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Implement the module trait directly for QMatMul. (#1372)

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This commit is contained in:
Laurent Mazare
2023-11-25 10:09:45 +00:00
committed by GitHub
parent 762e996ce6
commit bfa7c8fc01
7 changed files with 11 additions and 18 deletions
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11
candle-core/examples/basics.rs
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@ -8,11 +8,10 @@ use anyhow::Result;
use candle_core::{Device, Tensor}; use candle_core::{Device, Tensor};
fn main() -> Result<()> { fn main() -> Result<()> {
let inp = Tensor::randn(0f32, 1., (2, 320, 96, 96), &Device::Cpu)?; let a = Tensor::new(&[[0.0f32, 1.0, 2.0], [3.0, 4.0, 5.0]], &Device::Cpu)?;
let w = Tensor::randn(0f32, 1., (320, 320, 3, 3), &Device::Cpu)?; let b = Tensor::new(&[[88.0f32, 99.0]], &Device::Cpu)?;
let start = std::time::Instant::now(); let new_a = a.slice_scatter(&b, 1, 2)?;
let res = inp.conv2d(&w, 0, 1, 1, 1)?; assert_eq!(a.to_vec2::<f32>()?, [[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
println!("{:?}", start.elapsed()); assert_eq!(new_a.to_vec2::<f32>()?, [[0.0, 1.0, 2.0], [3.0, 4.0, 5.0]]);
println!("{res:?}");
Ok(()) Ok(())
} }

6
candle-core/src/lib.rs
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@ -123,12 +123,6 @@ pub trait Module {
fn forward(&self, xs: &Tensor) -> Result<Tensor>; fn forward(&self, xs: &Tensor) -> Result<Tensor>;
} }
impl Module for quantized::QMatMul {
fn forward(&self, xs: &Tensor) -> Result<Tensor> {
self.forward(xs)
}
}
impl<T: Fn(&Tensor) -> Result<Tensor>> Module for T { impl<T: Fn(&Tensor) -> Result<Tensor>> Module for T {
fn forward(&self, xs: &Tensor) -> Result<Tensor> { fn forward(&self, xs: &Tensor) -> Result<Tensor> {
self(xs) self(xs)

4
candle-core/src/quantized/mod.rs
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@ -307,8 +307,8 @@ impl crate::CustomOp1 for QTensor {
} }
} }
impl QMatMul { impl crate::Module for QMatMul {
pub fn forward(&self, xs: &Tensor) -> Result<Tensor> { fn forward(&self, xs: &Tensor) -> Result<Tensor> {
match self { match self {
Self::QTensor(t) => xs.apply_op1_no_bwd(t.as_ref()), Self::QTensor(t) => xs.apply_op1_no_bwd(t.as_ref()),
Self::Tensor(w) => { Self::Tensor(w) => {

2
candle-core/tests/quantized_tests.rs
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@ -1,7 +1,7 @@
use candle_core::{ use candle_core::{
quantized::{self, GgmlDType}, quantized::{self, GgmlDType},
test_utils::to_vec2_round, test_utils::to_vec2_round,
Device, Result, Tensor, Device, Module, Result, Tensor,
}; };
use quantized::{k_quants, GgmlType}; use quantized::{k_quants, GgmlType};
use rand::prelude::*; use rand::prelude::*;

2
candle-nn/examples/cpu_benchmarks.rs
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@ -6,7 +6,7 @@ extern crate intel_mkl_src;
extern crate accelerate_src; extern crate accelerate_src;
use candle::quantized::GgmlType; use candle::quantized::GgmlType;
use candle::{CpuStorage, Device, Layout, Result, Shape, Tensor, D}; use candle::{CpuStorage, Device, Layout, Module, Result, Shape, Tensor, D};
use clap::{Parser, Subcommand}; use clap::{Parser, Subcommand};
const CHECK_CONV2D: bool = false; const CHECK_CONV2D: bool = false;

2
candle-pyo3/src/lib.rs
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@ -17,7 +17,7 @@ extern crate intel_mkl_src;
#[cfg(feature = "accelerate")] #[cfg(feature = "accelerate")]
extern crate accelerate_src; extern crate accelerate_src;
use ::candle::{quantized::QTensor, DType, Device, Tensor, WithDType}; use ::candle::{quantized::QTensor, DType, Device, Module, Tensor, WithDType};
mod utils; mod utils;
use utils::wrap_err; use utils::wrap_err;

2
candle-wasm-tests/tests/quantized_tests.rs
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@ -1,7 +1,7 @@
use candle::{ use candle::{
quantized::{self, k_quants, GgmlDType, GgmlType}, quantized::{self, k_quants, GgmlDType, GgmlType},
test_utils::to_vec2_round, test_utils::to_vec2_round,
Device, Result, Tensor, Device, Module, Result, Tensor,
}; };
use wasm_bindgen_test::*; use wasm_bindgen_test::*;