boostr 0.1.0

ML framework built on numr - attention, quantization, model architectures
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86

//! WebGPU implementation of FusedQkvOps
//!
//! Delegates to impl_generic (composed from numr primitives).
//! F32 only (WebGPU limitation).

use crate::error::Result;
use crate::ops::impl_generic::attention::fused_qkv::{
    fused_output_projection_residual_bwd_impl, fused_output_projection_residual_impl,
    fused_qkv_projection_bwd_impl, fused_qkv_projection_impl,
};
use crate::ops::traits::attention::fused_qkv::FusedQkvOps;
use numr::runtime::wgpu::{WgpuClient, WgpuRuntime};
use numr::tensor::Tensor;

impl FusedQkvOps<WgpuRuntime> for WgpuClient {
    fn fused_qkv_projection(
        &self,
        input: &Tensor<WgpuRuntime>,
        weight: &Tensor<WgpuRuntime>,
        bias: Option<&Tensor<WgpuRuntime>>,
        num_heads: usize,
        num_kv_heads: usize,
        head_dim: usize,
    ) -> Result<(
        Tensor<WgpuRuntime>,
        Tensor<WgpuRuntime>,
        Tensor<WgpuRuntime>,
    )> {
        fused_qkv_projection_impl(self, input, weight, bias, num_heads, num_kv_heads, head_dim)
    }

    fn fused_output_projection_residual(
        &self,
        attn_out: &Tensor<WgpuRuntime>,
        weight: &Tensor<WgpuRuntime>,
        bias: Option<&Tensor<WgpuRuntime>>,
        residual: &Tensor<WgpuRuntime>,
    ) -> Result<Tensor<WgpuRuntime>> {
        fused_output_projection_residual_impl(self, attn_out, weight, bias, residual)
    }

    fn fused_qkv_projection_bwd(
        &self,
        dq: &Tensor<WgpuRuntime>,
        dk: &Tensor<WgpuRuntime>,
        dv: &Tensor<WgpuRuntime>,
        input: &Tensor<WgpuRuntime>,
        weight: &Tensor<WgpuRuntime>,
        has_bias: bool,
        num_heads: usize,
        num_kv_heads: usize,
        head_dim: usize,
    ) -> Result<(
        Tensor<WgpuRuntime>,
        Tensor<WgpuRuntime>,
        Option<Tensor<WgpuRuntime>>,
    )> {
        fused_qkv_projection_bwd_impl(
            self,
            dq,
            dk,
            dv,
            input,
            weight,
            has_bias,
            num_heads,
            num_kv_heads,
            head_dim,
        )
    }

    fn fused_output_projection_residual_bwd(
        &self,
        d_output: &Tensor<WgpuRuntime>,
        attn_out: &Tensor<WgpuRuntime>,
        weight: &Tensor<WgpuRuntime>,
        has_bias: bool,
    ) -> Result<(
        Tensor<WgpuRuntime>,
        Tensor<WgpuRuntime>,
        Option<Tensor<WgpuRuntime>>,
        Tensor<WgpuRuntime>,
    )> {
        fused_output_projection_residual_bwd_impl(self, d_output, attn_out, weight, has_bias)
    }
}