stride(), f_l.start_offset() * f.dtype.size_in_bytes()),
&buffer,
)
.map_err(MetalError::from)?;
@ -1264,7 +1264,7 @@ impl BackendStorage for MetalStorage {
let src_offset = (src_l.start_offset() * self.dtype.size_in_bytes()) as NSUInteger;
let length = (src_l.shape().elem_count() * self.dtype.size_in_bytes()) as NSUInteger;
let dst_offset = (dst_offset * dst.dtype().size_in_bytes()) as NSUInteger;
blit.copy_from_buffer(&self.buffer, src_offset, &dst.buffer(), dst_offset, length);
blit.copy_from_buffer(&self.buffer, src_offset, dst.buffer(), dst_offset, length);
blit.end_encoding();
} else {
let src_shape = src_l.shape();
@ -1636,7 +1636,7 @@ impl BackendDevice for MetalDevice {
min as f32,
max as f32,
shape.elem_count(),
&*self.seed.lock().unwrap(),
&self.seed.lock().unwrap(),
&buffer,
)
.map_err(MetalError::from)?;
@ -1667,7 +1667,7 @@ impl BackendDevice for MetalDevice {
mean as f32,
stddev as f32,
shape.elem_count(),
&*self.seed.lock().unwrap(),
&self.seed.lock().unwrap(),
&buffer,
)
.map_err(MetalError::from)?;

View File

@ -0,0 +1,321 @@
use super::{GgmlDType, QStorage};
use crate::{backend::BackendDevice, cuda_backend::WrapErr};
use crate::{CudaDevice, CudaStorage, Result};
use cudarc::driver::{CudaSlice, DeviceSlice};
pub struct QCudaStorage {
data: CudaSlice<u8>,
dtype: GgmlDType,
device: CudaDevice,
}
pub const WARP_SIZE: usize = 32;
pub const MMQ_X_Q4_0_AMPERE: usize = 4;
pub const MMQ_Y_Q4_0_AMPERE: usize = 32;
pub const NWARPS_Q4_0_AMPERE: usize = 4;
pub const GGML_CUDA_MMV_X: usize = 32;
pub const GGML_CUDA_MMV_Y: usize = 1;
fn dequantize(
data: &CudaSlice<u8>,
dtype: GgmlDType,
elem_count: usize,
dev: &CudaDevice,
) -> Result<CudaStorage> {
use cudarc::driver::LaunchAsync;
let (kernel_name, is_k) = match dtype {
GgmlDType::Q4_0 => ("dequantize_block_q4_0", false),
GgmlDType::Q4_1 => ("dequantize_block_q4_1", false),
GgmlDType::Q5_0 => ("dequantize_block_q5_0", false),
GgmlDType::Q5_1 => ("dequantize_block_q5_1", false),
GgmlDType::Q8_0 => ("dequantize_block_q8_0", false),
GgmlDType::Q2K => ("dequantize_block_q2_K", true),
GgmlDType::Q3K => ("dequantize_block_q3_K", true),
GgmlDType::Q4K => ("dequantize_block_q4_K", true),
GgmlDType::Q5K => ("dequantize_block_q5_K", true),
GgmlDType::Q6K => ("dequantize_block_q6_K", true),
_ => crate::bail!("unsupported dtype for quantized matmul {dtype:?}"),
};
let func = dev.get_or_load_func(kernel_name, candle_kernels::QUANTIZED)?;
let dst = dev.alloc_zeros::<f32>(elem_count).w()?;
let nb = (elem_count + 255) / 256;
let cfg = cudarc::driver::LaunchConfig {
grid_dim: (nb as u32, 1, 1),
block_dim: (32, 1, 1),
shared_mem_bytes: 0,
};
if is_k {
let params = (data, &dst);
unsafe { func.launch(cfg, params) }.w()?;
} else {
let nb32 = elem_count / 32;
let params = (data, &dst, nb32 as i32);
unsafe { func.launch(cfg, params) }.w()?;
}
Ok(CudaStorage::wrap_cuda_slice(dst, dev.clone()))
}
fn dequantize_mut_mal_vec(
data: &CudaSlice<u8>,
y: &cudarc::driver::CudaView<f32>,
dtype: GgmlDType,
ncols: usize,
nrows: usize,
dev: &CudaDevice,
) -> Result<CudaStorage> {
use cudarc::driver::LaunchAsync;
let kernel_name = match dtype {
GgmlDType::Q4_0 => "dequantize_mul_mat_vec_q4_0_cuda",
GgmlDType::Q4_1 => "dequantize_mul_mat_vec_q4_1_cuda",
GgmlDType::Q5_0 => "dequantize_mul_mat_vec_q5_0_cuda",
GgmlDType::Q5_1 => "dequantize_mul_mat_vec_q5_1_cuda",
GgmlDType::Q8_0 => "dequantize_mul_mat_vec_q8_0_cuda",
GgmlDType::Q2K => "dequantize_mul_mat_vec_q2_k",
GgmlDType::Q3K => "dequantize_mul_mat_vec_q3_k",
GgmlDType::Q4K => "dequantize_mul_mat_vec_q4_k",
GgmlDType::Q5K => "dequantize_mul_mat_vec_q5_k",
GgmlDType::Q6K => "dequantize_mul_mat_vec_q6_k",
_ => crate::bail!("unsupported dtype for quantized matmul {dtype:?}"),
};
let func = dev.get_or_load_func(kernel_name, candle_kernels::QUANTIZED)?;
let dst = dev.alloc_zeros::<f32>(nrows).w()?;
let block_num_y = (nrows + GGML_CUDA_MMV_Y - 1) / GGML_CUDA_MMV_Y;
let cfg = cudarc::driver::LaunchConfig {
grid_dim: (block_num_y as u32, 1, 1),
block_dim: (WARP_SIZE as u32, GGML_CUDA_MMV_Y as u32, 1),
shared_mem_bytes: 0,
};
let params = (data, y, &dst, ncols as i32, nrows as i32);
unsafe { func.launch(cfg, params) }.w()?;
Ok(CudaStorage::wrap_cuda_slice(dst, dev.clone()))
}
impl QCudaStorage {
pub fn zeros(device: &CudaDevice, el_count: usize, dtype: GgmlDType) -> Result<Self> {
let size_in_bytes = el_count * dtype.type_size() / dtype.block_size();
let data = device.alloc_zeros::<u8>(size_in_bytes).w()?;
Ok(QCudaStorage {
data,
device: device.clone(),
dtype,
})
}
pub fn dtype(&self) -> GgmlDType {
self.dtype
}
pub fn device(&self) -> &CudaDevice {
&self.device
}
pub fn dequantize(&self, elem_count: usize) -> Result<CudaStorage> {
let fast_kernel = match self.dtype {
GgmlDType::Q4_0
| GgmlDType::Q4_1
| GgmlDType::Q5_0
| GgmlDType::Q5_1
| GgmlDType::Q8_0
| GgmlDType::Q2K
| GgmlDType::Q3K
| GgmlDType::Q4K
| GgmlDType::Q5K
| GgmlDType::Q6K => true,
_ => false,
};
if fast_kernel {
return dequantize(&self.data, self.dtype, elem_count, self.device());
}
// Run the dequantization on cpu.
use crate::quantized::k_quants::GgmlType;
let buffer = self.device.dtoh_sync_copy(&self.data).w()?;
let mut out = vec![0.0; elem_count];
let block_len = elem_count / self.dtype.block_size();
match self.dtype {
GgmlDType::F32 => {
let slice =
unsafe { std::slice::from_raw_parts(buffer.as_ptr() as *const f32, block_len) };
out.copy_from_slice(slice)
}
GgmlDType::F16 => {
let vec: Vec<half::f16> = read_to_vec(&buffer, block_len);
half::f16::to_float(&vec, &mut out)?;
}
GgmlDType::Q4_0 => {
let vec: Vec<crate::quantized::BlockQ4_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q4_1 => {
let vec: Vec<crate::quantized::BlockQ4_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q5_0 => {
let vec: Vec<crate::quantized::BlockQ5_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q5_1 => {
let vec: Vec<crate::quantized::BlockQ5_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q8_0 => {
let vec: Vec<crate::quantized::BlockQ8_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q8_1 => {
let vec: Vec<crate::quantized::BlockQ8_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q2K => {
let vec: Vec<crate::quantized::BlockQ2K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ2K::to_float(&vec, &mut out)?;
}
GgmlDType::Q3K => {
let vec: Vec<crate::quantized::BlockQ3K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ3K::to_float(&vec, &mut out)?;
}
GgmlDType::Q4K => {
let vec: Vec<crate::quantized::BlockQ4K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4K::to_float(&vec, &mut out)?;
}
GgmlDType::Q5K => {
let vec: Vec<crate::quantized::BlockQ5K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5K::to_float(&vec, &mut out)?;
}
GgmlDType::Q6K => {
let vec: Vec<crate::quantized::BlockQ6K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ6K::to_float(&vec, &mut out)?;
}
GgmlDType::Q8K => {
let vec: Vec<crate::quantized::BlockQ8K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8K::to_float(&vec, &mut out)?;
}
}
self.device
.storage_from_cpu_storage(&crate::CpuStorage::F32(out))
}
pub fn quantize(&mut self, src: &CudaStorage) -> Result<()> {
// Run the quantization on cpu.
let src = match &src.slice {
crate::cuda_backend::CudaStorageSlice::F32(data) => {
self.device.dtoh_sync_copy(data).w()?
}
_ => crate::bail!("only f32 can be quantized"),
};
let src_len = src.len();
let src = crate::Storage::Cpu(crate::CpuStorage::F32(src));
let mut qcpu_storage = crate::Device::Cpu.qzeros(src_len, self.dtype)?;
qcpu_storage.quantize(&src)?;
let data = qcpu_storage.data()?;
let data = self.device.htod_sync_copy(data.as_ref()).w()?;
self.data = data;
Ok(())
}
pub fn storage_size_in_bytes(&self) -> usize {
self.data.len()
}
pub fn fwd(
&self,
self_shape: &crate::Shape,
storage: &CudaStorage,
layout: &crate::Layout,
) -> Result<(CudaStorage, crate::Shape)> {
let dmmv = match layout.shape().dims() {
[1, 1, _] | [1, _] => true,
_ => false,
};
if dmmv {
self.dequantize_matmul_vec(self_shape, storage, layout)
} else {
self.dequantize_matmul(self_shape, storage, layout)
}
}
}
impl QCudaStorage {
fn dequantize_matmul_vec(
&self,
self_shape: &crate::Shape,
rhs: &CudaStorage,
rhs_l: &crate::Layout,
) -> Result<(CudaStorage, crate::Shape)> {
let (nrows, ncols) = self_shape.dims2()?;
let rhs = rhs.as_cuda_slice::<f32>()?;
let rhs = match rhs_l.contiguous_offsets() {
Some((o1, o2)) => rhs.slice(o1..o2),
None => Err(crate::Error::RequiresContiguous { op: "dmmv" }.bt())?,
};
let (with_batch, k) = match rhs_l.shape().dims() {
[1, 1, k] => (true, k),
[1, k] => (false, k),
_ => crate::bail!("unexpected rhs shape in dmmv {:?}", rhs_l.shape()),
};
if ncols != *k {
crate::bail!("mismatch on matmul dim {self_shape:?} {:?}", rhs_l.shape())
}
let out =
dequantize_mut_mal_vec(&self.data, &rhs, self.dtype, ncols, nrows, self.device())?;
let out_shape = if with_batch {
vec![1, 1, nrows]
} else {
vec![1, nrows]
};
Ok((out, out_shape.into()))
}
fn dequantize_matmul(
&self,
self_shape: &crate::Shape,
storage: &CudaStorage,
layout: &crate::Layout,
) -> Result<(CudaStorage, crate::Shape)> {
use crate::backend::BackendStorage;
let (n, k) = self_shape.dims2()?;
let (b, m, k2) = match layout.shape().dims() {
&[b, m, k2] => (b, m, k2),
&[m, k2] => (1, m, k2),
s => crate::bail!("unexpected shape for input {s:?}"),
};
if k2 != k {
crate::bail!("mismatch on matmul dim {self_shape:?} {:?}", layout.shape())
}
let data_f32 = self.dequantize(n * k)?;
let rhs_l = crate::Layout::new((k, n).into(), vec![1, k], 0);
let out = storage.matmul(&data_f32, (b, m, n, k), layout, &rhs_l)?;
let mut out_shape = layout.shape().dims().to_vec();
out_shape.pop();
out_shape.push(n);
Ok((out, out_shape.into()))
}
}
fn read_to_vec<T: Clone>(buffer: &[u8], n: usize) -> Vec<T> {
let slice = unsafe { std::slice::from_raw_parts(buffer.as_ptr() as *const T, n) };
slice.to_vec()
}
pub fn load_quantized<T: super::GgmlType + Send + Sync + 'static>(
device: &CudaDevice,
data: &[T],
) -> Result<super::QStorage> {
let data = unsafe {
std::slice::from_raw_parts(data.as_ptr() as *const u8, core::mem::size_of_val(data))
};
let data = device.htod_sync_copy(data).w()?;
Ok(QStorage::Cuda(QCudaStorage {
data,
device: device.clone(),
dtype: T::DTYPE,
}))
}

View File

@ -0,0 +1,50 @@
#![allow(unused)]
use super::GgmlDType;
use crate::{CudaDevice, CudaStorage, Error, Result};
pub struct QCudaStorage {
dtype: GgmlDType,
device: CudaDevice,
}
impl QCudaStorage {
pub fn zeros(_: &CudaDevice, _: usize, _: GgmlDType) -> Result<Self> {
Err(Error::NotCompiledWithCudaSupport)
}
pub fn dtype(&self) -> GgmlDType {
self.dtype
}
pub fn device(&self) -> &CudaDevice {
&self.device
}
pub fn dequantize(&self, _elem_count: usize) -> Result<CudaStorage> {
Err(Error::NotCompiledWithCudaSupport)
}
pub fn quantize(&mut self, _src: &CudaStorage) -> Result<()> {
Err(Error::NotCompiledWithCudaSupport)
}
pub fn storage_size_in_bytes(&self) -> usize {
0
}
pub fn fwd(
&self,
_self_shape: &crate::Shape,
_storage: &CudaStorage,
_layout: &crate::Layout,
) -> Result<(CudaStorage, crate::Shape)> {
Err(Error::NotCompiledWithCudaSupport)
}
}
pub fn load_quantized<T: super::GgmlType + Send + Sync + 'static>(
_device: &CudaDevice,
_data: &[T],
) -> Result<super::QStorage> {
Err(Error::NotCompiledWithCudaSupport)
}

View File

@ -41,3 +41,10 @@ impl QMetalStorage {
Err(Error::NotCompiledWithMetalSupport)
}
}
pub fn load_quantized<T: super::GgmlType + Send + Sync + 'static>(
_device: &MetalDevice,
_data: &[T],
) -> Result<super::QStorage> {
Err(Error::NotCompiledWithMetalSupport)
}

View File

@ -1,7 +1,5 @@
//! Support for the GGML file format.
#[cfg(feature = "metal")]
use super::metal::load_quantized_metal;
use super::{k_quants, GgmlDType, QStorage};
use crate::{Device, Result};
use byteorder::{LittleEndian, ReadBytesExt};
@ -130,13 +128,8 @@ fn from_raw_data<T: super::GgmlType + Send + Sync + 'static>(
let data = unsafe { std::slice::from_raw_parts(raw_data_ptr as *const T, n_blocks) };
let data: QStorage = match device {
Device::Cpu => QStorage::Cpu(Box::new(data.to_vec())),
#[cfg(feature = "metal")]
Device::Metal(metal) => load_quantized_metal(metal, data)?,
#[cfg(not(feature = "metal"))]
Device::Metal(_metal) => {
crate::bail!("Metal backend requires `metal` feature")
}
device => unimplemented!("Implement quantized tensor for device {device:?}"),
Device::Metal(metal) => super::metal::load_quantized(metal, data)?,
Device::Cuda(cuda) => super::cuda::load_quantized(cuda, data)?,
};
super::QTensor::new(data, dims)
}

View File

@ -34,6 +34,8 @@ impl QMetalStorage {
}
pub fn dequantize(&self, elem_count: usize) -> Result<MetalStorage> {
use crate::quantized::k_quants::GgmlType;
let buffer = self.device.new_buffer_managed(self.buffer.length())?;
let command_buffer = self.device.command_buffer()?;
command_buffer.set_label("to_cpu");
@ -43,81 +45,62 @@ impl QMetalStorage {
blit.end_encoding();
self.device.wait_until_completed()?;
let mut out = vec![0.0; elem_count];
let block_len = elem_count / self.dtype.block_size();
match self.dtype {
GgmlDType::F32 => {
let vec: Vec<f32> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<f32> = read_to_vec(&buffer, block_len);
f32::to_float(&vec, &mut out)?;
}
GgmlDType::F16 => {
let vec: Vec<half::f16> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<half::f16> = read_to_vec(&buffer, block_len);
half::f16::to_float(&vec, &mut out)?;
}
GgmlDType::Q4_0 => {
let vec: Vec<crate::quantized::BlockQ4_0> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ4_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q4_1 => {
let vec: Vec<crate::quantized::BlockQ4_1> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ4_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q5_0 => {
let vec: Vec<crate::quantized::BlockQ5_0> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ5_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q5_1 => {
let vec: Vec<crate::quantized::BlockQ5_1> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ5_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q8_0 => {
let vec: Vec<crate::quantized::BlockQ8_0> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ8_0> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8_0::to_float(&vec, &mut out)?;
}
GgmlDType::Q8_1 => {
let vec: Vec<crate::quantized::BlockQ8_1> = read_to_vec(&buffer, elem_count);
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ8_1> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8_1::to_float(&vec, &mut out)?;
}
GgmlDType::Q2K => {
let vec: Vec<crate::quantized::BlockQ2K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ2K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ2K::to_float(&vec, &mut out)?;
}
GgmlDType::Q3K => {
let vec: Vec<crate::quantized::BlockQ3K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ3K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ3K::to_float(&vec, &mut out)?;
}
GgmlDType::Q4K => {
let vec: Vec<crate::quantized::BlockQ4K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ4K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ4K::to_float(&vec, &mut out)?;
}
GgmlDType::Q5K => {
let vec: Vec<crate::quantized::BlockQ5K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ5K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ5K::to_float(&vec, &mut out)?;
}
GgmlDType::Q6K => {
let vec: Vec<crate::quantized::BlockQ6K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ6K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ6K::to_float(&vec, &mut out)?;
}
GgmlDType::Q8K => {
let vec: Vec<crate::quantized::BlockQ8K> =
read_to_vec(&buffer, elem_count / self.dtype.block_size());
use crate::quantized::k_quants::GgmlType;
let vec: Vec<crate::quantized::BlockQ8K> = read_to_vec(&buffer, block_len);
crate::quantized::BlockQ8K::to_float(&vec, &mut out)?;
}
}
@ -192,7 +175,7 @@ impl QMetalStorage {
}
}
pub fn load_quantized_metal<T: super::GgmlType + Send + Sync + 'static>(
pub fn load_quantized<T: super::GgmlType + Send + Sync + 'static>(
device: &MetalDevice,
data: &[T],
) -> Result<QStorage> {

View File

@ -4,6 +4,7 @@ use std::borrow::Cow;
#[cfg(target_feature = "avx")]
pub mod avx;
mod dummy_cuda;
mod dummy_metal;
pub mod ggml_file;
pub mod gguf_file;
@ -14,6 +15,13 @@ pub mod metal;
mod metal {
pub use super::dummy_metal::*;
}
#[cfg(feature = "cuda")]
pub mod cuda;
#[cfg(not(feature = "cuda"))]
mod cuda {
pub use super::dummy_cuda::*;
}
#[cfg(target_feature = "neon")]
pub mod neon;
#[cfg(target_feature = "simd128")]
@ -39,8 +47,9 @@ impl Device {
let storage = metal::QMetalStorage::zeros(metal, elem_count, dtype)?;
Ok(QStorage::Metal(storage))
}
Device::Cuda(_cuda) => {
crate::bail!("Cuda ggml quantization not supported");
Device::Cuda(cuda) => {
let storage = cuda::QCudaStorage::zeros(cuda, elem_count, dtype)?;
Ok(QStorage::Cuda(storage))
}
}
}
@ -49,6 +58,7 @@ impl Device {
pub enum QStorage {
Cpu(Box<dyn QuantizedType>),
Metal(metal::QMetalStorage),
Cuda(cuda::QCudaStorage),
}
impl QStorage {
@ -56,6 +66,7 @@ impl QStorage {
match self {
QStorage::Cpu(storage) => storage.block_size(),
QStorage::Metal(storage) => storage.dtype().block_size(),
QStorage::Cuda(storage) => storage.dtype().block_size(),
}
}
@ -63,6 +74,7 @@ impl QStorage {
match self {
QStorage::Cpu(storage) => storage.dtype(),
QStorage::Metal(storage) => storage.dtype(),
QStorage::Cuda(storage) => storage.dtype(),
}
}
@ -70,6 +82,7 @@ impl QStorage {
match self {
QStorage::Cpu(_storage) => Device::Cpu,
QStorage::Metal(storage) => Device::Metal(storage.device().clone()),
QStorage::Cuda(storage) => Device::Cuda(storage.device().clone()),
}
}
@ -77,6 +90,7 @@ impl QStorage {
match self {
QStorage::Cpu(storage) => storage.storage_size_in_bytes(),
QStorage::Metal(storage) => storage.storage_size_in_bytes(),
QStorage::Cuda(storage) => storage.storage_size_in_bytes(),
}
}
@ -86,6 +100,7 @@ impl QStorage {
storage.from_float(src.as_slice::<f32>()?)?;
}
(QStorage::Metal(storage), Storage::Metal(src)) => storage.quantize(src)?,
(QStorage::Cuda(storage), Storage::Cuda(src)) => storage.quantize(src)?,
_ => crate::bail!("Invalid dequantize storage locations do not match"),
}
Ok(())
@ -95,6 +110,7 @@ impl QStorage {
match self {
QStorage::Cpu(storage) => Ok(Storage::Cpu(storage.dequantize(elem_count)?)),
QStorage::Metal(storage) => Ok(Storage::Metal(storage.dequantize(elem_count)?)),
QStorage::Cuda(storage) => Ok(Storage::Cuda(storage.dequantize(elem_count)?)),
}
}
@ -106,7 +122,7 @@ impl QStorage {
let data = unsafe { std::slice::from_raw_parts(data_ptr, size_in_bytes) };
Ok(Cow::from(data))
}
QStorage::Metal(_storage) => {
QStorage::Metal(_) | QStorage::Cuda(_) => {
crate::bail!("not implemented");
}
}
@ -424,7 +440,7 @@ impl crate::CustomOp1 for QTensor {
#[allow(clippy::infallible_destructuring_match)]
let self_storage = match &self.storage {
QStorage::Cpu(storage) => storage,
QStorage::Metal(_) => crate::bail!("Invalid storage"),
QStorage::Metal(_) | QStorage::Cuda(_) => crate::bail!("Invalid storage"),
};
let slice = storage.as_slice::<f32>()?;
let slice = &slice[layout.start_offset()..layout.start_offset() + src_shape.elem_count()];
@ -444,6 +460,18 @@ impl crate::CustomOp1 for QTensor {
};
self_storage.fwd(&self.shape, storage, layout)
}
fn cuda_fwd(
&self,
storage: &crate::CudaStorage,
layout: &crate::Layout,
) -> Result<(crate::CudaStorage, Shape)> {
let self_storage = match &self.storage {
QStorage::Cuda(cuda) => cuda,
_ => unreachable!("Cannot call cuda matmul on non cuda QTensor"),
};
self_storage.fwd(&self.shape, storage, layout)
}
}
impl crate::Module for QMatMul {

View File

@ -0,0 +1 @@
pub const LAYERNORM_KERNELS: &str = include_str!(concat!(env!("OUT_DIR"), "/layernorm_kernels.ptx"));

View File

@ -4,6 +4,7 @@ pub const CAST: &str = include_str!(concat!(env!("OUT_DIR"), "/cast.ptx"));
pub const CONV: &str = include_str!(concat!(env!("OUT_DIR"), "/conv.ptx"));
pub const FILL: &str = include_str!(concat!(env!("OUT_DIR"), "/fill.ptx"));
pub const INDEXING: &str = include_str!(concat!(env!("OUT_DIR"), "/indexing.ptx"));
pub const QUANTIZED: &str = include_str!(concat!(env!("OUT_DIR"), "/quantized.ptx"));
pub const REDUCE: &str = include_str!(concat!(env!("OUT_DIR"), "/reduce.ptx"));
pub const TERNARY: &str = include_str!(concat!(env!("OUT_DIR"), "/ternary.ptx"));
pub const UNARY: &str = include_str!(concat!(env!("OUT_DIR"), "/unary.ptx"));

File diff suppressed because it is too large Load Diff