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ktransformers/website/src/router/index.ts 0 → 100644
View file @ 18c42e67
import { createRouter, createWebHashHistory, RouteRecordRaw, createWebHistory } from 'vue-router'
import HomeView from '@/views/home.vue'
const routes: Array<RouteRecordRaw> = [
{
path: '/',
name: 'home',
component: HomeView,
redirect: '/chat',
children: [{
path: '/chat',
name: '',
component: () => import(/* webpackChunkName: "about" */ '../components/chat/index.vue')
},]
},
]
const router = createRouter({
history: createWebHashHistory(),
routes
})
export default router
ktransformers/website/src/shims-vue.d.ts 0 → 100644
View file @ 18c42e67
/* eslint-disable */
declare module '*.vue' {
import type { DefineComponent } from 'vue'
const component: DefineComponent<{}, {}, any>
export default component
}
declare module '@/locals'
declare module 'pdfobject';
ktransformers/website/src/store/index.ts 0 → 100644
View file @ 18c42e67
import { createStore } from 'vuex'
export default createStore({
state: {
},
getters: {
},
mutations: {
},
actions: {
},
modules: {
}
})
ktransformers/website/src/utils/copy.ts 0 → 100644
View file @ 18c42e67
import { ElMessage } from "element-plus";
const copy = (value: string) => {
//Try using the navigator.clipboard.writeText method
if (navigator.clipboard && window.isSecureContext) {
navigator.clipboard.writeText(value)
.then(() => {
//Using ElMessage to Display Success Messages in Windows Systems
if (navigator.appVersion.includes("Win")) {
ElMessage({
message: "内容复制成功!",
type: "success",
plain: true,
});
} else {
//Using custom DOM elements to display success messages in macOS system
showCopySuccessMessage();
}
})
.catch(() => {
//Using ElMessage to Display Failure Messages in Windows Systems
if (navigator.appVersion.includes("Win")) {
ElMessage({
message: "内容复制失败!",
type: "error",
plain: true,
});
} else {
//Using custom DOM elements to display failure messages in macOS system
showCopyErrorMessage();
}
});
} else {
const textarea = document.createElement("textarea");
textarea.value = value;
document.body.appendChild(textarea);
textarea.select();
try {
const successful = document.execCommand('copy');
if (successful) {
if (navigator.appVersion.includes("Win")) {
ElMessage({
message: "内容复制成功!",
type: "success",
plain: true,
});
} else {
showCopySuccessMessage();
}
} else {
if (navigator.appVersion.includes("Win")) {
ElMessage({
message: "内容复制失败!",
type: "error",
plain: true,
});
} else {
showCopyErrorMessage();
}
}
} catch (err) {
if (navigator.appVersion.includes("Win")) {
ElMessage({
message: "内容复制失败!",
type: "error",
plain: true,
});
} else {
showCopyErrorMessage();
}
}
document.body.removeChild(textarea);
}
};
function showCopySuccessMessage() {
const messageElement = document.createElement('div');
messageElement.textContent = '内容复制成功!';
messageElement.style.position = 'fixed';
messageElement.style.bottom = '10px';
messageElement.style.left = '50%';
messageElement.style.transform = 'translateX(-50%)';
messageElement.style.padding = '10px';
messageElement.style.backgroundColor = '#4CAF50';
messageElement.style.color = 'white';
messageElement.style.borderRadius = '15px';
messageElement.style.zIndex = '1000';
document.body.appendChild(messageElement);
setTimeout(() => {
document.body.removeChild(messageElement);
}, 3000);
}
function showCopyErrorMessage() {
const messageElement = document.createElement('div');
messageElement.textContent = '内容复制失败!';
messageElement.style.position = 'fixed';
messageElement.style.bottom = '10px';
messageElement.style.left = '50%';
messageElement.style.transform = 'translateX(-50%)';
messageElement.style.padding = '10px';
messageElement.style.backgroundColor = '#F44336';
messageElement.style.color = 'white';
messageElement.style.borderRadius = '5px';
messageElement.style.zIndex = '1000';
document.body.appendChild(messageElement);
setTimeout(() => {
document.body.removeChild(messageElement);
}, 3000);
}
export default copy;
\ No newline at end of file
ktransformers/website/src/utils/types.ts 0 → 100644
View file @ 18c42e67
export interface IAssistant {
id: string;
object: string;
created_at: number;
name?: string;
description?: string;
model: string;
instructions?: string;
tools: any[];
tool_resources?: object;
metadata?:{[key:string]:any}
top_p?: number;
temperature?: number;
response_format: string | object;
}
export interface IAssistantWithStatus {
build_status:{status:string}
id: string;
object: string;
created_at: number;
name?: string;
description?: string;
model: string;
instructions?: string;
tools: any[];
tool_resources?: object;
metadata?:{[key:string]:any}
top_p?: number;
temperature?: number;
response_format: string | object;
}
export interface IMessage {
id: string;
object: string;
created_at: number;
thread_id: string;
status: string;
incomplete_details?: object;
completed_at?: number;
incomplete_at?: number;
role: string;
content: any[];
assistant_id?: string;
run_id?: string;
attachments?: any[];
metadata:{[key:string]:any}
}
export interface IThread {
id: string;
object: string;
created_at: number;
tool_resources?: object;
metadata?:{[key:string]:any}
}
export interface IRun {
id: string;
object: string;
created_at: number;
thread_id: string,
assistant_id: string,
status: string,
required_action?: object,
last_error?: object,
expires_at?: number,
started_at?: number,
cancelled_at?: number,
failed_at?: number,
completed_at?: number,
incomplete_details?: object,
model: string,
instructions: string,
tools: any[],
metadata: Map<string, string>,
usage?: object,
temperature?: number,
top_p?: number,
max_prompt_tokens?: number,
max_completion_tokens?: number,
truncation_strategy: object,
tool_choice: string | object,
response_format: string | object,
}
export interface IFile {
id: string,
bytes: number,
created_at: number,
filename: string,
object: string,
purpose: string,
}
export interface IMessageData {
role: string;
content: any[];
created_at?: number;
assistant_id?: string,
}
export interface IThreadAndMessageAndAssistant {
thread: IThread;
first_message: IMessage;
assistant: IAssistantWithStatus
}
export interface IDeleteResult {
id: string;
object: string;
deleted: boolean;
}
export interface IBuildData {
parsed_file_count:number;
total_file_count:number;
prefilling_current:number;
prefilling_total:number;
build_completed_time:number;
build_started_time:number;
storage_total:number;
storage_usage:number;
status:string
}
\ No newline at end of file
ktransformers/website/src/views/home.vue 0 → 100644
View file @ 18c42e67
<template>
<div class="home flex-row">
<nav class="left-panel flex-column">
<div class="logo-box">
<div class="logo flex-row">
<img class="img" src="../../public/images/three.png" />
<span class="text">{{ projectName }}</span>
</div>
<div class="version">{{ projectVersion }}</div>
</div>
<div class="divider"></div>
<div class="assistant-box">
<div class="assistant-list">
<ul>
<li
class="assistant-item flex-row"
v-for="(item, index) in assistantList"
:key="index"
@click="setActiveAssistant(item)"
>
<img src="../../public/images/avatar.png" />
<span class="name flex-unit">{{ item.name }}</span>
<i class="iconfont icon-edit"></i>
</li>
</ul>
</div>
</div>
<div class="divider"></div>
<!-- History area -->
<div class="history-box flex-unit">
<div class="">
<div class="date">{{ $t("home.today") }}</div>
<ul>
<li
v-for="(item, index) in todayThreads"
:key="index"
class="chat-item"
:class="{ active: activeThreadIndex === index }"
@click="setActiveThreadIndex(index)"
>
<div class="chat-abbr">
{{ firstMessages[index] }}
</div>
<div class="chat-ops flex-row">
<img src="../../public/images/avatar.png" />
<div class="name flex-unit">
{{ assistantOfThread[index].name || "" }}
</div>
<i class="iconfont icon-delete" @click="delThread(index)"></i>
</div>
</li>
</ul>
<div class="date" v-if="previousThreads.length > 0">
{{ $t("home.previous") }}
</div>
<ul>
<li
v-for="(item, index) in previousThreads"
:key="index"
class="chat-item"
:class="{
active: activeThreadIndex === index + todayThreads.length,
}"
@click="setActiveThreadIndex(index + todayThreads.length)"
>
<div class="chat-abbr">
{{ firstMessages[index + todayThreads.length] }}
</div>
<div class="chat-ops flex-row">
<img src="../../public/images/avatar.png" />
<div class="name flex-unit">
{{
assistantOfThread[index + todayThreads.length].name || ""
}}
</div>
<i
class="iconfont icon-delete"
@click="delThread(index + todayThreads.length)"
></i>
</div>
</li>
</ul>
</div>
</div>
<div class="icon-box example-2">
<div class="iconhub icon-content" @click="navigateToIconHub">
<svg
xmlns="http://www.w3.org/2000/svg"
width="16"
height="16"
fill="currentColor"
class="bi bi-github"
viewBox="0 0 16 16"
xml:space="preserve"
>
<path
d="M8 0C3.58 0 0 3.58 0 8c0 3.54 2.29 6.53 5.47 7.59.4.07.55-.17.55-.38 0-.19-.01-.82-.01-1.49-2.01.37-2.53-.49-2.69-.94-.09-.23-.48-.94-.82-1.13-.28-.15-.68-.52-.01-.53.63-.01 1.08.58 1.23.82.72 1.21 1.87.87 2.33.66.07-.52.28-.87.51-1.07-1.78-.2-3.64-.89-3.64-3.95 0-.87.31-1.59.82-2.15-.08-.2-.36-1.02.08-2.12 0 0 .67-.21 2.2.82.64-.18 1.32-.27 2-.27s1.36.09 2 .27c1.53-1.04 2.2-.82 2.2-.82.44 1.1.16 1.92.08 2.12.51.56.82 1.27.82 2.15 0 3.07-1.87 3.75-3.65 3.95.29.25.54.73.54 1.48 0 1.07-.01 1.93-.01 2.2 0 .21.15.46.55.38A8.01 8.01 0 0 0 16 8c0-4.42-3.58-8-8-8"
fill="currentColor"
></path>
</svg>
<div class="tooltip">GitHub</div>
</div>
<div class="iconlanguage" @click="changeLanguage">
<svg
v-if="!flag"
t="1719306572024"
class="icon"
viewBox="0 0 1024 1024"
version="1.1"
xmlns="http://www.w3.org/2000/svg"
p-id="16849"
data-spm-anchor-id="a313x.search_index.0.i21.366e3a81tz0TYS"
width="18"
height="18"
>
<path
d="M64.064 768V192H448.64v64H127.936v192h320v64h-320v192h320v64H64.064z m511.872 0V192h64l256 447.68V192h64v576h-64l-256-447.168V768h-64z"
p-id="16850"
data-spm-anchor-id="a313x.search_index.0.i22.366e3a81tz0TYS"
class="selected"
fill="#000000"
></path>
</svg>
<svg
v-else
t="1719306494614"
class="icon"
viewBox="0 0 1024 1024"
version="1.1"
xmlns="http://www.w3.org/2000/svg"
p-id="12325"
width="18"
height="18"
>
<path
d="M1023.488 831.552h-96l-265.472-451.904c-8.96-12.8-16-25.344-21.44-37.888H638.08c2.176 12.992 3.2 40.128 3.2 81.408v408.32L576 836.928V256h101.568l257.024 445.632c14.592 20.992 23.232 34.368 25.92 40.128h1.6c-2.688-16.512-4.032-44.8-4.032-84.736v-399.36L1024 256l-0.512 575.552zM435.008 804.224c-42.752 21.76-96.384 32.64-160.896 32.64-83.2 0-149.76-25.6-199.488-76.736C24.896 708.928 0 641.344 0 557.12c0-90.432 27.968-163.2 84.032-218.368C140.032 283.52 211.072 256 297.344 256c55.552 0 101.376 7.616 137.6 22.848v75.84a284.992 284.992 0 0 0-136.832-33.408c-64.768 0-117.504 20.864-158.208 62.592-40.768 41.728-61.184 98.048-61.184 168.96 0 67.2 19.008 120.576 57.024 160.128 38.016 39.552 87.744 59.328 149.248 59.328 57.536 0 107.52-12.544 150.016-37.76v69.696z"
fill="#000000"
p-id="12326"
data-spm-anchor-id="a313x.search_index.0.i16.366e3a81tz0TYS"
class="selected"
></path>
</svg>
</div>
</div>
</nav>
<router-view v-slot="{ Component }" class="main-panel flex-unit">
<component
:is="Component"
:chatInit="chatInit"
:activeAssistant="activeAssistant"
:activeThread="activeThread"
:messages="allMessageInCurrentThread"
:completedAssistant="assistantList"
:inputDisabled="inputDisabled"
@updateAssistant="handleUpdateAssistant"
/>
</router-view>
</div>
</template>
<script lang="ts">
import { defineComponent, ref, onMounted, computed, nextTick } from "vue";
import {
IThread,
IAssistant,
IMessageData,
IThreadAndMessageAndAssistant,
IAssistantWithStatus,
} from "@/utils/types";
import { listThreads, deleteThread, getThread } from "@/api/thread";
import { ElMessage, ElMessageBox } from "element-plus";
import { listAssistants } from "@/api/assistant";
import { listMessages } from "@/api/message";
import { useRouter } from "vue-router";
import BScroll from "better-scroll";
import { useI18n } from "vue-i18n";
export default defineComponent({
name: "HomeView",
setup() {
const assistantList = ref<IAssistant[]>([]);
const threadsList = ref<IThread[]>([]);
const firstMessages = ref<string[]>([]);
const activeAssistant = ref({} as IAssistant);
const assistantOfThread = ref<IAssistantWithStatus[]>([]);
const threadAndMessages = ref<IThreadAndMessageAndAssistant[]>([]);
const assistantScroll = ref<BScroll | null>(null);
const historyScroll = ref<BScroll | null>(null);
const router = useRouter();
const { t, locale } = useI18n();
const flag = ref(true);
const changeLanguage = () => {
if (flag.value) {
locale.value = "zh";
localStorage.setItem("lang", "zh");
flag.value = false;
} else {
locale.value = "en";
flag.value = true;
localStorage.setItem("lang", "en");
}
};
// Initialize data
const initData = async () => {
try {
threadsList.value = [];
firstMessages.value = [];
assistantOfThread.value = [];
const assistantsRes = await listAssistants();
if (assistantsRes && assistantsRes.length > 0) {
assistantList.value = assistantsRes;
activeAssistant.value = assistantsRes[0];
}
const threadsRes = await listThreads(100);
if (threadsRes) {
threadAndMessages.value = threadsRes;
for (let t of threadsRes) {
if (t.thread && !t.thread.metadata?.hidden) {
threadsList.value.push(t.thread);
if (
t.first_message &&
t.first_message.content &&
t.first_message.content.length > 0
) {
firstMessages.value.push(t.first_message.content[0].text.value);
} else {
firstMessages.value.push("no message yet");
}
assistantOfThread.value.push(
t.assistant || ({} as IAssistantWithStatus)
);
}
}
}
assistantScroll.value = new BScroll(".assistant-list", {
click: true,
mouseWheel: true,
scrollbar: {
fade: true,
interactive: true,
},
});
historyScroll.value = new BScroll(".history-box", {
click: true,
mouseWheel: true,
scrollbar: {
fade: true,
interactive: true,
},
});
} catch (err) {
console.error("Failed to initialize data:", err);
}
};
const navigateToIconHub = () => {
window.open("https://github.com/kvcache-ai/Lexllama");
};
const isEmptyObject = (obj: object): boolean => {
//Determine if the object is empty
return Object.keys(obj).length === 0;
};
//Jump route
const navigateToExplore = () => {
router.push("/explore");
};
const navigatorToChat = () => {
router.push("/chat");
};
// Calculate date
const todayThreads = computed(() => {
const today = Math.floor(Date.now() / 1000);
return threadsList.value.filter((thread) => {
return today - thread.created_at <= 86400;
});
});
const previousThreads = computed(() => {
const today = Math.floor(Date.now() / 1000);
return threadsList.value.filter((thread) => {
return today - thread.created_at > 86400;
});
});
onMounted(async () => {
initData();
});
return {
t,
flag,
assistantList,
isEmptyObject,
activeAssistant,
navigateToExplore,
navigatorToChat,
threadsList,
firstMessages,
navigateToIconHub,
assistantScroll,
historyScroll,
assistantOfThread,
changeLanguage,
initData,
todayThreads,
previousThreads,
};
},
data() {
return {
projectName: "KTransformers",
projectVersion: "v0.01",
activeThreadIndex: -1,
chatInit: true,
activeThread: {} as IThread,
allMessageInCurrentThread: [] as IMessageData[],
inputDisabled: false,
isSettingActiveThread: false,
isDeletingThread: false,
threadAndMessages: <IThreadAndMessageAndAssistant[]>[],
};
},
methods: {
setActiveAssistant(assistant: IAssistant) {
this.chatInit = true;
this.inputDisabled = false;
this.activeThreadIndex = -1;
this.activeAssistant = assistant;
this.activeThread = {} as IThread;
this.allMessageInCurrentThread = [];
if (this.$route.path != "/chat") {
this.navigatorToChat();
}
},
async setActiveThreadIndex(index: number) {
//If setting up an active thread, return directly
if (this.isSettingActiveThread) {
return;
}
this.isSettingActiveThread = true;
this.activeThreadIndex = index;
this.chatInit = false;
this.inputDisabled = false;
this.activeAssistant = {} as IAssistant;
this.activeThread = this.threadsList[index];
//If the assistant of the current thread is an empty object
if (this.isEmptyObject(this.assistantOfThread[index])) {
ElMessage({
message: this.t("home.withoutAssistantTip"),
type: "warning",
});
this.inputDisabled = true;
}
try {
//Call asynchronous function to obtain the message list of the current thread
const res = await listMessages(this.activeThread.id, 100, "asc");
//Convert the obtained message list to the specified format and assign values to all messages of the current thread
this.allMessageInCurrentThread = res.map((m) => ({
role: m.role,
content: m.content,
assistant_id: m.assistant_id,
created_at: m.created_at,
}));
} catch (err) {
console.log(err);
} finally {
this.isSettingActiveThread = false;
}
if (this.$route.path != "/chat") {
this.navigatorToChat();
}
},
async delThread(index: number) {
// If the thread is currently being deleted, return directly
if (this.isDeletingThread) {
return;
}
this.isDeletingThread = true;
try {
//Pop up a confirmation box and ask the user if they are sure to delete the thread
await ElMessageBox.confirm(this.t("home.deleteThreadTip"), "Warning", {
confirmButtonText: "OK",
cancelButtonText: "Cancel",
type: "warning",
});
const res = await deleteThread(this.threadsList[index].id);
this.threadsList.splice(index, 1);
this.firstMessages.splice(index, 1);
this.assistantOfThread.splice(index, 1);
// Jump to the first assistant or other suitable page
this.setActiveAssistant(this.assistantList[0]);
ElMessage({
type: "success",
message: "Delete completed",
});
} catch (err) {
// Specific error handling, such as logging or displaying specific error messages to users
console.error("Delete session failed:", err);
ElMessage({
type: "error",
message: `Delete failed`, // Display specific error messages
});
} finally {
this.isDeletingThread = false; //Ensure that the delete thread flag is reset no matter what
}
},
// Handles the update of the assistant asynchronously.
async handleUpdateAssistant(value: any) {
await this.initData();
if (this.activeThreadIndex != -1) {
this.setActiveThreadIndex(this.activeThreadIndex);
} else if (this.activeAssistant.id) {
this.setActiveThreadIndex(0);
} else {
this.setActiveAssistant(this.assistantList[0]);
}
},
},
});
</script>
<style lang="stylus" rel="stylesheet/stylus" scoped>
@import '../assets/css/mixins.styl';
.home {
width: 100%;
height: 100%;
position: relative;
}
.left-panel {
width: 320px;
height: 100%;
background-color: #363433;
padding: 30px 30px;
.logo-box {
.logo {
.img {
width: 36px;
height: 36px;
}
.text {
font-size: 28px;
font-weight: bold;
margin-left: 10px;
color: #edf2ea;
}
}
.version {
text-align: right;
font-size: 14px;
color: #bdbdbd;
}
}
.divider {
border-bottom: 1px solid #D7D7D7;
width: 30%;
margin: 30px auto;
}
.lang-box {
position: relative;
width: 100%;
height: 30px;
margin: auto;
margin-bottom: 10px;
.el-dropdown {
font-size: 14px;
position: absolute;
top: 50%;
left: 50%;
transform: translate(-50%, -50%);
}
}
.assistant-box {
.assistant-list {
min-height: 50px;
max-height: 300px;
overflow: hidden;
position: relative;
ul > li.assistant-item {
padding: 8px 15px;
color: #edf2ea;
img {
width: 32px;
height: 32px;
}
.name {
margin-left: 12px;
font-size: 14px;
color: #edf2ea;
}
i.iconfont {
display: none;
margin-left: 10px;
}
&:hover {
background-color: $bg_gray_light_hover;
cursor: pointer;
border-radius: 4px;
.name {
color: #313433;
}
i.iconfont {
display: block;
}
}
}
}
.explore {
position: relative;
justify-content: center;
display: flex;
margin-top: 10px;
.explore-btn {
margin: 0 auto;
padding: 0 20px;
justify-content: center;
height: 32px;
line-height: 32px;
background-color: #FFFFFF;
border: 1px solid RGBA(0, 0, 0, 0.15);
border-radius: 16px;
i {
color: #8080FF;
}
.text {
color: #7F7F7F;
margin-left: 4px;
}
&:hover {
background-color: #FAFAFA;
cursor: pointer;
}
}
}
}
.history-box {
position: relative;
.date {
font-size: 14px;
color: #7F7F7F;
margin: 8px 0;
&:first-child {
margin-top: 0;
}
}
li.chat-item {
padding: 12px 15px;
cursor: pointer;
background-color: #edf2ea;
border-radius: 4px;
margin-bottom: 10px;
font-size: 16px;
.chat-abbr {
font-size: 14px;
color: #313433;
white-space: nowrap;
overflow: hidden;
text-overflow: ellipsis;
}
.chat-ops {
display: flex;
margin-top: 5px;
img {
width: 16px;
height: 16px;
}
.name {
font-size: 12px;
color: #898989;
margin-left: 8px;
}
i.iconfont {
color: $gray_60;
}
}
&:hover, &.active {
transition: 0.3s all;
cursor: pointer;
background-color: #a2a79f;
.chat-abbr {
color: black;
}
.name, i.iconfont {
color: black;
}
}
}
}
.icon-box {
width: 100%;
display: flex;
flex-direction: row;
justify-content: flex-end;
align-items: center;
.iconhub {
width: 32px;
height: 24px;
background: white;
font-size: 30px;
border: none;
ovferflow: hidden;
border-radius: 15%;
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
color: #898989;
transition: all 0.5s;
cursor: pointer;
}
.iconhub:hover {
background: #e5e5e5;
text-decoration: none;
}
.iconlanguage {
margin-left: 15px;
width: 32px;
height: 24px;
background: white;
font-size: 30px;
border: none;
ovferflow: hidden;
border-radius: 15%;
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
color: #898989;
transition: all 0.5s;
cursor: pointer;
}
.iconlanguage:hover {
background: #e5e5e5;
text-decoration: none;
}
}
}
ul {
list-style: none;
}
.example-2 {
display: flex;
justify-content: center;
align-items: center;
}
.example-2 .icon-content {
margin: 0 10px;
position: relative;
}
.example-2 .icon-content .tooltip {
position: absolute;
top: -30px;
left: 50%;
transform: translateX(-50%);
color: #fff;
padding: 6px 10px;
border-radius: 5px;
opacity: 0;
visibility: hidden;
font-size: 14px;
transition: all 0.3s ease;
}
.example-2 .icon-content:hover .tooltip {
opacity: 1;
visibility: visible;
top: -50px;
}
.main-panel {
height: 100%;
background-color: #f1f0ed;
}
</style>
ktransformers/website/tests/unit/example.spec.ts 0 → 100644
View file @ 18c42e67
import { shallowMount } from '@vue/test-utils'
import HelloWorld from '@/components/HelloWorld.vue'
describe('HelloWorld.vue', () => {
it('renders props.msg when passed', () => {
const msg = 'new message'
const wrapper = shallowMount(HelloWorld, {
props: { msg }
})
expect(wrapper.text()).toMatch(msg)
})
})
ktransformers/website/tsconfig.json 0 → 100644
View file @ 18c42e67
{
"compilerOptions": {
"target": "es5",
"module": "esnext",
"strict": true,
"jsx": "preserve",
"importHelpers": true,
"moduleResolution": "node",
"skipLibCheck": true,
"esModuleInterop": true,
"allowSyntheticDefaultImports": true,
"forceConsistentCasingInFileNames": true,
"useDefineForClassFields": true,
"sourceMap": true,
"allowJs": true,
"baseUrl": ".",
"types": [
"webpack-env",
"jest"
],
"paths": {
"@/*": [
"src/*"
]
},
"lib": [
"esnext",
"dom",
"dom.iterable",
"scripthost"
]
},
"include": [
"src/**/*.ts",
"src/**/*.tsx",
"src/**/*.vue",
"tests/**/*.ts",
"tests/**/*.tsx",
"config.d.ts"
],
"exclude": [
"node_modules"
]
}
\ No newline at end of file
ktransformers/website/vue.config.js 0 → 100644
View file @ 18c42e67
module.exports = {
// 配置 webpack-dev-server 行为。
devServer: {
open: false, // 编译后默认打开浏览器
host: '0.0.0.0', // 域名
port: 8082, // 端口
https: false, // 是否https
proxy: {
'/api': {
target: 'http://localhost:9016/v1', // 你的后端服务器地址
changeOrigin: true, // 是否允许跨域
pathRewrite: {
'/api': '' // 将 '/api' 前缀替换为空，如果你的后端不需要这个前缀
}
}
}
},
publicPath: '/web/', // 基本路径
outputDir: 'dist', // 构建时的输出目录
assetsDir: 'static', // 放置静态资源的目录
indexPath: 'index.html', // html 的输出路径
filenameHashing: true, // 文件名哈希值
lintOnSave: false, // 是否在保存的时候使用 `eslint-loader` 进行检查。
// 组件是如何被渲染到页面中的？ （ast：抽象语法树；vDom：虚拟DOM）
// template ---> ast ---> render ---> vDom ---> 真实的Dom ---> 页面
// runtime-only：将template在打包的时候，就已经编译为render函数
// runtime-compiler：在运行的时候才去编译template
runtimeCompiler: false,
transpileDependencies: [], // babel-loader 默认会跳过 node_modules 依赖。
productionSourceMap: false, // 是否为生产环境构建生成 source map
//调整内部的 webpack 配置
configureWebpack: () => {},
chainWebpack: () => {},
}
\ No newline at end of file
pyproject.toml 0 → 100644
View file @ 18c42e67
[build-system]
requires = [
"setuptools",
"torch == 2.3.1",
"ninja",
"packaging"
]
build-backend = "setuptools.build_meta"
requirements-local_chat.txt 0 → 100644
View file @ 18c42e67
fire
transformers
numpy
torch>=2.3.0
packaging
setup.py 0 → 100644
View file @ 18c42e67
#!/usr/bin/env python
# coding=utf-8
'''
Description :
Author : chenxl
Date : 2024-07-12 07:25:42
Version : 1.0.0
LastEditors : chenxl
LastEditTime : 2024-07-27 04:31:03
'''
import os
import shutil
import sys
import re
import ast
import subprocess
import platform
import io
from pathlib import Path
from packaging.version import parse
import torch.version
from wheel.bdist_wheel import bdist_wheel as _bdist_wheel
from setuptools import setup, Extension
import torch
from torch.utils.cpp_extension import BuildExtension, CUDAExtension, CUDA_HOME
ROOT_DIR = os.path.dirname(__file__)
class VersionInfo:
THIS_DIR = os.path.dirname(os.path.abspath(__file__))
PACKAGE_NAME = "ktransformers"
def get_cuda_bare_metal_version(self, cuda_dir):
raw_output = subprocess.check_output([cuda_dir + "/bin/nvcc", "-V"], universal_newlines=True)
output = raw_output.split()
release_idx = output.index("release") + 1
bare_metal_version = parse(output[release_idx].split(",")[0])
cuda_version = f"{bare_metal_version.major}{bare_metal_version.minor}"
return cuda_version
def get_cuda_version_of_torch(self,):
torch_cuda_version = parse(torch.version.cuda)
cuda_version = f"{torch_cuda_version.major}{torch_cuda_version.minor}"
return cuda_version
def get_platform(self,):
"""
Returns the platform name as used in wheel filenames.
"""
if sys.platform.startswith("linux"):
return f'linux_{platform.uname().machine}'
else:
raise ValueError("Unsupported platform: {}".format(sys.platform))
def get_cpu_instruct(self,):
if sys.platform.startswith("linux"):
with open('/proc/cpuinfo', 'r') as cpu_f:
cpuinfo = cpu_f.read()
flags_line = [line for line in cpuinfo.split('\n') if line.startswith('flags')][0]
flags = flags_line.split(':')[1].strip().split(' ')
for flag in flags:
if 'avx512' in flag:
return 'avx512'
for flag in flags:
if 'avx2' in flag:
return 'avx2'
raise ValueError("Unsupported cpu Instructions: {}".format(flags_line))
def get_torch_version(self,):
torch_version_raw = parse(torch.__version__)
torch_version = f"{torch_version_raw.major}{torch_version_raw.minor}"
return torch_version
def get_package_version(self,):
version_file = os.path.join(Path(VersionInfo.THIS_DIR), VersionInfo.PACKAGE_NAME, "__init__.py")
with open(version_file, "r", encoding="utf-8") as f:
version_match = re.search(r"^__version__\s*=\s*(.*)$", f.read(), re.MULTILINE)
public_version = ast.literal_eval(version_match.group(1))
package_version = f"{str(public_version)}+cu{self.get_cuda_bare_metal_version(CUDA_HOME)}torch{self.get_torch_version()}{self.get_cpu_instruct()}"
return package_version
class BuildWheelsCommand(_bdist_wheel):
def get_wheel_name(self,):
version_info = VersionInfo()
python_version = f"cp{sys.version_info.major}{sys.version_info.minor}"
wheel_filename = f"{VersionInfo.PACKAGE_NAME}-{version_info.get_package_version()}-{python_version}-{python_version}-{version_info.get_platform()}.whl"
return wheel_filename
def run(self):
super().run()
impl_tag, abi_tag, plat_tag = self.get_tag()
archive_basename = f"{self.wheel_dist_name}-{impl_tag}-{abi_tag}-{plat_tag}"
wheel_path = os.path.join(self.dist_dir, archive_basename + ".whl")
wheel_name_with_platform = os.path.join(self.dist_dir, self.get_wheel_name())
os.rename(wheel_path, wheel_name_with_platform)
# Convert distutils Windows platform specifiers to CMake -A arguments
PLAT_TO_CMAKE = {
"win32": "Win32",
"win-amd64": "x64",
"win-arm32": "ARM",
"win-arm64": "ARM64",
}
class CopyExtension(Extension):
def __init__(self, name: str, sourcedir: str = "", copy_file_source="") -> None:
super().__init__(name, sources=[])
self.sourcedir = os.fspath(Path(sourcedir).resolve())
self.source_file = copy_file_source
class CMakeExtension(Extension):
def __init__(self, name: str, sourcedir: str = "") -> None:
super().__init__(name, sources=[])
self.sourcedir = os.fspath(Path(sourcedir).resolve() / "ktransformers/ktransformers_ext")
class CMakeBuild(BuildExtension):
def build_extension(self, ext) -> None:
if isinstance(ext, CopyExtension):
ext_fullpath = Path.cwd() / self.get_ext_fullpath(ext.name)
extdir = ext_fullpath.parent.resolve()
shutil.copy(ext.source_file, extdir)
return
if not isinstance(ext, CMakeExtension):
super().build_extension(ext)
return
ext_fullpath = Path.cwd() / self.get_ext_fullpath(ext.name)
extdir = ext_fullpath.parent.resolve()
# Using this requires trailing slash for auto-detection & inclusion of
# auxiliary "native" libs
debug = int(os.environ.get("DEBUG", 0)) if self.debug is None else self.debug
cfg = "Debug" if debug else "Release"
# CMake lets you override the generator - we need to check this.
# Can be set with Conda-Build, for example.
cmake_generator = os.environ.get("CMAKE_GENERATOR", "")
# Set Python_EXECUTABLE instead if you use PYBIND11_FINDPYTHON
# EXAMPLE_VERSION_INFO shows you how to pass a value into the C++ code
# from Python.
cmake_args = [
f"-DCMAKE_LIBRARY_OUTPUT_DIRECTORY={extdir}{os.sep}",
f"-DPYTHON_EXECUTABLE={sys.executable}",
f"-DCMAKE_BUILD_TYPE={cfg}", # not used on MSVC, but no harm
]
build_args = []
if "CMAKE_ARGS" in os.environ:
cmake_args += [item for item in os.environ["CMAKE_ARGS"].split(" ") if item]
# In this example, we pass in the version to C++. You might not need to.
cmake_args += [f"-DEXAMPLE_VERSION_INFO={self.distribution.get_version()}"]
if self.compiler.compiler_type != "msvc":
if not cmake_generator or cmake_generator == "Ninja":
try:
import ninja
ninja_executable_path = Path(ninja.BIN_DIR) / "ninja"
cmake_args += [
"-GNinja",
f"-DCMAKE_MAKE_PROGRAM:FILEPATH={ninja_executable_path}",
]
except ImportError:
pass
else:
# Single config generators are handled "normally"
single_config = any(x in cmake_generator for x in {"NMake", "Ninja"})
# CMake allows an arch-in-generator style for backward compatibility
contains_arch = any(x in cmake_generator for x in {"ARM", "Win64"})
if not single_config and not contains_arch:
cmake_args += ["-A", PLAT_TO_CMAKE[self.plat_name]]
# Multi-config generators have a different way to specify configs
if not single_config:
cmake_args += [
f"-DCMAKE_LIBRARY_OUTPUT_DIRECTORY_{cfg.upper()}={extdir}"
]
build_args += ["--config", cfg]
if sys.platform.startswith("darwin"):
# Cross-compile support for macOS - respect ARCHFLAGS if set
archs = re.findall(r"-arch (\S+)", os.environ.get("ARCHFLAGS", ""))
if archs:
cmake_args += ["-DCMAKE_OSX_ARCHITECTURES={}".format(";".join(archs))]
if "CMAKE_BUILD_PARALLEL_LEVEL" not in os.environ:
if hasattr(self, "parallel") and self.parallel:
build_args += [f"-j{self.parallel}"]
build_temp = Path(ext.sourcedir) / "build"
if not build_temp.exists():
build_temp.mkdir(parents=True)
subprocess.run(
["cmake", ext.sourcedir, *cmake_args], cwd=build_temp, check=True
)
subprocess.run(
["cmake", "--build", ".", *build_args], cwd=build_temp, check=True
)
def read_readme() -> str:
p = os.path.join(ROOT_DIR, "README.md")
if os.path.isfile(p):
return io.open(p, "r", encoding="utf-8").read()
else:
return ""
setup(
name="ktransformers",
version=VersionInfo().get_package_version(),
author="KVCache.ai",
license="Apache 2.0",
description = "KTransformers, pronounced as Quick Transformers, is designed to enhance your Transformers experience with advanced kernel optimizations and placement/parallelism strategies.",
long_description=read_readme(),
long_description_content_type="text/markdown",
cmdclass={"build_ext": CMakeBuild},
install_requires = [
"torch >= 2.3.0",
"transformers == 4.43.2",
"fastapi >= 0.111.0",
"langchain >= 0.2.0",
"blessed >= 1.20.0",
"accelerate >= 0.31.0",
"sentencepiece >= 0.1.97",
"setuptools",
"ninja",
"wheel",
"colorlog",
"build",
"packaging",
"fire"
],
python_requires=">=3.10",
entry_points={
"console_scripts": [
"ktransformers=ktransformers.server.main:main",
],
},
packages=["ktransformers"],
include_package_data=True,
ext_modules=[
CUDAExtension('KTransformersOps', [
'ktransformers/ktransformers_ext/cuda/custom_gguf/dequant.cu',
'ktransformers/ktransformers_ext/cuda/binding.cpp',
'ktransformers/ktransformers_ext/cuda/gptq_marlin/gptq_marlin.cu',
]),
CMakeExtension("cpuinfer_ext")]
)
\ No newline at end of file
llama.cpp @ a94e6ff8
Subproject commit a94e6ff8774b7c9f950d9545baf0ce35e8d1ed2f
third_party/llamafile/README.md 0 → 100644
View file @ 18c42e67
The code in this folder is copied from [Mozilla-Ocho/llamafile](https://github.com/Mozilla-Ocho/llamafile). Special thanks to the Mozilla-Ocho team.
third_party/llamafile/bench.h 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/bench.h
// Copyrigth 2024 Mozilla Foundation.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;coding:utf-8 -*-
// vi: set et ft=cpp ts=4 sts=4 sw=4 fenc=utf-8 :vi
#pragma once
#include <stdio.h>
#include "micros.h"
#define BENCH(x) \
do { \
x; \
__asm__ volatile("" ::: "memory"); \
long long start = micros(); \
for (int i = 0; i < ITERATIONS; ++i) { \
__asm__ volatile("" ::: "memory"); \
x; \
__asm__ volatile("" ::: "memory"); \
} \
printf("%9lld us %s\n", (micros() - start + ITERATIONS - 1) / ITERATIONS, #x); \
} while (0)
third_party/llamafile/flags.cpp 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/flags.cpp
// Copyrigth 2024 Mozilla Foundation.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
#include "flags.h"
bool FLAG_precise = false;
third_party/llamafile/flags.h 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/flags.cpp
// Copyrigth 2024 Mozilla Foundation.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
#pragma once
extern bool FLAG_precise;
third_party/llamafile/iqk_mul_mat.inc 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/iqk_mul_mat.inc
// Copyrigth 2024 Iwan Kawrakow.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
// -*- mode:c++;indent-tabs-mode:nil;c-basic-offset:4;coding:utf-8 -*-
// vi: set et ft=cpp fenc=utf-8 :vi
//
// Copyright 2024 Iwan Kawrakow
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include <cstring>
#include <type_traits>
#if defined __x86_64__ || defined __aarch64__
#include "llama.cpp/ggml-impl.h"
#include "llama.cpp/ggml-quants.h"
#include "sgemm.h"
// For i-quants, I had to explicitely specify which
// functions to inline / not inline (at least for some
// of the functions), else performance would be significantly
// lower. This is worrysome as things can change with,
// e.g., a different compiler version or running on a different
// CPU.
#ifdef _MSC_VER
#define IQK_NOINLINE __declspec(noinline)
#define IQK_ALWAYS_INLINE inline
#else
#define IQK_NOINLINE __attribute__((__noinline__))
#define IQK_ALWAYS_INLINE __attribute__((always_inline))
#endif
#define GGML_COMMON_IMPL_C
#include "llama.cpp/ggml-common.h"
// clang-format off
// This matrix - vector and matrix - matrix multiplication implementation
// for legacy quants, k-quants and i-quants makes prompt processing 150-200%
// (legacy and k-quants) or 250-400% (i-quants) faster.
// compared to mainline llama.cpp (and llamafile).
// It provides implementations for ARM_NEON (all quants) and AVX2
// (all quants except sub-4 bit i-quants).
//
// Main idea is that unpacking the quants and the block scales to
// be ready for dot products with the corresponding Q8_Y quants
// takes time (here 'Y' stands for K, 0, or 1, depending on quantization type).
// Hence, if we are performing a QX x Q8_Y matrix matrix
// multiplication (as needed for prompt processing), we can get
// a significant speedup by reusing the unpacked QX quants and scales
// for multiplication with several Q8_K columns. We also achieve fewer
// loads from memory, which is the main purpose of tiling in general
// purpose matrix multiplication packages.
#include <utility>
#include <array>
#endif
namespace {
typedef struct {
int32_t i1;
int32_t i2;
} mmid_row_mapping;
struct DataInfo {
float * s;
const char * cy;
size_t bs;
size_t by;
int cur_y = 0;
int ne11;
const mmid_row_mapping * row_mapping = nullptr;
size_t bs2 = 0;
inline const char * src1_row(int iy) const {
if (!row_mapping) return cy + (cur_y + iy)*by;
int i11 = row_mapping[cur_y + iy].i1 % ne11;
int i12 = row_mapping[cur_y + iy].i2;
return cy + (i11 + i12*ne11)*by;
}
inline void store(int ix, int iy, float result) const {
*(dst_row(iy) + ix) = result;
//dst_row(iy)[ix] = result;
}
inline float * dst_row(int iy) const {
if (!row_mapping) return s + (cur_y + iy)*bs;
int i12 = row_mapping[cur_y + iy].i2;
int i1 = row_mapping[cur_y + iy].i1;
int i2 = i12;
return s + i1*bs + i2*bs2;
}
};
typedef void (*mul_mat_t)(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x);
struct MulMat {
std::array<mul_mat_t, 8> funcs = {};
//inline void mul_mat_NxM(int n, const void * vx, size_t bx, DataInfo& info, int nrc_x, int nrc_y) {
IQK_NOINLINE void mul_mat_NxM(int n, const void * vx, size_t bx, DataInfo& info, int nrc_x, int nrc_y) {
constexpr int k_x_step = 64; // This works best on my Ryzen-7950X and M2 Max CPUs (but differences to other tile size are small)
int n_step = (nrc_y - info.cur_y)/funcs.size();
if (n_step > 0) {
for (int ix = 0; ix < nrc_x; ix += k_x_step) {
auto this_info = info;
this_info.s += ix;
int this_nrc_x = ix + k_x_step <= nrc_x ? k_x_step : nrc_x - ix;
for (int iy = 0; iy < n_step; ++iy) {
funcs.back()(n, (const void *)((const char *)vx + ix*bx), bx, this_info, this_nrc_x);
this_info.cur_y += funcs.size();
}
}
info.cur_y += funcs.size() * n_step;
}
int n_left = nrc_y - info.cur_y;
if (n_left > 0) {
funcs[n_left-1](n, vx, bx, info, nrc_x);
}
}
static IQK_NOINLINE bool set_mul_mat(int typeA, int ne00, MulMat& mm, int& row_size_q8, int Ny);
private:
template <typename Dequantizer> static IQK_NOINLINE void set_functions(MulMat& m);
};
inline void make_q4_scales(const uint8_t * scales8, uint32_t * aux32) {
const uint16_t * scales = (const uint16_t *)scales8;
const uint32_t a0 = scales[0] | (scales[1] << 16);
const uint32_t a1 = scales[2] | (scales[3] << 16);
const uint32_t a2 = scales[4] | (scales[5] << 16);
aux32[3] = ((a2 >> 4) & 0x0f0f0f0f) | ((a1 >> 2) & 0x30303030);
aux32[1] = ((a2 >> 0) & 0x0f0f0f0f) | ((a0 >> 2) & 0x30303030);
aux32[2] = a1 & 0x3f3f3f3f;
aux32[0] = a0 & 0x3f3f3f3f;
}
const uint64_t keven_signs[128] = {
0x0101010101010101, 0xff010101010101ff, 0xff0101010101ff01, 0x010101010101ffff,
0xff01010101ff0101, 0x0101010101ff01ff, 0x0101010101ffff01, 0xff01010101ffffff,
0xff010101ff010101, 0x01010101ff0101ff, 0x01010101ff01ff01, 0xff010101ff01ffff,
0x01010101ffff0101, 0xff010101ffff01ff, 0xff010101ffffff01, 0x01010101ffffffff,
0xff0101ff01010101, 0x010101ff010101ff, 0x010101ff0101ff01, 0xff0101ff0101ffff,
0x010101ff01ff0101, 0xff0101ff01ff01ff, 0xff0101ff01ffff01, 0x010101ff01ffffff,
0x010101ffff010101, 0xff0101ffff0101ff, 0xff0101ffff01ff01, 0x010101ffff01ffff,
0xff0101ffffff0101, 0x010101ffffff01ff, 0x010101ffffffff01, 0xff0101ffffffffff,
0xff01ff0101010101, 0x0101ff01010101ff, 0x0101ff010101ff01, 0xff01ff010101ffff,
0x0101ff0101ff0101, 0xff01ff0101ff01ff, 0xff01ff0101ffff01, 0x0101ff0101ffffff,
0x0101ff01ff010101, 0xff01ff01ff0101ff, 0xff01ff01ff01ff01, 0x0101ff01ff01ffff,
0xff01ff01ffff0101, 0x0101ff01ffff01ff, 0x0101ff01ffffff01, 0xff01ff01ffffffff,
0x0101ffff01010101, 0xff01ffff010101ff, 0xff01ffff0101ff01, 0x0101ffff0101ffff,
0xff01ffff01ff0101, 0x0101ffff01ff01ff, 0x0101ffff01ffff01, 0xff01ffff01ffffff,
0xff01ffffff010101, 0x0101ffffff0101ff, 0x0101ffffff01ff01, 0xff01ffffff01ffff,
0x0101ffffffff0101, 0xff01ffffffff01ff, 0xff01ffffffffff01, 0x0101ffffffffffff,
0xffff010101010101, 0x01ff0101010101ff, 0x01ff01010101ff01, 0xffff01010101ffff,
0x01ff010101ff0101, 0xffff010101ff01ff, 0xffff010101ffff01, 0x01ff010101ffffff,
0x01ff0101ff010101, 0xffff0101ff0101ff, 0xffff0101ff01ff01, 0x01ff0101ff01ffff,
0xffff0101ffff0101, 0x01ff0101ffff01ff, 0x01ff0101ffffff01, 0xffff0101ffffffff,
0x01ff01ff01010101, 0xffff01ff010101ff, 0xffff01ff0101ff01, 0x01ff01ff0101ffff,
0xffff01ff01ff0101, 0x01ff01ff01ff01ff, 0x01ff01ff01ffff01, 0xffff01ff01ffffff,
0xffff01ffff010101, 0x01ff01ffff0101ff, 0x01ff01ffff01ff01, 0xffff01ffff01ffff,
0x01ff01ffffff0101, 0xffff01ffffff01ff, 0xffff01ffffffff01, 0x01ff01ffffffffff,
0x01ffff0101010101, 0xffffff01010101ff, 0xffffff010101ff01, 0x01ffff010101ffff,
0xffffff0101ff0101, 0x01ffff0101ff01ff, 0x01ffff0101ffff01, 0xffffff0101ffffff,
0xffffff01ff010101, 0x01ffff01ff0101ff, 0x01ffff01ff01ff01, 0xffffff01ff01ffff,
0x01ffff01ffff0101, 0xffffff01ffff01ff, 0xffffff01ffffff01, 0x01ffff01ffffffff,
0xffffffff01010101, 0x01ffffff010101ff, 0x01ffffff0101ff01, 0xffffffff0101ffff,
0x01ffffff01ff0101, 0xffffffff01ff01ff, 0xffffffff01ffff01, 0x01ffffff01ffffff,
0x01ffffffff010101, 0xffffffffff0101ff, 0xffffffffff01ff01, 0x01ffffffff01ffff,
0xffffffffffff0101, 0x01ffffffffff01ff, 0x01ffffffffffff01, 0xffffffffffffffff,
};
}
bool iqk_mul_mat(long Nx, long Ny, long ne00, int typeA, const void * A, const void * B,
float * C, long stride_C, int ith, int nth) {
MulMat mm;
int row_size_q8;
if (!MulMat::set_mul_mat(typeA, ne00, mm, row_size_q8, Ny)) {
return false;
}
auto row_size_qx = ggml_row_size((ggml_type)typeA, ne00);
auto nrc_x = (Nx + nth - 1)/nth;
auto first_x = ith*nrc_x;
if (first_x + nrc_x > Nx) nrc_x = Nx - first_x;
DataInfo info{C + first_x, (const char *)B, (size_t)stride_C, (size_t)row_size_q8, 0, 1, nullptr, 0};
mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny);
return true;
}
bool iqk_mul_mat_moe(long Nx, long Ny, long ne00, int ne11, int typeA, const void * A, const void * B,
float * C, long nb1, long nb2, const void * vrow_mapping, int ith, int nth) {
const mmid_row_mapping * row_mapping = (const mmid_row_mapping *)vrow_mapping;
assert(row_mapping != nullptr);
MulMat mm;
int row_size_q8;
if (!MulMat::set_mul_mat(typeA, ne00, mm, row_size_q8, Ny)) {
return false;
}
int row_size_qx = ggml_row_size((ggml_type)typeA, ne00);
int nrc_x = (Nx + nth - 1)/nth;
int first_x = ith*nrc_x;
if (first_x + nrc_x > Nx) nrc_x = Nx - first_x;
DataInfo info{C + first_x, (const char *)B, nb1/sizeof(float), (size_t)row_size_q8, 0, ne11, row_mapping, nb2/sizeof(float)};
mm.mul_mat_NxM(ne00, (const char *)A + row_size_qx*first_x, row_size_qx, info, nrc_x, Ny);
return true;
}
#if defined __x86_64__
#if defined HAVE_FANCY_SIMD
#undef HAVE_FANCY_SIMD
#endif
#if defined(__AVX512F__) && defined(__AVX512VNNI__) && defined(__AVX512VL__) && defined(__AVX512BW__) && defined(__AVX512DQ__)
#define HAVE_FANCY_SIMD
#endif
namespace {
inline float hsum_float_4(__m128 x) {
x = _mm_add_ps(x, _mm_movehl_ps(x, x));
x = _mm_add_ss(x, _mm_movehdup_ps(x));
return _mm_cvtss_f32(x);
}
inline float hsum_float_8(__m256 x) {
return hsum_float_4(_mm_add_ps(_mm256_castps256_ps128(x), _mm256_extractf128_ps(x, 1)));
}
#define MM256_SET_M128I(a, b) _mm256_insertf128_si256(_mm256_castsi128_si256(b), (a), 1)
template <int nrc, typename block_q8 = block_q8_K> struct Q8 {
constexpr static int nrc_y = nrc;
Q8(const DataInfo& info) {
for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy);
}
#ifdef HAVE_FANCY_SIMD
inline __m512i load_quants(int iy, int i, int j) const { return _mm512_loadu_si512((const __m512i*)y[iy][i].qs + j); }
#else
inline __m256i load_quants(int iy, int i, int j) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].qs + j); }
#endif
inline __m256i load_bsums(int iy, int i) const { return _mm256_loadu_si256((const __m256i*)y[iy][i].bsums); }
inline float scale(int iy, int i) const { return y[iy][i].d; }
const block_q8 * y[nrc_y];
};
// Handles q4_K and q5_K scales/mins
struct Scales8K {
template <typename Q8>
inline __m256i process_mins_and_scales(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) {
make_q4_scales(data, utmp);
const __m256i mins_and_scales = _mm256_cvtepu8_epi16(_mm_set_epi32(utmp[3], utmp[2], utmp[1], utmp[0]));
const __m128i mins128 = _mm256_extracti128_si256(mins_and_scales, 1);
accum_mins(mins128, q8, i, c, accd);
const __m128i sc128 = _mm256_extracti128_si256(mins_and_scales, 0);
return MM256_SET_M128I(sc128, sc128);
}
#ifdef HAVE_FANCY_SIMD
template <typename Q8>
inline __m512i process_mins_and_scales_64(const uint8_t * data, float c, int i, const Q8& q8, __m256 * accd) {
auto scales = process_mins_and_scales(data, c, i, q8, accd);
return _mm512_inserti32x8(_mm512_castsi256_si512(scales), scales, 1);
}
#endif
template <typename Q8>
inline void accum_mins(const __m128i& mins128, const Q8& q8, int i, float c, __m256 * accd) const {
const __m256i mins = MM256_SET_M128I(_mm_shuffle_epi8(mins128, shuffles[1]), _mm_shuffle_epi8(mins128, shuffles[0]));
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
const __m256i q8s = q8.load_bsums(iy, i);
const __m256i prod = _mm256_madd_epi16(mins, q8s);
accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(c*q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accd[iy]);
}
}
#ifdef HAVE_FANCY_SIMD
const __m512i shuffles512[2] = {
_mm512_set_epi64(0x0706070607060706, 0x0302030203020302, 0x0706070607060706, 0x0302030203020302,
0x0504050405040504, 0x0100010001000100, 0x0504050405040504, 0x0100010001000100),
_mm512_set_epi64(0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a, 0x0f0e0f0e0f0e0f0e, 0x0b0a0b0a0b0a0b0a,
0x0d0c0d0c0d0c0d0c, 0x0908090809080908, 0x0d0c0d0c0d0c0d0c, 0x0908090809080908)
};
#endif
const __m128i shuffles[2] = {_mm_set_epi32(0x07060706, 0x05040504, 0x03020302, 0x01000100),
_mm_set_epi32(0x0f0e0f0e, 0x0d0c0d0c, 0x0b0a0b0a, 0x09080908)};
uint32_t utmp[4];
};
template <typename Q8>
inline void process_mins_16(const __m256i& all_scales, const Q8& q8, int i, float d, __m256 * accm) {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
const __m256i prod = _mm256_madd_epi16(all_scales, q8.load_bsums(iy, i));
accm[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d * q8.scale(iy, i)), _mm256_cvtepi32_ps(prod), accm[iy]);
}
}
inline void prepare_scales_16(const __m256i& all_scales, __m256i * scales) {
const __m128i l_scales = _mm256_extracti128_si256(all_scales, 0);
const __m128i h_scales = _mm256_extracti128_si256(all_scales, 1);
scales[0] = MM256_SET_M128I(l_scales, l_scales);
scales[1] = MM256_SET_M128I(h_scales, h_scales);
}
struct ScaleQ3 {
inline __m128i make_scales(const uint16_t * s8) const {
const uint16_t * scales16 = (const uint16_t *)s8;
uint32_t aux0 = scales16[0] | (scales16[1] << 16);
uint32_t aux1 = scales16[2] | (scales16[3] << 16);
uint32_t aux2 = scales16[4] | (scales16[5] << 16);
__m128i scales128 = _mm_set_epi32(
((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030),
((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030),
(aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030),
(aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030));
return _mm_add_epi8(scales128, m32);
}
const __m128i m32 = _mm_set1_epi8(-32);
};
struct ScaleIQ4XS {
inline __m128i make_scales(const uint32_t scales_l, const uint16_t scales_h) {
uint32_t tmp32 = scales_h | (scales_h << 14);
const __m128i sh = _mm_slli_epi16(_mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(tmp32), hshift), hmask), 4);
const __m128i sl = _mm_and_si128(_mm_srlv_epi32(_mm_set1_epi32(scales_l), lshift), lmask);
return _mm_add_epi16(_mm_or_si128(sh, _mm_cvtepi8_epi16(_mm_shuffle_epi8(sl, lshuffle))), m32);
}
const __m128i hshift = _mm_set_epi32(12, 8, 4, 0);
const __m128i lshift = _mm_set_epi32(4, 0, 4, 0);
const __m128i hmask = _mm_set1_epi16(0x03);
const __m128i lmask = _mm_set1_epi8(0xf);
const __m128i lshuffle = _mm_set_epi32(0x07030602, 0x05010400, 0x07030602, 0x05010400);
const __m128i m32 = _mm_set1_epi16(-32);
};
template <typename Block>
struct BaseDequantizer {
BaseDequantizer(const void * vx, size_t bx) : vx(vx), bx(bx) {}
inline void new_row(int ix) {
x = (const Block *)((const char *)vx + bx*ix);
}
const void * vx;
size_t bx;
const Block * x;
float d;
};
#ifdef HAVE_FANCY_SIMD
//====================================== Zen4 ==================================================
struct BlockPermuter {
const __m512i permute1 = _mm512_set_epi64(11, 10, 9, 8, 3, 2, 1, 0);
const __m512i permute2 = _mm512_set_epi64(15, 14, 13, 12, 7, 6, 5, 4);
};
struct Q4Bits {
inline void prepare(const uint8_t * q4) {
auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0);
auto tmp1 = _mm512_and_si512(q4bits, ml);
auto tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
values[0] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2);
values[1] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2);
q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1);
tmp1 = _mm512_and_si512(q4bits, ml);
tmp2 = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
values[2] = _mm512_permutex2var_epi64(tmp1, perm.permute1, tmp2);
values[3] = _mm512_permutex2var_epi64(tmp1, perm.permute2, tmp2);
}
inline void prepare64(const uint8_t * q4) {
auto q4bits = _mm512_loadu_si512((const __m512i*)q4 + 0);
values[0] = _mm512_and_si512(q4bits, ml);
values[1] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
q4bits = _mm512_loadu_si512((const __m512i*)q4 + 1);
values[2] = _mm512_and_si512(q4bits, ml);
values[3] = _mm512_and_si512(_mm512_srli_epi16(q4bits, 4), ml);
}
__m512i values[4];
const __m512i ml = _mm512_set1_epi8(0xf);
BlockPermuter perm;
};
struct Q2Bits {
inline void prepare(const uint8_t * q2) {
auto q2bits = _mm512_loadu_si512((const __m512i*)q2);
auto tmp = _mm512_srli_epi16(q2bits, 2);
values[0] = _mm512_permutex2var_epi64(q2bits, perm.permute1, tmp);
values[2] = _mm512_permutex2var_epi64(q2bits, perm.permute2, tmp);
values[1] = _mm512_and_si512(_mm512_srli_epi16(values[0], 4), ml);
values[3] = _mm512_and_si512(_mm512_srli_epi16(values[2], 4), ml);
values[0] = _mm512_and_si512(values[0], ml);
values[2] = _mm512_and_si512(values[2], ml);
}
__m512i values[4];
const __m512i ml = _mm512_set1_epi8(0x03);
BlockPermuter perm;
};
struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
bits.prepare(x[i].qs);
auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
}
Q4Bits bits;
Scales8K s8k;
};
struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_values()) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
prepare(x[i].qs);
auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h);
s8k.accum_mins(scales128, q8, i, -128.f*d, accd);
auto scales256 = MM256_SET_M128I(scales128, scales128);
auto all_scales = _mm512_inserti32x8(_mm512_castsi256_si512(scales256), scales256, 1);
scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
}
static __m512i load_values() {
static const uint8_t kvalues_iq4nl[16] = {1, 24, 45, 63, 79, 93, 106, 118, 129, 141, 153, 166, 181, 197, 217, 241};
auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
auto val256 = MM256_SET_M128I(val128, val128);
return _mm512_inserti32x8(_mm512_castsi256_si512(val256), val256, 1);
}
inline void prepare(const uint8_t * q4) {
bits.prepare64(q4);
// We now have in bits.valuse[0]: 0...15, 32...47, 64...79, 96...111
// bits.valuse[1]: 16..31, 48...63, 80...95, 112..127
// etc.
auto tmp = _mm512_permutex2var_epi64(bits.values[0], permute1, bits.values[1]);
bits.values[1] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[0], permute2, bits.values[1]));
bits.values[0] = _mm512_shuffle_epi8(values, tmp);
tmp = _mm512_permutex2var_epi64(bits.values[2], permute1, bits.values[3]);
bits.values[3] = _mm512_shuffle_epi8(values, _mm512_permutex2var_epi64(bits.values[2], permute2, bits.values[3]));
bits.values[2] = _mm512_shuffle_epi8(values, tmp);
}
Q4Bits bits;
Scales8K s8k;
ScaleIQ4XS siq4;
const __m512i values;
const __m512i permute1 = _mm512_set_epi64(11, 10, 3, 2, 9, 8, 1, 0);
const __m512i permute2 = _mm512_set_epi64(15, 14, 7, 6, 13, 12, 5, 4);
};
struct HighBit5 {
inline void apply(const uint8_t * h, Q4Bits& bits) {
auto hbits256 = _mm256_loadu_si256((const __m256i *)h);
auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1);
bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh));
bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh));
bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(hbits, mh));
bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh));
}
const __m512i mh = _mm512_set1_epi8(0x10);
};
struct HighBit3 {
inline void apply(const uint8_t * h, Q2Bits& bits) {
auto hbits256 = _mm256_loadu_si256((const __m256i *)h);
auto hbits = _mm512_inserti32x8(_mm512_castsi256_si512(hbits256), _mm256_srli_epi16(hbits256, 1), 1);
bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh));
bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_and_si512(hbits, mh));
bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh));
bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_and_si512(_mm512_srli_epi16(hbits, 4), mh));
}
const __m512i mh = _mm512_set1_epi8(0x04);
};
struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accd, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
bits.prepare(x[i].qs);
hbits.apply(x[i].qh, bits);
auto all_scales = s8k.process_mins_and_scales_64(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
scales[0] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[0]);
scales[1] = _mm512_shuffle_epi8(all_scales, s8k.shuffles512[1]);
}
Q4Bits bits;
HighBit5 hbits;
Scales8K s8k;
};
struct Scale16 {
inline void make_scales(const __m128i& scales8, __m512i * scales) const {
auto all_scales8 = MM256_SET_M128I(scales8, scales8);
auto scales1 = _mm256_shuffle_epi8(all_scales8, shuffle1);
auto scales2 = _mm256_shuffle_epi8(all_scales8, shuffle2);
scales[0] = _mm512_cvtepi8_epi16(scales1);
scales[1] = _mm512_cvtepi8_epi16(scales2);
}
template <typename Q8>
inline void process_mins_and_scales(int i, float c, const __m128i& mins8, const __m128i& scales8,
const Q8& q8, __m256 * accm, __m512i * scales) const {
process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, c, accm);
make_scales(scales8, scales);
}
const __m256i shuffle1 = _mm256_set_epi32(0x07070707, 0x03030303, 0x06060606, 0x02020202,
0x05050505, 0x01010101, 0x04040404, 0x00000000);
const __m256i shuffle2 = _mm256_set_epi32(0x0f0f0f0f, 0x0b0b0b0b, 0x0e0e0e0e, 0x0a0a0a0a,
0x0d0d0d0d, 0x09090909, 0x0c0c0c0c, 0x08080808);
};
struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
bits.prepare(x[i].qs);
const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales);
const __m128i scales8 = _mm_and_si128(mins_and_scales, m4);
const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4);
sc16.process_mins_and_scales(i, -GGML_FP16_TO_FP32(x[i].dmin), mins8, scales8, q8, accm, scales);
}
Q2Bits bits;
Scale16 sc16;
const __m128i m4 = _mm_set1_epi8(0xf);
};
struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
bits.prepare(x[i].qs);
hbits.apply(x[i].hmask, bits);
auto scales128 = sc3.make_scales((const uint16_t *)x[i].scales);
sc16.process_mins_and_scales(i, -4.f*d, scales128, scales128, q8, accm, scales);
}
Q2Bits bits;
HighBit3 hbits;
ScaleQ3 sc3;
Scale16 sc16;
const __m128i m4 = _mm_set1_epi8(0xf);
const __m128i m32 = _mm_set1_epi8(-32);
};
struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m512i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
bits.prepare64(x[i].ql);
add_high_bits(x[i].qh, bits);
auto scales128 = _mm_loadu_si128((const __m128i *)x[i].scales);
sc16.process_mins_and_scales(i, -32.f*d, scales128, scales128, q8, accm, scales);
}
inline void add_high_bits(const uint8_t * qh, Q4Bits& bits) const {
auto hbits = _mm512_loadu_si512((const __m512i *)qh);
auto tmp1 = _mm512_and_si512(_mm512_slli_epi16(hbits, 4), mh);
auto tmp2 = _mm512_and_si512(_mm512_slli_epi16(hbits, 2), mh);
bits.values[0] = _mm512_or_si512(bits.values[0], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2));
bits.values[2] = _mm512_or_si512(bits.values[2], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2));
tmp1 = _mm512_and_si512(hbits, mh);
tmp2 = _mm512_and_si512(_mm512_srli_epi16(hbits, 2), mh);
bits.values[1] = _mm512_or_si512(bits.values[1], _mm512_permutex2var_epi64(tmp1, bits.perm.permute1, tmp2));
bits.values[3] = _mm512_or_si512(bits.values[3], _mm512_permutex2var_epi64(tmp1, bits.perm.permute2, tmp2));
}
Q4Bits bits;
HighBit3 hbits;
Scale16 sc16;
const __m512i mh = _mm512_set1_epi8(0x30);
};
template <typename Dequantizer, int nrc_y>
static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n % QK_K == 0);
const int nb = n / QK_K;
Q8<nrc_y> q8(info);
Dequantizer deq(vx, bx);
__m256 accm[nrc_y];
__m512 accd[nrc_y];
__m512i scales[2];
for (int ix = 0; ix < nrc_x; ++ix) {
for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm512_setzero_ps();
for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm256_setzero_ps();
deq.new_row(ix);
for (int i = 0; i < nb; ++i) {
deq.new_block(i, q8, accm, scales);
for (int iy = 0; iy < nrc_y; ++iy) {
const __m512i p1 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[0], q8.load_quants(iy, i, 0));
const __m512i p2 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[1], q8.load_quants(iy, i, 1));
const __m512i p3 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[2], q8.load_quants(iy, i, 2));
const __m512i p4 = _mm512_dpbusd_epi32(_mm512_setzero_si512(), deq.bits.values[3], q8.load_quants(iy, i, 3));
auto sumi = _mm512_dpwssd_epi32(_mm512_setzero_si512(), scales[0], _mm512_packs_epi32(p1, p2));
sumi = _mm512_dpwssd_epi32(sumi, scales[1], _mm512_packs_epi32(p3, p4));
accd[iy] = _mm512_fmadd_ps(_mm512_set1_ps(deq.d*q8.scale(iy, i)), _mm512_cvtepi32_ps(sumi), accd[iy]);
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
auto sum256 = _mm256_add_ps(_mm512_castps512_ps256(accd[iy]), _mm512_extractf32x8_ps(accd[iy], 1));
info.store(ix, iy, hsum_float_8(_mm256_add_ps(accm[iy], sum256)));
}
}
}
#else
// ===================================== Vanilla AVX2 =====================================
struct Q4Bits {
inline void prepare(const uint8_t * q4, int j) {
auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0);
values[0] = _mm256_and_si256(q4bits, ml);
values[1] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1);
values[2] = _mm256_and_si256(q4bits, ml);
values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
}
inline void prepare64(const uint8_t * q4, int j) {
auto q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+0);
values[0] = _mm256_and_si256(q4bits, ml);
values[2] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
q4bits = _mm256_loadu_si256((const __m256i*)q4 + 2*j+1);
values[1] = _mm256_and_si256(q4bits, ml);
values[3] = _mm256_and_si256(_mm256_srli_epi16(q4bits, 4), ml);
}
inline void prepare16(const uint8_t * q4, int j) {
values[0] = dequant16(q4 + 64*j + 0);
values[1] = dequant16(q4 + 64*j + 16);
values[2] = dequant16(q4 + 64*j + 32);
values[3] = dequant16(q4 + 64*j + 48);
}
inline __m256i dequant16(const uint8_t * qs) const {
const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs);
const __m256i aux256 = MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128);
return _mm256_and_si256(ml, aux256);
};
__m256i values[4];
const __m256i ml = _mm256_set1_epi8(0xf);
};
struct Q2Bits {
inline void prepare(const uint8_t * q2, int j) {
auto q2bits = _mm256_loadu_si256((const __m256i *)q2 + j);
values[0] = _mm256_and_si256(q2bits, ml);
values[1] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 2), ml);
values[2] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 4), ml);
values[3] = _mm256_and_si256(_mm256_srli_epi16(q2bits, 6), ml);
}
__m256i values[4];
const __m256i ml = _mm256_set1_epi8(0x03);
};
struct HighBit5 {
inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); }
inline void apply(Q4Bits& bits, bool do_shift) {
bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh));
bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 3), mh));
bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh));
if (do_shift) {
hbits = _mm256_srli_epi16(hbits, 4);
}
}
const __m256i mh = _mm256_set1_epi8(0x10);
__m256i hbits;
};
struct HighBit3 {
inline void load(const uint8_t * h) { hbits = _mm256_loadu_si256((const __m256i *)h); }
inline void apply(Q2Bits& bits, bool do_shift) {
bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 1), mh));
bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh));
bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 1), mh));
if (do_shift) {
hbits = _mm256_srli_epi16(hbits, 4);
}
}
const __m256i mh = _mm256_set1_epi8(0x04);
__m256i hbits;
};
inline __m256i get_scale_shuffle_8(int i) {
return _mm256_set1_epi16((2*i) | ((2*i+1) << 8));
}
inline void set_scales_8(const __m256i& all_scales, int j, __m256i * scales) {
scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+0));
scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+1));
scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+2));
scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_8(4*j+3));
}
template <typename Q8, typename Bits>
inline void multiply_add(const Bits& bits, const __m256i * scales, int j, int i, const Q8& q8, __m256i * sumi) {
if (j == 0) {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 0)));
const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 1)));
const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 2)));
const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 3)));
sumi[iy] = _mm256_add_epi32(_mm256_add_epi32(p1, p3), _mm256_add_epi32(p2, p4));
}
} else {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
const __m256i p1 = _mm256_madd_epi16(scales[0], _mm256_maddubs_epi16(bits.values[0], q8.load_quants(iy, i, 4)));
const __m256i p2 = _mm256_madd_epi16(scales[1], _mm256_maddubs_epi16(bits.values[1], q8.load_quants(iy, i, 5)));
const __m256i p3 = _mm256_madd_epi16(scales[2], _mm256_maddubs_epi16(bits.values[2], q8.load_quants(iy, i, 6)));
const __m256i p4 = _mm256_madd_epi16(scales[3], _mm256_maddubs_epi16(bits.values[3], q8.load_quants(iy, i, 7)));
sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p1, p3));
sumi[iy] = _mm256_add_epi32(sumi[iy], _mm256_add_epi32(p2, p4));
}
}
}
struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
DequantizerQ4K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
d = GGML_FP16_TO_FP32(x[i].d);
return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs, j);
}
Q4Bits bits;
Scales8K s8k;
};
struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
DequantizerIQ4XS(const void * vx, size_t bx) : BaseDequantizer(vx, bx), values(load_values()) {}
template <typename Q8>
inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
d = GGML_FP16_TO_FP32(x[i].d);
auto scales128 = siq4.make_scales(*(const uint32_t *)x[i].scales_l, x[i].scales_h);
s8k.accum_mins(scales128, q8, i, -128.f*d, accd);
return MM256_SET_M128I(scales128, scales128);
}
inline void prepare(int i, int j) {
bits.prepare16(x[i].qs, j);
bits.values[0] = _mm256_shuffle_epi8(values, bits.values[0]);
bits.values[1] = _mm256_shuffle_epi8(values, bits.values[1]);
bits.values[2] = _mm256_shuffle_epi8(values, bits.values[2]);
bits.values[3] = _mm256_shuffle_epi8(values, bits.values[3]);
}
static __m256i load_values() {
static const uint8_t kvalues_iq4nl[16] = {1, 24, 45, 63, 79, 93, 106, 118, 129, 141, 153, 166, 181, 197, 217, 241};
auto val128 = _mm_loadu_si128((const __m128i *)kvalues_iq4nl);
return MM256_SET_M128I(val128, val128);
}
Q4Bits bits;
Scales8K s8k;
ScaleIQ4XS siq4;
const __m256i values;
};
struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
DequantizerQ5K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline __m256i new_block(int i, const Q8& q8, __m256 * accd) {
d = GGML_FP16_TO_FP32(x[i].d);
hbits.load(x[i].qh);
return s8k.process_mins_and_scales(x[i].scales, -GGML_FP16_TO_FP32(x[i].dmin), i, q8, accd);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs, j);
hbits.apply(bits, j == 0);
}
Q4Bits bits;
HighBit5 hbits;
Scales8K s8k;
};
template <typename Q8>
inline void process_mins_and_scales_16(const __m128i& scales128, const Q8& q8, int i, float d,
__m256 * accm, __m256i * scales) {
const __m256i all_scales = _mm256_cvtepi8_epi16(scales128);
process_mins_16(all_scales, q8, i, d, accm);
prepare_scales_16(all_scales, scales);
}
struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
DequantizerQ3K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
hbits.load(x[i].hmask);
process_mins_and_scales_16(sc3.make_scales((const uint16_t *)x[i].scales), q8, i, -4.f*d, accm, scales);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs, j);
hbits.apply(bits, j == 0);
}
Q2Bits bits;
HighBit3 hbits;
ScaleQ3 sc3;
const __m128i m32 = _mm_set1_epi8(-32);
};
struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
DequantizerQ2K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
const __m128i mins_and_scales = _mm_loadu_si128((const __m128i*)x[i].scales);
const __m128i scales8 = _mm_and_si128(mins_and_scales, m4);
const __m128i mins8 = _mm_and_si128(_mm_srli_epi16(mins_and_scales, 4), m4);
process_mins_16(_mm256_cvtepi8_epi16(mins8), q8, i, -GGML_FP16_TO_FP32(x[i].dmin), accm);
prepare_scales_16(_mm256_cvtepi8_epi16(scales8), scales);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs, j);
}
Q2Bits bits;
const __m128i m4 = _mm_set1_epi8(0xf);
};
struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
DequantizerQ6K(const void * vx, size_t bx) : BaseDequantizer(vx, bx) {}
template <typename Q8>
inline void new_block(int i, const Q8& q8, __m256 * accm, __m256i * scales) {
d = GGML_FP16_TO_FP32(x[i].d);
process_mins_and_scales_16(_mm_loadu_si128((const __m128i *)x[i].scales), q8, i, -32.f*d, accm, scales);
}
inline void prepare(int i, int j) {
bits.prepare64(x[i].ql, j);
auto hbits = _mm256_loadu_si256((const __m256i *)x[i].qh + j);
bits.values[0] = _mm256_or_si256(bits.values[0], _mm256_and_si256(_mm256_slli_epi16(hbits, 4), mh));
bits.values[1] = _mm256_or_si256(bits.values[1], _mm256_and_si256(_mm256_slli_epi16(hbits, 2), mh));
bits.values[2] = _mm256_or_si256(bits.values[2], _mm256_and_si256(hbits, mh));
bits.values[3] = _mm256_or_si256(bits.values[3], _mm256_and_si256(_mm256_srli_epi16(hbits, 2), mh));
}
Q4Bits bits;
const __m256i mh = _mm256_set1_epi8(0x30);
};
inline __m256i get_scale_shuffle_16(int i) {
static const uint8_t k_shuffle[128] = {
0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 0, 1, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3, 2, 3,
4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 4, 5, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7, 6, 7,
8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 8, 9, 10,11,10,11,10,11,10,11,10,11,10,11,10,11,10,11,
12,13,12,13,12,13,12,13,12,13,12,13,12,13,12,13, 14,15,14,15,14,15,14,15,14,15,14,15,14,15,14,15,
};
return _mm256_loadu_si256((const __m256i*)k_shuffle + i);
}
inline void set_scales_16(const __m256i& all_scales, __m256i * scales) {
scales[0] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(0));
scales[1] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(1));
scales[2] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(2));
scales[3] = _mm256_shuffle_epi8(all_scales, get_scale_shuffle_16(3));
}
template <typename Dequantizer, int nrc_y>
static void mul_mat_qY_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n%QK_K == 0);
const int nb = n/QK_K;
Q8<nrc_y> q8(info);
__m256i all_scales[2];
__m256i scales[4];
__m256 accd[nrc_y];
Dequantizer deq(vx, bx);
for (int ix = 0; ix < nrc_x; ++ix) {
deq.new_row(ix);
for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps();
for (int i = 0; i < nb; ++i) {
deq.new_block(i, q8, accd, all_scales);
__m256i sumi[nrc_y];
for (int j = 0; j < QK_K/128; ++j) {
deq.prepare(i, j);
set_scales_16(all_scales[j], scales);
multiply_add(deq.bits, scales, j, i, q8, sumi);
}
for (int iy = 0; iy < nrc_y; ++iy) {
accd[iy] = _mm256_fmadd_ps(_mm256_set1_ps(deq.d*q8.scale(iy, i)), _mm256_cvtepi32_ps(sumi[iy]), accd[iy]);
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, hsum_float_8(accd[iy]));
}
}
}
template <typename Dequantizer, int nrc_y>
static void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n % QK_K == 0);
const int nb = n / QK_K;
Q8<nrc_y> q8(info);
Dequantizer deq(vx, bx);
__m256 accd[nrc_y];
__m256i scales[4];
for (int ix = 0; ix < nrc_x; ++ix) {
for (int iy = 0; iy < nrc_y; ++iy) accd[iy] = _mm256_setzero_ps();
deq.new_row(ix);
for (int i = 0; i < nb; ++i) {
auto all_scales = deq.new_block(i, q8, accd);
__m256i sumi[nrc_y];
for (int j = 0; j < QK_K/128; ++j) {
deq.prepare(i, j);
set_scales_8(all_scales, j, scales);
multiply_add(deq.bits, scales, j, i, q8, sumi);
}
for (int iy = 0; iy < nrc_y; ++iy) {
const __m256 vd = _mm256_set1_ps(deq.d*q8.scale(iy, i));
accd[iy] = _mm256_fmadd_ps(vd, _mm256_cvtepi32_ps(sumi[iy]), accd[iy]);
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, hsum_float_8(accd[iy]));
}
}
}
#endif // Zen4 or vanilla AVX2
//
// ============================== Legacy quants
//
struct DotHelper {
const __m256i m1 = _mm256_set1_epi16(1);
#if defined(__AVX512VNNI__) && defined(__AVX512VL__)
inline __m256i dot(__m256i x, __m256i y) const {
return _mm256_dpbusd_epi32(_mm256_setzero_si256(), x, y);
}
#else
inline __m256i dot(__m256i x, __m256i y) const {
return _mm256_madd_epi16(m1, _mm256_maddubs_epi16(x, y));
}
#endif
};
struct SignedDot {
DotHelper helper;
inline __m256i compute(__m256i x, __m256i y) const {
return helper.dot(_mm256_sign_epi8(x, x), _mm256_sign_epi8(y, x));
}
};
struct UnsignedDot {
DotHelper helper;
inline __m256i compute(__m256i x, __m256i y) const {
return helper.dot(x, y);
}
};
template <typename Q8, typename Dot> struct Sum4 {
Dot dot;
inline __m256i compute(const __m256i * qx, const Q8 * y) const {
const __m256i p0 = dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[0].qs));
const __m256i p1 = dot.compute(qx[1], _mm256_loadu_si256((const __m256i *)y[1].qs));
const __m256i p2 = dot.compute(qx[2], _mm256_loadu_si256((const __m256i *)y[2].qs));
const __m256i p3 = dot.compute(qx[3], _mm256_loadu_si256((const __m256i *)y[3].qs));
const __m256i p01 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p0, p1)); // 0,0, 1,1, 0,0, 1,1
const __m256i p23 = _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p2, p3)); // 2,2, 3,3, 2,2, 3,3
return _mm256_madd_epi16(dot.helper.m1, _mm256_packs_epi32(p01, p23)); // 0,1,2,3, 0,1,2,3
}
};
struct Sum4_Q8 {
SignedDot dot;
static inline __m256i add1(__m256i a, __m256i b) {
return _mm256_add_epi32(_mm256_unpacklo_epi32(a, b), _mm256_unpackhi_epi32(a, b));
}
static inline __m256i add2(__m256i a, __m256i b) {
return _mm256_add_epi32(_mm256_unpacklo_epi64(a, b), _mm256_unpackhi_epi64(a, b));
}
inline __m256i compute(const __m256i * qx, const block_q8_0 * y) const {
const __m256i p0 = dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[0].qs));
const __m256i p1 = dot.compute(qx[1], _mm256_loadu_si256((const __m256i *)y[1].qs));
const __m256i p2 = dot.compute(qx[2], _mm256_loadu_si256((const __m256i *)y[2].qs));
const __m256i p3 = dot.compute(qx[3], _mm256_loadu_si256((const __m256i *)y[3].qs));
const __m256i p01 = add1(p0, p1); // 0,1, 0,1, 0,1, 0,1
const __m256i p23 = add1(p2, p3); // 2,3, 2,3, 2,3, 2,3
return add2(p01, p23); // returns 0,1,2,3, 0,1,2,3
}
};
struct ScaleHelperQ_0 {
ggml_half scales8[4];
template <typename Q>
inline __m128 prepare4(const Q * y) {
for (int j = 0; j < 4; ++j) scales8[j] = y[j].d;
return _mm_cvtph_ps(_mm_loadl_epi64((const __m128i *)scales8));
}
template <typename Q>
inline __m128 prepare4(__m128 other_scales, const Q * y) {
return _mm_mul_ps(other_scales, prepare4<Q>(y));
}
template <typename Q> inline float prepare1(const Q * y) const { return GGML_FP16_TO_FP32(y->d); }
template <typename Q> inline float prepare1(float d, const Q * y) const { return d*prepare1(y); }
};
struct ScaleHelperQ_1 {
uint32_t scales8[4];
const __m128i shuffle = _mm_set_epi16(0x0f0e, 0x0b0a, 0x0706, 0x0302, 0x0d0c, 0x0908, 0x0504, 0x0100);
template <typename Q>
inline __m256 prepare4(const Q * y) {
for (int j = 0; j < 4; ++j) {
// it is slightly faster to directly dereference (const uint32 *)&y[j].d, but some compilers
// complain that this breaks strict-aliasing rules.
memcpy(scales8 + j, &y[j].d, sizeof(uint32_t));
}
return _mm256_cvtph_ps(_mm_shuffle_epi8(_mm_loadu_si128((const __m128i *)scales8), shuffle));
}
template <typename Q>
inline __m256 prepare4(__m256 other_scales, const Q * y) {
return _mm256_mul_ps(other_scales, prepare4<Q>(y));
}
template <typename Q> inline std::pair<float, float> prepare1(const Q * y) const {
return std::make_pair(GGML_FP16_TO_FP32(y->d), GGML_FP16_TO_FP32(y->m));
}
template <typename Q> inline std::pair<float, float> prepare1(const std::pair<float, float>& dm, const Q * y) const {
return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->m));
}
std::pair<float, float> inline prepare1(const std::pair<float, float>& dm, const block_q8_1 * y) const {
return std::make_pair(dm.first*GGML_FP16_TO_FP32(y->d), dm.second*GGML_FP16_TO_FP32(y->s));
}
};
struct MinusType0 {
inline __m256 compute(__m128 d, int) const { return _mm256_set_m128(d, d); }
inline float compute(float d, int) const { return d; }
inline float result(__m256 acc, int) const { return hsum_float_8(acc); }
};
template <int nrc_y> struct MinusType1 {
__m128 accm[nrc_y];
MinusType1() { for (int iy = 0; iy < nrc_y; ++iy) accm[iy] = _mm_setzero_ps(); }
inline __m256 compute(__m256 dm, int iy) {
const __m128 d = _mm256_castps256_ps128(dm);
const __m128 m = _mm256_extractf128_ps(dm, 1);
accm[iy] = _mm_add_ps(accm[iy], m);
return _mm256_set_m128(d, d);
}
inline float compute(const std::pair<float, float>& dm, int iy) {
accm[iy] = _mm_add_ps(accm[iy], _mm_set1_ps(dm.second*0.25f));
return dm.first;
}
inline float result(__m256 acc, int iy) const {
const __m128 sum = _mm_add_ps(_mm256_castps256_ps128(acc), _mm256_extractf128_ps(acc, 1));
return hsum_float_4(_mm_add_ps(sum, accm[iy]));
}
};
template <typename Minus, int nrc_y, bool is_multiple_of_4> struct AccumT {
__m256 acc[nrc_y];
Minus accm;
AccumT() { for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = _mm256_setzero_ps(); }
template <typename Unpacker, typename Scales, typename Sum, typename Q8>
inline void compute(int nb, Unpacker& unp, Scales& scales, Sum& sum, const Q8 ** y, const DataInfo& info, int ix) {
auto qx = unp.quants();
__m256 dall[nrc_y];
for (int i = 0; i < nb/4; ++i) {
auto other_scales = unp.set_block_4(i);
for (int iy = 0; iy < nrc_y; ++iy) {
auto s12 = scales.prepare4(other_scales, y[iy] + 4*i);
dall[iy] = accm.compute(s12, iy);
}
for (int iy = 0; iy < nrc_y; ++iy) {
auto pall = sum.compute(qx, y[iy] + 4*i);
acc[iy] = _mm256_fmadd_ps(dall[iy], _mm256_cvtepi32_ps(pall), acc[iy]);
}
}
if (!is_multiple_of_4) {
for (int i = 4*(nb/4); i < nb; ++i) {
auto other_scales = unp.set_block(i);
for (int iy = 0; iy < nrc_y; ++iy) {
auto s12 = scales.prepare1(other_scales, y[iy] + i);
auto d = accm.compute(s12, iy);
const __m256i p0 = sum.dot.compute(qx[0], _mm256_loadu_si256((const __m256i *)y[iy][i].qs));
acc[iy] = _mm256_fmadd_ps(_mm256_set1_ps(d), _mm256_cvtepi32_ps(p0), acc[iy]);
}
}
}
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, accm.result(acc[iy], iy));
//s[iy*bs] = accm.result(acc[iy], iy);
}
}
};
template <int nrc_y, bool is_multiple_of_4>
using AccumType0 = AccumT<MinusType0, nrc_y, is_multiple_of_4>;
template <int nrc_y, bool is_multiple_of_4>
using AccumType1 = AccumT<MinusType1<nrc_y>, nrc_y, is_multiple_of_4>;
using Sum4Type0 = Sum4<block_q8_0, SignedDot>;
using Sum4Type1 = Sum4<block_q8_1, UnsignedDot>;
template <typename Unpacker, typename Sum4Type, typename AccumType, typename Scales, typename Q8, int nrc_y>
void mul_mat_qX_q8_Helper(int nb, const void * vx, size_t bx, const DataInfo& info, const Q8 ** y, int nrc_x) {
Unpacker unp(vx, bx);
Sum4Type sum4;
Scales scales;
for (int ix = 0; ix < nrc_x; ++ix) {
unp.set_row(ix);
AccumType accum;
accum.compute(nb, unp, scales, sum4, y, info, ix);
}
}
template <typename Unpacker, int nrc_y>
void mul_mat_qX_0_q8_0_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n%Unpacker::block_size() == 0);
Q8<nrc_y, block_q8_0> q8(info);
int nb = n/Unpacker::block_size();
if (nb%4 == 0) {
mul_mat_qX_q8_Helper<Unpacker, Sum4Type0, AccumType0<nrc_y, true>, ScaleHelperQ_0, block_q8_0, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
} else {
mul_mat_qX_q8_Helper<Unpacker, Sum4Type0, AccumType0<nrc_y, false>, ScaleHelperQ_0, block_q8_0, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
}
}
template <typename Unpacker, int nrc_y>
void mul_mat_qX_1_q8_1_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n%Unpacker::block_size() == 0);
Q8<nrc_y, block_q8_1> q8(info);
int nb = n/Unpacker::block_size();
if (nb%4 == 0) {
mul_mat_qX_q8_Helper<Unpacker, Sum4Type1, AccumType1<nrc_y, true>, ScaleHelperQ_1, block_q8_1, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
} else {
mul_mat_qX_q8_Helper<Unpacker, Sum4Type1, AccumType1<nrc_y, false>, ScaleHelperQ_1, block_q8_1, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
}
}
struct Dequantizer4bit {
const __m256i m4 = _mm256_set1_epi8(0xf);
inline __m256i dequant(const uint8_t * qs) const {
const __m128i aux128 = _mm_loadu_si128((const __m128i *)qs);
return _mm256_and_si256(MM256_SET_M128I(_mm_srli_epi16(aux128, 4), aux128), m4);
}
};
struct Q8_0_Dequantizer {
inline __m256i dequant(const block_q8_0 * x) const {
return _mm256_loadu_si256((const __m256i *)x->qs);
}
};
struct Q4_0_Dequantizer {
Dequantizer4bit b4;
const __m256i m8 = _mm256_set1_epi8(-8);
inline __m256i dequant(const block_q4_0 * x) const {
return _mm256_add_epi8(b4.dequant(x->qs), m8);
}
};
struct Q4_1_Dequantizer {
Dequantizer4bit b4;
inline __m256i dequant(const block_q4_1 * x) const {
return b4.dequant(x->qs);
}
};
struct HBitDequantizer {
const __m256i shuffle = _mm256_set_epi64x(0x0303030303030303, 0x0202020202020202, 0x0101010101010101, 0x0000000000000000);
const __m256i mask = _mm256_set1_epi64x(0x7fbfdfeff7fbfdfe);
const __m256i minus1 = _mm256_set1_epi64x(-1);
inline __m256i to_bytes(const uint8_t * bits) const {
// Note: Data in all ggml quants is at least 2-byte aligned.
// => we can cast to uint16_t and use or on two consecutive entries
// which is faster than memcpy
const uint16_t * aux16 = (const uint16_t *)bits;
const uint32_t aux32 = aux16[0] | (aux16[1] << 16);
//uint32_t aux32; memcpy(&aux32, bits, sizeof(uint32_t));
__m256i bytes = _mm256_shuffle_epi8(_mm256_set1_epi32(aux32), shuffle);
bytes = _mm256_or_si256(bytes, mask);
return _mm256_cmpeq_epi8(bytes, minus1);
}
};
struct Q5_0_Dequantizer {
Dequantizer4bit b4;
HBitDequantizer hbit;
const __m256i mh = _mm256_set1_epi8((char)0xF0);
inline __m256i dequant(const block_q5_0 * x) const {
const __m256i vqh = _mm256_andnot_si256(hbit.to_bytes(x->qh), mh);
return _mm256_or_si256(b4.dequant(x->qs), vqh);
}
};
struct Q5_1_Dequantizer {
Dequantizer4bit b4;
HBitDequantizer hbit;
const __m256i mh = _mm256_set1_epi8(0x10);
inline __m256i dequant(const block_q5_1 * x) const {
const __m256i vqh = _mm256_and_si256(hbit.to_bytes(x->qh), mh);
return _mm256_or_si256(b4.dequant(x->qs), vqh);
}
};
template <typename Q, typename Scales, typename Dequantizer>
struct Q_Unpacker {
Q_Unpacker(const void * vx, size_t bx) : cx_0((const char *)vx), x((const Q*)cx_0), bx(bx) {}
const char * cx_0;
const Q * x;
size_t bx;
Scales scales;
Dequantizer deq;
__m256i qx[4];
inline const __m256i* quants() const { return qx; }
inline void set_row(int ix) { x = (const Q*)(cx_0 + ix*bx); }
inline auto set_block_4(int i) {
for (int j = 0; j < 4; ++j) {
qx[j] = deq.dequant(x + 4*i + j);
}
return scales.prepare4(x + 4*i);
}
inline auto set_block(int i) {
qx[0] = deq.dequant(x + i);
return scales.prepare1(x + i);
}
};
struct Q8_0_Unpacker final : public Q_Unpacker<block_q8_0, ScaleHelperQ_0, Q8_0_Dequantizer> {
Q8_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
inline static int block_size() { return QK4_0; }
};
struct Q4_0_Unpacker final : public Q_Unpacker<block_q4_0, ScaleHelperQ_0, Q4_0_Dequantizer> {
Q4_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
inline static int block_size() { return QK4_0; }
};
struct Q5_0_Unpacker final : public Q_Unpacker<block_q5_0, ScaleHelperQ_0, Q5_0_Dequantizer> {
Q5_0_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
inline static int block_size() { return QK5_0; }
};
struct Q4_1_Unpacker final : public Q_Unpacker<block_q4_1, ScaleHelperQ_1, Q4_1_Dequantizer> {
Q4_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
inline static int block_size() { return QK4_1; }
};
struct Q5_1_Unpacker final : public Q_Unpacker<block_q5_1, ScaleHelperQ_1, Q5_1_Dequantizer> {
Q5_1_Unpacker(const void * vx, size_t bx) : Q_Unpacker(vx, bx) {}
inline static int block_size() { return QK4_1; }
};
template <int nrc_y>
void mul_mat_q8_0_q8_0_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n%Q8_0_Unpacker::block_size() == 0);
Q8<nrc_y, block_q8_0> q8(info);
int nb = n/Q8_0_Unpacker::block_size();
if (nb%4 == 0) {
mul_mat_qX_q8_Helper<Q8_0_Unpacker, Sum4_Q8, AccumType0<nrc_y, true>, ScaleHelperQ_0, block_q8_0, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
} else {
mul_mat_qX_q8_Helper<Q8_0_Unpacker, Sum4_Q8, AccumType0<nrc_y, false>, ScaleHelperQ_0, block_q8_0, nrc_y>(
nb, vx, bx, info, q8.y, nrc_x
);
}
}
template <typename Dequantizer> void MulMat::set_functions(MulMat& m) {
if constexpr (std::is_same_v<Dequantizer, Q4_0_Unpacker> || std::is_same_v<Dequantizer, Q5_0_Unpacker>) {
m.funcs[0] = mul_mat_qX_0_q8_0_T<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_0_q8_0_T<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_0_q8_0_T<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_0_q8_0_T<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_0_q8_0_T<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_0_q8_0_T<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_0_q8_0_T<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_0_q8_0_T<Dequantizer, 8>;
}
else if constexpr (std::is_same_v<Dequantizer, Q4_1_Unpacker> || std::is_same_v<Dequantizer, Q5_1_Unpacker>) {
m.funcs[0] = mul_mat_qX_1_q8_1_T<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_1_q8_1_T<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_1_q8_1_T<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_1_q8_1_T<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_1_q8_1_T<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_1_q8_1_T<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_1_q8_1_T<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_1_q8_1_T<Dequantizer, 8>;
}
else {
#ifdef HAVE_FANCY_SIMD
m.funcs[0] = mul_mat_qX_K_q8_K_T<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_K_q8_K_T<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_K_q8_K_T<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_K_q8_K_T<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_K_q8_K_T<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_K_q8_K_T<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_K_q8_K_T<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_K_q8_K_T<Dequantizer, 8>;
#else
if constexpr (std::is_same_v<Dequantizer, DequantizerQ2K> ||
std::is_same_v<Dequantizer, DequantizerQ3K> ||
std::is_same_v<Dequantizer, DequantizerQ6K>) {
m.funcs[0] = mul_mat_qY_K_q8_K_T<Dequantizer, 1>;
m.funcs[1] = mul_mat_qY_K_q8_K_T<Dequantizer, 2>;
m.funcs[2] = mul_mat_qY_K_q8_K_T<Dequantizer, 3>;
m.funcs[3] = mul_mat_qY_K_q8_K_T<Dequantizer, 4>;
m.funcs[4] = mul_mat_qY_K_q8_K_T<Dequantizer, 5>;
m.funcs[5] = mul_mat_qY_K_q8_K_T<Dequantizer, 6>;
m.funcs[6] = mul_mat_qY_K_q8_K_T<Dequantizer, 7>;
m.funcs[7] = mul_mat_qY_K_q8_K_T<Dequantizer, 8>;
} else {
m.funcs[0] = mul_mat_qX_K_q8_K_T<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_K_q8_K_T<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_K_q8_K_T<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_K_q8_K_T<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_K_q8_K_T<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_K_q8_K_T<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_K_q8_K_T<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_K_q8_K_T<Dequantizer, 8>;
}
#endif
}
}
bool MulMat::set_mul_mat(int typeA, int ne00, MulMat& mm, int& row_size_q8, int) {
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_K, ne00);
switch (typeA) {
case GGML_TYPE_Q2_K:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerQ2K>(mm);
break;
case GGML_TYPE_Q3_K:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerQ3K>(mm);
break;
case GGML_TYPE_Q4_K:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerQ4K>(mm);
break;
case GGML_TYPE_Q5_K:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerQ5K>(mm);
break;
case GGML_TYPE_Q6_K:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerQ6K>(mm);
break;
case GGML_TYPE_IQ4_XS:
assert (ne00 % QK_K == 0);
MulMat::set_functions<DequantizerIQ4XS>(mm);
break;
case GGML_TYPE_Q4_0:
assert (ne00 % QK4_0 == 0);
MulMat::set_functions<Q4_0_Unpacker>(mm);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
break;
case GGML_TYPE_Q4_1:
assert (ne00 % QK4_1 == 0);
MulMat::set_functions<Q4_1_Unpacker>(mm);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
break;
case GGML_TYPE_Q5_0:
assert (ne00 % QK5_0 == 0);
MulMat::set_functions<Q5_0_Unpacker>(mm);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
break;
case GGML_TYPE_Q5_1:
assert (ne00 % QK5_1 == 0);
MulMat::set_functions<Q5_1_Unpacker>(mm);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
break;
default:
return false;
}
return true;
}
} // namespace
#else // __aarch64__
namespace {
template <int nrc, typename block_q8 = block_q8_K> struct Q8 {
constexpr static int nrc_y = nrc;
Q8(const DataInfo& info) {
for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8 *)info.src1_row(iy);
}
inline int8x16_t load_quants_16(int iy, int i, int j) const { return vld1q_s8(y[iy][i].qs + 16*j); }
inline int8x16x2_t load_quants(int iy, int i, int j) const { return vld1q_s8_x2(y[iy][i].qs + 32*j); }
inline int8x16x4_t load_quants_64(int iy, int i, int j) const { return vld1q_s8_x4(y[iy][i].qs + 64*j); }
inline int16x8x2_t load_bsums(int iy, int i) const { return vld1q_s16_x2(y[iy][i].bsums); }
inline int16x8_t load_bsums8(int iy, int i) const {
auto q8s = vld1q_s16_x2(y[iy][i].bsums);
return vpaddq_s16(q8s.val[0], q8s.val[1]);
}
inline float scale(int iy, int i) const { return y[iy][i].d; }
const block_q8 * y[nrc_y];
};
template <int nrc_y, typename Dequantizer>
IQK_NOINLINE void mul_mat_qX_K_q8_K_T(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n % QK_K == 0);
const int nb = n / QK_K;
Q8<nrc_y, block_q8_K> q8(info);
Dequantizer deq(vx, bx, nrc_y);
for (int ix = 0; ix < nrc_x; ++ix) {
deq.new_row(ix);
float32x4_t acc[nrc_y];
for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
//#pragma GCC unroll 4
for (int i = 0; i < nb; ++i) {
int32x4_t sumi[nrc_y];
for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = vdupq_n_s32(0);
if constexpr (nrc_y > 1 && Dequantizer::should_scale_quants()) {
deq.process_scales(i, q8, acc);
deq.prepare(i, 0);
deq.compute(q8, i, 0, sumi);
deq.prepare(i, 1);
deq.compute(q8, i, 1, sumi);
} else {
if constexpr (Dequantizer::num_blocks() == 8) {
auto scales = deq.new_block(i, q8, acc);
deq.prepare(i, 0);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
deq.prepare(i, 1);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
}
else if constexpr (Dequantizer::num_blocks() == 16) {
auto scales = deq.new_block(i, q8, acc);
deq.prepare(i, 0);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
deq.prepare(i, 1);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
}
else {
GGML_ASSERT(false);
}
}
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
acc[iy] = vmlaq_f32(acc[iy], vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i)));
}
}
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, vaddvq_f32(acc[iy]));
}
}
}
template <int nrc_y, typename Dequantizer>
IQK_NOINLINE void mul_mat_qX_K_q8_K_IQ(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n % QK_K == 0);
const int nb = n / QK_K;
Q8<nrc_y, block_q8_K> q8(info);
Dequantizer deq(vx, bx, nrc_y);
for (int ix = 0; ix < nrc_x; ++ix) {
deq.new_row(ix);
float32x4_t acc[nrc_y];
for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
for (int i = 0; i < nb; ++i) {
int32x4_t sumi[nrc_y];
for (int iy = 0; iy < nrc_y; ++iy) sumi[iy] = vdupq_n_s32(0);
if constexpr (Dequantizer::num_blocks() == 8) {
auto scales = deq.new_block(i);
deq.prepare(i, 0);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
deq.prepare(i, 1);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_8_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
}
else if constexpr (Dequantizer::num_blocks() == 16) {
auto scales = deq.new_block(i);
deq.prepare(i, 0);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 0, sumi[iy]);
deq.prepare(i, 1);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) compute_16_blocks(deq.bits.b1, deq.bits.b2, q8, scales, iy, i, 1, sumi[iy]);
}
else {
GGML_ASSERT(false);
}
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
acc[iy] = vmlaq_f32(acc[iy], vcvtq_f32_s32(sumi[iy]), vdupq_n_f32(deq.d*q8.scale(iy, i)));
}
}
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, vaddvq_f32(acc[iy]));
}
}
}
template <typename Q8>
IQK_ALWAYS_INLINE void compute_8_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8,
const int32x4x2_t& scales, int iy, int i, int j, int32x4_t& sumi) {
auto mzero = vdupq_n_s32(0);
const int8x16_t * qs_1 = (const int8x16_t *)qx_1.val;
const int8x16_t * qs_2 = (const int8x16_t *)qx_2.val;
auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
auto p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qs_1[0], q8b_1.val[0]), qs_1[1], q8b_1.val[1]); // block 1
auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
auto p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qs_1[2], q8b_2.val[0]), qs_1[3], q8b_2.val[1]); // block 2
auto p12 = vpaddq_s32(p1, p2);
auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
auto p3 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qs_2[0], q8b_3.val[0]), qs_2[1], q8b_3.val[1]); // block 3
auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
auto p4 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qs_2[2], q8b_4.val[0]), qs_2[3], q8b_4.val[1]); // block 4
auto p34 = vpaddq_s32(p3, p4);
auto pall = vpaddq_s32(p12, p34);
sumi = vmlaq_s32(sumi, scales.val[j], pall);
}
template <typename Q8>
IQK_ALWAYS_INLINE void compute_8_blocks(const int8x16_t * qx, const Q8& q8,
const int32x4_t& scales, int iy, int i, int j, int32x4_t& sumi) {
auto mzero = vdupq_n_s32(0);
auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
auto p1 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qx[0], q8b_1.val[0]), qx[1], q8b_1.val[1]); // block 1
auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
auto p2 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qx[2], q8b_2.val[0]), qx[3], q8b_2.val[1]); // block 2
auto p12 = vpaddq_s32(p1, p2);
auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
auto p3 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qx[4], q8b_3.val[0]), qx[5], q8b_3.val[1]); // block 3
auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
auto p4 = ggml_vdotq_s32(ggml_vdotq_s32(mzero, qx[6], q8b_4.val[0]), qx[7], q8b_4.val[1]); // block 4
auto p34 = vpaddq_s32(p3, p4);
auto pall = vpaddq_s32(p12, p34);
sumi = vmlaq_s32(sumi, scales, pall);
}
template <typename Q8>
IQK_ALWAYS_INLINE void compute_16_blocks(const uint8x16x4_t& qx_1, const uint8x16x4_t& qx_2, const Q8& q8,
const int32x4x4_t& scales, int iy, int i, int j, int32x4_t& sumi) {
auto mzero = vdupq_n_s32(0);
auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
auto p1 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[0]), q8b_1.val[0]),
ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[1]), q8b_1.val[1])); // blocks 0, 0, 1, 1,
auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
auto p2 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[2]), q8b_2.val[0]),
ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_1.val[3]), q8b_2.val[1])); // blocks 3, 3, 4, 4,
auto p12 = vpaddq_s32(p1, p2); // blocks 0, 1, 2, 3
sumi = vmlaq_s32(sumi, scales.val[2*j+0], p12);
auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
auto p3 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[0]), q8b_3.val[0]),
ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[1]), q8b_3.val[1])); // block 4, 4, 5, 5,
auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
auto p4 = vpaddq_s32(ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[2]), q8b_4.val[0]),
ggml_vdotq_s32(mzero, vreinterpretq_s8_u8(qx_2.val[3]), q8b_4.val[1])); // block 6, 6, 7, 7,
auto p34 = vpaddq_s32(p3, p4); // blocks 4, 5, 6, 7
sumi = vmlaq_s32(sumi, scales.val[2*j+1], p34);
}
template <typename Q8>
inline void accum_mins_8(const int16x8_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
auto q8s = q8.load_bsums8(iy, i);
int32x4_t b1 = vmull_s16(vget_low_s16(mins), vget_low_s16(q8s));
int32x4_t b2 = vmull_s16(vget_high_s16(mins), vget_high_s16(q8s));
float32x4_t prod = vcvtq_f32_s32(vaddq_s32(b1, b2));
acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i)));
}
}
template <typename Q8>
inline void accum_mins_16(const int16x8x2_t& mins, const Q8& q8, float32x4_t * acc, int i, float c) {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
auto q8s = q8.load_bsums(iy, i);
int32x4_t b1 = vmull_s16(vget_low_s16 (mins.val[0]), vget_low_s16 (q8s.val[0]));
int32x4_t b2 = vmull_s16(vget_high_s16(mins.val[0]), vget_high_s16(q8s.val[0]));
int32x4_t b3 = vmull_s16(vget_low_s16 (mins.val[1]), vget_low_s16 (q8s.val[1]));
int32x4_t b4 = vmull_s16(vget_high_s16(mins.val[1]), vget_high_s16(q8s.val[1]));
float32x4_t prod = vcvtq_f32_s32(vaddq_s32(vaddq_s32(b1, b2), vaddq_s32(b3, b4)));
acc[iy] = vmlaq_f32(acc[iy], prod, vdupq_n_f32(c*q8.scale(iy, i)));
}
}
struct Scales8 {
uint32_t utmp[4];
const uint8_t * sc8 = (const uint8_t *)utmp;
template <typename Q8, typename Qx>
inline int32x4x2_t process_scales_mins(const Qx& x, const Q8& q8, int i, float32x4_t * acc) {
make_q4_scales(x.scales, utmp);
int16x8_t mins = vmovl_s8(vld1_s8((const int8_t *)sc8 + 8));
accum_mins_8(mins, q8, acc, i, -GGML_FP16_TO_FP32(x.dmin));
uint8x8_t scales8 = vld1_u8(sc8);
uint16x8_t scales16 = vmovl_u8(scales8);
int32x4x2_t scales = {vreinterpretq_s32_u32(vmovl_u16(vget_low_u16(scales16))),
vreinterpretq_s32_u32(vmovl_u16(vget_high_u16(scales16)))};
return scales;
}
};
struct Q4bits {
const uint8x16_t m4b = vdupq_n_u8(0xf);
uint8x16x4_t b1, b2;
inline void prepare4(uint8x16x4_t& b, const uint8x16_t * val) const {
b.val[0] = vandq_u8(val[0], m4b);
b.val[2] = vshrq_n_u8(val[0], 4);
b.val[1] = vandq_u8(val[1], m4b);
b.val[3] = vshrq_n_u8(val[1], 4);
}
inline void prepare4_16(uint8x16x4_t& b, const uint8x16_t * val) const {
b.val[0] = vandq_u8(val[0], m4b);
b.val[1] = vshrq_n_u8(val[0], 4);
b.val[2] = vandq_u8(val[1], m4b);
b.val[3] = vshrq_n_u8(val[1], 4);
}
inline void prepare(const uint8_t * qs) {
auto q4bits = vld1q_u8_x2(qs);
prepare4(b1, q4bits.val);
q4bits = vld1q_u8_x2(qs+32);
prepare4(b2, q4bits.val);
}
inline void prepare_v2(const uint8_t * qs) {
auto q4bits = vld1q_u8_x4(qs);
prepare4(b1, q4bits.val+0);
prepare4(b2, q4bits.val+2);
}
inline void prepare64(const uint8_t * qs) {
auto q4bits = vld1q_u8_x4(qs);
b1.val[0] = vandq_u8(q4bits.val[0], m4b);
b1.val[1] = vandq_u8(q4bits.val[1], m4b);
b1.val[2] = vandq_u8(q4bits.val[2], m4b);
b1.val[3] = vandq_u8(q4bits.val[3], m4b);
b2.val[0] = vshrq_n_u8(q4bits.val[0], 4);
b2.val[1] = vshrq_n_u8(q4bits.val[1], 4);
b2.val[2] = vshrq_n_u8(q4bits.val[2], 4);
b2.val[3] = vshrq_n_u8(q4bits.val[3], 4);
}
inline void prepare16(const uint8_t * qs) {
auto q4bits = vld1q_u8_x2(qs);
prepare4_16(b1, q4bits.val);
q4bits = vld1q_u8_x2(qs+32);
prepare4_16(b2, q4bits.val);
}
inline void prepare16_v2(const uint8_t * qs) {
auto q4bits = vld1q_u8_x4(qs);
prepare4_16(b1, q4bits.val+0);
prepare4_16(b2, q4bits.val+2);
}
};
struct Q2bits {
const uint8x16_t m4b = vdupq_n_u8(0x03);
uint8x16x4_t b1, b2;
inline void prepare(const uint8_t * qs) {
auto q2bits = vld1q_u8_x2(qs);
b1.val[0] = vandq_u8(q2bits.val[0], m4b);
b1.val[1] = vandq_u8(q2bits.val[1], m4b);
q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
b1.val[2] = vandq_u8(q2bits.val[0], m4b);
b1.val[3] = vandq_u8(q2bits.val[1], m4b);
q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
b2.val[0] = vandq_u8(q2bits.val[0], m4b);
b2.val[1] = vandq_u8(q2bits.val[1], m4b);
q2bits.val[0] = vshrq_n_u8(q2bits.val[0], 2);
q2bits.val[1] = vshrq_n_u8(q2bits.val[1], 2);
b2.val[2] = vandq_u8(q2bits.val[0], m4b);
b2.val[3] = vandq_u8(q2bits.val[1], m4b);
}
};
template <typename block_q>
struct BaseDequantizer {
BaseDequantizer(const void * vx, size_t bx, int nrc) : vx(vx), x(nullptr), bx(bx), nrc(nrc) {}
inline void new_row(int ix) { x = (const block_q *)((const char *)vx + ix*bx); }
const void * vx;
const block_q * x;
const size_t bx;
const int nrc;
};
struct DequantizerQ4K final : public BaseDequantizer<block_q4_K> {
DequantizerQ4K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 8; }
constexpr static bool should_scale_quants() { return false; }
template <typename Q8>
inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
d = GGML_FP16_TO_FP32(x[i].d);
return s8.process_scales_mins(x[i], q8, i, acc);
}
inline void prepare(int i, int j) {
if (nrc == 1) bits.prepare_v2(x[i].qs+64*j);
else bits.prepare(x[i].qs+64*j);
}
Q4bits bits;
Scales8 s8;
float d;
};
struct HighBit5 {
const uint8x16_t mhb = vdupq_n_u8(0x10);
uint8x16x2_t bits;
inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) {
b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 4), mhb));
b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 4), mhb));
b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 3), mhb));
b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 3), mhb));
b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb));
b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb));
b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb));
b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb));
if (do_shift) {
bits.val[0] = vshrq_n_u8(bits.val[0], 4);
bits.val[1] = vshrq_n_u8(bits.val[1], 4);
}
}
};
struct HighBit3 {
const uint8x16_t mhb = vdupq_n_u8(0x04);
uint8x16x2_t bits;
inline void apply(uint8x16x4_t& b1, uint8x16x4_t& b2, bool do_shift) {
b1.val[0] = vorrq_u8(b1.val[0], vandq_u8(vshlq_n_u8(bits.val[0], 2), mhb));
b1.val[1] = vorrq_u8(b1.val[1], vandq_u8(vshlq_n_u8(bits.val[1], 2), mhb));
b1.val[2] = vorrq_u8(b1.val[2], vandq_u8(vshlq_n_u8(bits.val[0], 1), mhb));
b1.val[3] = vorrq_u8(b1.val[3], vandq_u8(vshlq_n_u8(bits.val[1], 1), mhb));
b2.val[0] = vorrq_u8(b2.val[0], vandq_u8(bits.val[0], mhb));
b2.val[1] = vorrq_u8(b2.val[1], vandq_u8(bits.val[1], mhb));
b2.val[2] = vorrq_u8(b2.val[2], vandq_u8(vshrq_n_u8(bits.val[0], 1), mhb));
b2.val[3] = vorrq_u8(b2.val[3], vandq_u8(vshrq_n_u8(bits.val[1], 1), mhb));
if (do_shift) {
bits.val[0] = vshrq_n_u8(bits.val[0], 4);
bits.val[1] = vshrq_n_u8(bits.val[1], 4);
}
}
};
struct DequantizerQ5K final : public BaseDequantizer<block_q5_K> {
DequantizerQ5K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 8; }
constexpr static bool should_scale_quants() { return false; }
template <typename Q8>
inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
d = GGML_FP16_TO_FP32(x[i].d);
h.bits = vld1q_u8_x2(x[i].qh);
return s8.process_scales_mins(x[i], q8, i, acc);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs+64*j);
h.apply(bits.b1, bits.b2, j == 0);
}
Q4bits bits;
HighBit5 h;
Scales8 s8;
uint8x16x2_t hbits;
float d;
};
inline int32x4x4_t make_wider(const int16x8x2_t& scales16) {
int32x4x4_t scales = {
vmovl_s16(vget_low_s16 (scales16.val[0])),
vmovl_s16(vget_high_s16(scales16.val[0])),
vmovl_s16(vget_low_s16 (scales16.val[1])),
vmovl_s16(vget_high_s16(scales16.val[1])),
};
return scales;
}
template <typename Q8>
inline int32x4x4_t process_scales_mins_16(const int8x16_t& scales8, const Q8& q8, float32x4_t * acc, int i, float c) {
int16x8x2_t scales16;
scales16.val[0] = vmovl_s8(vget_low_s8(scales8));
scales16.val[1] = vmovl_s8(vget_high_s8(scales8));
accum_mins_16(scales16, q8, acc, i, c);
return make_wider(scales16);
}
struct DequantizerQ6K final : public BaseDequantizer<block_q6_K> {
DequantizerQ6K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 16; }
constexpr static bool should_scale_quants() { return false; }
template <typename Q8>
inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
d = GGML_FP16_TO_FP32(x[i].d);
return process_scales_mins_16(vld1q_s8(x[i].scales), q8, acc, i, -32.f*d);
}
inline void prepare(int i, int j) {
auto hbits = vld1q_u8_x2(x[i].qh + 32*j);
bits.prepare64(x[i].ql+64*j);
bits.b1.val[0] = vorrq_u8(bits.b1.val[0], vandq_u8(vshlq_n_u8(hbits.val[0], 4), mhb));
bits.b1.val[1] = vorrq_u8(bits.b1.val[1], vandq_u8(vshlq_n_u8(hbits.val[1], 4), mhb));
bits.b1.val[2] = vorrq_u8(bits.b1.val[2], vandq_u8(vshlq_n_u8(hbits.val[0], 2), mhb));
bits.b1.val[3] = vorrq_u8(bits.b1.val[3], vandq_u8(vshlq_n_u8(hbits.val[1], 2), mhb));
bits.b2.val[0] = vorrq_u8(bits.b2.val[0], vandq_u8(hbits.val[0], mhb));
bits.b2.val[1] = vorrq_u8(bits.b2.val[1], vandq_u8(hbits.val[1], mhb));
bits.b2.val[2] = vorrq_u8(bits.b2.val[2], vandq_u8(vshrq_n_u8(hbits.val[0], 2), mhb));
bits.b2.val[3] = vorrq_u8(bits.b2.val[3], vandq_u8(vshrq_n_u8(hbits.val[1], 2), mhb));
}
Q4bits bits;
const uint8x16_t mhb = vdupq_n_u8(0x30);
float d;
};
struct DequantizerQ3K final : public BaseDequantizer<block_q3_K> {
DequantizerQ3K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 16; }
constexpr static bool should_scale_quants() { return false; }
template <typename Q8>
inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
d = GGML_FP16_TO_FP32(x[i].d);
h.bits = vld1q_u8_x2(x[i].hmask);
const uint16_t * sc16 = (const uint16_t *)x[i].scales;
uint32_t aux0 = sc16[0] | (sc16[1] << 16);
uint32_t aux1 = sc16[2] | (sc16[3] << 16);
uint32_t aux2 = sc16[4] | (sc16[5] << 16);
aux32[0] = (aux0 & 0x0f0f0f0f) | ((aux2 << 4) & 0x30303030);
aux32[1] = (aux1 & 0x0f0f0f0f) | ((aux2 << 2) & 0x30303030);
aux32[2] = ((aux0 >> 4) & 0x0f0f0f0f) | ((aux2 >> 0) & 0x30303030);
aux32[3] = ((aux1 >> 4) & 0x0f0f0f0f) | ((aux2 >> 2) & 0x30303030);
return process_scales_mins_16(vaddq_s8(vld1q_s8((const int8_t *)aux32), vdupq_n_s8(-32)), q8, acc, i, -4.f*d);
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs+32*j);
h.apply(bits.b1, bits.b2, j == 0);
}
uint32_t aux32[4];
Q2bits bits;
HighBit3 h;
float d;
};
struct DequantizerQ2K final : public BaseDequantizer<block_q2_K> {
DequantizerQ2K(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 16; }
constexpr static bool should_scale_quants() { return true; }
template <typename Q8>
inline void process_scales(int i, const Q8& q8, float32x4_t * acc) {
d = GGML_FP16_TO_FP32(x[i].d);
auto scales_and_mins = vld1q_u8(x[i].scales);
auto mins8 = vreinterpretq_s8_u8(vshrq_n_u8(scales_and_mins, 4));
int16x8x2_t scales16;
scales16.val[0] = vmovl_s8(vget_low_s8(mins8));
scales16.val[1] = vmovl_s8(vget_high_s8(mins8));
accum_mins_16(scales16, q8, acc, i, -GGML_FP16_TO_FP32(x[i].dmin));
scales8 = vandq_u8(scales_and_mins, vdupq_n_u8(0xf));
}
template <typename Q8>
inline int32x4x4_t new_block(int i, const Q8& q8, float32x4_t * acc) {
process_scales(i, q8, acc);
int16x8x2_t scales16;
scales16.val[0] = vmovl_s8(vget_low_s8(vreinterpretq_s8_u8(scales8)));
scales16.val[1] = vmovl_s8(vget_high_s8(vreinterpretq_s8_u8(scales8)));
return make_wider(scales16);
}
template <typename Q8>
inline void compute(const Q8& q8, int i, int j, int32x4_t * sumi) {
auto m1 = vdupq_n_u8(1);
auto shuffle = vdupq_n_u8(8*j);
bits.b1.val[0] = vmulq_u8(bits.b1.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b1.val[1] = vmulq_u8(bits.b1.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b1.val[2] = vmulq_u8(bits.b1.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b1.val[3] = vmulq_u8(bits.b1.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b2.val[0] = vmulq_u8(bits.b2.val[0], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b2.val[1] = vmulq_u8(bits.b2.val[1], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b2.val[2] = vmulq_u8(bits.b2.val[2], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
bits.b2.val[3] = vmulq_u8(bits.b2.val[3], vqtbl1q_u8(scales8, shuffle)); shuffle = vaddq_u8(shuffle, m1);
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
auto q8b_1 = q8.load_quants(iy, i, 4*j+0);
sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[0]), q8b_1.val[0]),
vreinterpretq_s8_u8(bits.b1.val[1]), q8b_1.val[1]);
auto q8b_2 = q8.load_quants(iy, i, 4*j+1);
sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b1.val[2]), q8b_2.val[0]),
vreinterpretq_s8_u8(bits.b1.val[3]), q8b_2.val[1]);
auto q8b_3 = q8.load_quants(iy, i, 4*j+2);
sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[0]), q8b_3.val[0]),
vreinterpretq_s8_u8(bits.b2.val[1]), q8b_3.val[1]);
auto q8b_4 = q8.load_quants(iy, i, 4*j+3);
sumi[iy] = ggml_vdotq_s32(ggml_vdotq_s32(sumi[iy], vreinterpretq_s8_u8(bits.b2.val[2]), q8b_4.val[0]),
vreinterpretq_s8_u8(bits.b2.val[3]), q8b_4.val[1]);
}
}
inline void prepare(int i, int j) {
bits.prepare(x[i].qs+32*j);
}
uint32_t aux32[4];
uint8x16_t scales8;
Q2bits bits;
float d;
};
// ============================= i-quants
struct DequantizerIQ4XS final : public BaseDequantizer<block_iq4_xs> {
static int8x16_t load_values() {
static const int8_t iq4nl_values[16] = {-127, -104, -83, -65, -49, -35, -22, -10, 1, 13, 25, 38, 53, 69, 89, 113};
return vld1q_s8(iq4nl_values);
}
DequantizerIQ4XS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc), values(load_values()) {}
constexpr static int num_blocks() { return 8; }
constexpr static bool should_scale_quants() { return false; }
inline void new_row(int ix) { x = (const block_iq4_xs *)((const char *)vx + bx*ix); }
template <typename Q8>
inline int32x4x2_t new_block(int i, const Q8& q8, float32x4_t * acc) {
(void)q8;
(void)acc;
d = GGML_FP16_TO_FP32(x[i].d);
const uint16_t scales_h = x[i].scales_h;
const uint16_t * scales_l = (const uint16_t *)x[i].scales_l;
aux32[0] = scales_l[0] | (scales_l[1] << 16);
aux32[1] = aux32[0] >> 4;
// scl is ordered as 0, 2, 4, 6, 1, 3, 5, 7
uint8x8_t scl8 = vand_u8(vld1_u8((const uint8_t *)aux32), vdup_n_u8(0xf));
uint16_t * aux16 = (uint16_t *)aux32;
aux16[0] = scales_h << 4; aux16[1] = scales_h << 2; aux16[2] = scales_h; aux16[3] = scales_h >> 2;
// sch is ordered as 0, 4, 1, 5, 2, 6, 3, 7
uint8x8_t sch8 = vand_u8(vld1_u8((const uint8_t *)aux16), vdup_n_u8(0x30));
int8x8_t scales8 = vadd_s8(vreinterpret_s8_u8(vorr_u8(scl8, vtbl1_u8(sch8, vreinterpret_u8_u32(hshuff)))), vdup_n_s8(-32));
// shuffle 0, 2, 4, 6, 1, 3, 5, 7 -> 0, 1, 2, 3, 4, 5, 6, 7
scales8 = vtbl1_s8(scales8, vreinterpret_s8_u32(hshuff));
int16x8_t scales16 = vmovl_s8(scales8);
int32x4x2_t scales = {vmovl_s16(vget_low_s16(scales16)), vmovl_s16(vget_high_s16(scales16))};
return scales;
}
inline void prepare(int i, int j) {
bits.prepare16(x[i].qs+64*j);
for (int k = 0; k < 4; ++k) {
bits.b1.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b1.val[k]));
bits.b2.val[k] = vreinterpretq_u8_s8(vqtbl1q_s8(values, bits.b2.val[k]));
}
}
Q4bits bits;
const int8x16_t values;
uint32_t aux32[2];
constexpr static uint32x2_t hshuff = {0x05010400, 0x07030602};
float d;
};
struct SimpleBits {
uint8x16x4_t b1;
uint8x16x4_t b2;
};
IQK_ALWAYS_INLINE int32x4x2_t prepare_scales_8(const uint32x4_t& v1, const uint32x4_t& v2) {
int32x4x2_t scales;
auto one = vdupq_n_u32(1);
scales.val[0] = vreinterpretq_s32_u32(vsliq_n_u32(one, vshrq_n_u32(v1, 28), 1));
scales.val[1] = vreinterpretq_s32_u32(vsliq_n_u32(one, vshrq_n_u32(v2, 28), 1));
return scales;
}
inline void apply_signs_2(uint8x16_t * b, const uint64_t * signs, uint32_t sidx) {
auto s1 = vcombine_s8(vld1_s8((const int8_t *)(signs + ((sidx >> 0) & 127))), vld1_s8((const int8_t *)(signs + ((sidx >> 7) & 127))));
auto s2 = vcombine_s8(vld1_s8((const int8_t *)(signs + ((sidx >>14) & 127))), vld1_s8((const int8_t *)(signs + ((sidx >>21) & 127))));
b[0] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[0]), s1));
b[1] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[1]), s2));
}
IQK_ALWAYS_INLINE int32x4_t prepare_scales_8(const uint32x4_t& v1) {
return vreinterpretq_s32_u32(vsliq_n_u32(vdupq_n_u32(1), vshrq_n_u32(v1, 28), 1));
}
struct DequantizerIQ2XXS final : public BaseDequantizer<block_iq2_xxs> {
DequantizerIQ2XXS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
IQK_ALWAYS_INLINE float new_block(int i) const { return 0.125f * GGML_FP16_TO_FP32(x[i].d); }
inline int32x4_t unpack(int i, int j, uint8x16_t * q) const {
auto data = vld1q_u32_x2((const uint32_t *)(x[i].qs + 16*j));
prepare_all(data, q);
return prepare_scales_8(vuzp2q_u32(data.val[0], data.val[1]));
}
private:
static inline void prepare2(uint8x16_t * b, const uint32_t * bits, const uint64_t * signs) {
const uint8_t * idx = (const uint8_t *)bits;
b[0] = vreinterpretq_u8_u64(uint64x2_t{iq2xxs_grid[idx[0]], iq2xxs_grid[idx[1]]});
b[1] = vreinterpretq_u8_u64(uint64x2_t{iq2xxs_grid[idx[2]], iq2xxs_grid[idx[3]]});
apply_signs_2(b, signs, bits[1]);
}
inline static void prepare_all(const uint32x4x2_t& data, uint8x16_t * quants) {
const uint32_t * q2 = (const uint32_t *)data.val;
prepare2(quants+0, q2+0, keven_signs);
prepare2(quants+2, q2+2, keven_signs);
prepare2(quants+4, q2+4, keven_signs);
prepare2(quants+6, q2+6, keven_signs);
}
};
inline int32x4x4_t prepare_4bit_scales16(const uint8_t * sc) {
auto aux = vld1_u8(sc);
auto scales_l = vand_u8(aux, vdup_n_u8(0xf));
auto scales_h = vshr_n_u8(aux, 4);
auto aux1 = vcombine_u8(vzip1_u8(scales_l, scales_h), vzip2_u8(scales_l, scales_h));
auto scales8 = vreinterpretq_s8_u8(vorrq_u8(vshlq_n_u8(aux1, 1), vdupq_n_u8(1)));
int16x8x2_t scales16 = { vmovl_s8(vget_low_s8(scales8)), vmovl_s8(vget_high_s8(scales8)) };
return make_wider(scales16);
}
struct DequantizerIQ2XS final : public BaseDequantizer<block_iq2_xs> {
DequantizerIQ2XS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 16; }
constexpr static bool should_scale_quants() { return false; }
SimpleBits bits;
float d;
inline int32x4x4_t new_block(int i) {
d = 0.125f * GGML_FP16_TO_FP32(x[i].d);
prepare_internal(i, 0);
return prepare_4bit_scales16(x[i].scales);
}
inline void prepare(int i, int j) {
if (j == 1) prepare_internal(i, 1);
}
private:
static void make2(const uint16_t * qs, uint8x16_t * b) {
auto v1 = vcombine_s8(vld1_s8((const int8_t *)(iq2xs_grid + (qs[0] & 511))), vld1_s8((const int8_t *)(iq2xs_grid + (qs[1] & 511))));
auto v2 = vcombine_s8(vld1_s8((const int8_t *)(iq2xs_grid + (qs[2] & 511))), vld1_s8((const int8_t *)(iq2xs_grid + (qs[3] & 511))));
auto s1 = vcombine_s8(vld1_s8((const int8_t *)(keven_signs + (qs[0] >> 9))), vld1_s8((const int8_t *)(keven_signs + (qs[1] >> 9))));
auto s2 = vcombine_s8(vld1_s8((const int8_t *)(keven_signs + (qs[2] >> 9))), vld1_s8((const int8_t *)(keven_signs + (qs[3] >> 9))));
b[0] = vreinterpretq_u8_s8(vmulq_s8(v1, s1));
b[1] = vreinterpretq_u8_s8(vmulq_s8(v2, s2));
}
inline static void make4(const uint16_t * qs, uint8x16_t * b) {
make2(qs + 0, b + 0);
make2(qs + 4, b + 2);
}
IQK_ALWAYS_INLINE void prepare_internal(int i, int j) {
make4(x[i].qs + 16*j + 0, bits.b1.val);
make4(x[i].qs + 16*j + 8, bits.b2.val);
}
};
// So, I hate to include this table, but with the GCC 12.3 compiler
// bundled in the Cosmopolitan tools, loading the unpacked sign bytes
// from this table using the packed 8 sign bits as index is faster than
// using the standard trick of vceqq_u8(vandq_u8(bits, mask), mask) to
// expand the bits to bytes.
static const uint64_t kall_signs[256] = {
0x0101010101010101, 0x01010101010101ff, 0x010101010101ff01, 0x010101010101ffff,
0x0101010101ff0101, 0x0101010101ff01ff, 0x0101010101ffff01, 0x0101010101ffffff,
0x01010101ff010101, 0x01010101ff0101ff, 0x01010101ff01ff01, 0x01010101ff01ffff,
0x01010101ffff0101, 0x01010101ffff01ff, 0x01010101ffffff01, 0x01010101ffffffff,
0x010101ff01010101, 0x010101ff010101ff, 0x010101ff0101ff01, 0x010101ff0101ffff,
0x010101ff01ff0101, 0x010101ff01ff01ff, 0x010101ff01ffff01, 0x010101ff01ffffff,
0x010101ffff010101, 0x010101ffff0101ff, 0x010101ffff01ff01, 0x010101ffff01ffff,
0x010101ffffff0101, 0x010101ffffff01ff, 0x010101ffffffff01, 0x010101ffffffffff,
0x0101ff0101010101, 0x0101ff01010101ff, 0x0101ff010101ff01, 0x0101ff010101ffff,
0x0101ff0101ff0101, 0x0101ff0101ff01ff, 0x0101ff0101ffff01, 0x0101ff0101ffffff,
0x0101ff01ff010101, 0x0101ff01ff0101ff, 0x0101ff01ff01ff01, 0x0101ff01ff01ffff,
0x0101ff01ffff0101, 0x0101ff01ffff01ff, 0x0101ff01ffffff01, 0x0101ff01ffffffff,
0x0101ffff01010101, 0x0101ffff010101ff, 0x0101ffff0101ff01, 0x0101ffff0101ffff,
0x0101ffff01ff0101, 0x0101ffff01ff01ff, 0x0101ffff01ffff01, 0x0101ffff01ffffff,
0x0101ffffff010101, 0x0101ffffff0101ff, 0x0101ffffff01ff01, 0x0101ffffff01ffff,
0x0101ffffffff0101, 0x0101ffffffff01ff, 0x0101ffffffffff01, 0x0101ffffffffffff,
0x01ff010101010101, 0x01ff0101010101ff, 0x01ff01010101ff01, 0x01ff01010101ffff,
0x01ff010101ff0101, 0x01ff010101ff01ff, 0x01ff010101ffff01, 0x01ff010101ffffff,
0x01ff0101ff010101, 0x01ff0101ff0101ff, 0x01ff0101ff01ff01, 0x01ff0101ff01ffff,
0x01ff0101ffff0101, 0x01ff0101ffff01ff, 0x01ff0101ffffff01, 0x01ff0101ffffffff,
0x01ff01ff01010101, 0x01ff01ff010101ff, 0x01ff01ff0101ff01, 0x01ff01ff0101ffff,
0x01ff01ff01ff0101, 0x01ff01ff01ff01ff, 0x01ff01ff01ffff01, 0x01ff01ff01ffffff,
0x01ff01ffff010101, 0x01ff01ffff0101ff, 0x01ff01ffff01ff01, 0x01ff01ffff01ffff,
0x01ff01ffffff0101, 0x01ff01ffffff01ff, 0x01ff01ffffffff01, 0x01ff01ffffffffff,
0x01ffff0101010101, 0x01ffff01010101ff, 0x01ffff010101ff01, 0x01ffff010101ffff,
0x01ffff0101ff0101, 0x01ffff0101ff01ff, 0x01ffff0101ffff01, 0x01ffff0101ffffff,
0x01ffff01ff010101, 0x01ffff01ff0101ff, 0x01ffff01ff01ff01, 0x01ffff01ff01ffff,
0x01ffff01ffff0101, 0x01ffff01ffff01ff, 0x01ffff01ffffff01, 0x01ffff01ffffffff,
0x01ffffff01010101, 0x01ffffff010101ff, 0x01ffffff0101ff01, 0x01ffffff0101ffff,
0x01ffffff01ff0101, 0x01ffffff01ff01ff, 0x01ffffff01ffff01, 0x01ffffff01ffffff,
0x01ffffffff010101, 0x01ffffffff0101ff, 0x01ffffffff01ff01, 0x01ffffffff01ffff,
0x01ffffffffff0101, 0x01ffffffffff01ff, 0x01ffffffffffff01, 0x01ffffffffffffff,
0xff01010101010101, 0xff010101010101ff, 0xff0101010101ff01, 0xff0101010101ffff,
0xff01010101ff0101, 0xff01010101ff01ff, 0xff01010101ffff01, 0xff01010101ffffff,
0xff010101ff010101, 0xff010101ff0101ff, 0xff010101ff01ff01, 0xff010101ff01ffff,
0xff010101ffff0101, 0xff010101ffff01ff, 0xff010101ffffff01, 0xff010101ffffffff,
0xff0101ff01010101, 0xff0101ff010101ff, 0xff0101ff0101ff01, 0xff0101ff0101ffff,
0xff0101ff01ff0101, 0xff0101ff01ff01ff, 0xff0101ff01ffff01, 0xff0101ff01ffffff,
0xff0101ffff010101, 0xff0101ffff0101ff, 0xff0101ffff01ff01, 0xff0101ffff01ffff,
0xff0101ffffff0101, 0xff0101ffffff01ff, 0xff0101ffffffff01, 0xff0101ffffffffff,
0xff01ff0101010101, 0xff01ff01010101ff, 0xff01ff010101ff01, 0xff01ff010101ffff,
0xff01ff0101ff0101, 0xff01ff0101ff01ff, 0xff01ff0101ffff01, 0xff01ff0101ffffff,
0xff01ff01ff010101, 0xff01ff01ff0101ff, 0xff01ff01ff01ff01, 0xff01ff01ff01ffff,
0xff01ff01ffff0101, 0xff01ff01ffff01ff, 0xff01ff01ffffff01, 0xff01ff01ffffffff,
0xff01ffff01010101, 0xff01ffff010101ff, 0xff01ffff0101ff01, 0xff01ffff0101ffff,
0xff01ffff01ff0101, 0xff01ffff01ff01ff, 0xff01ffff01ffff01, 0xff01ffff01ffffff,
0xff01ffffff010101, 0xff01ffffff0101ff, 0xff01ffffff01ff01, 0xff01ffffff01ffff,
0xff01ffffffff0101, 0xff01ffffffff01ff, 0xff01ffffffffff01, 0xff01ffffffffffff,
0xffff010101010101, 0xffff0101010101ff, 0xffff01010101ff01, 0xffff01010101ffff,
0xffff010101ff0101, 0xffff010101ff01ff, 0xffff010101ffff01, 0xffff010101ffffff,
0xffff0101ff010101, 0xffff0101ff0101ff, 0xffff0101ff01ff01, 0xffff0101ff01ffff,
0xffff0101ffff0101, 0xffff0101ffff01ff, 0xffff0101ffffff01, 0xffff0101ffffffff,
0xffff01ff01010101, 0xffff01ff010101ff, 0xffff01ff0101ff01, 0xffff01ff0101ffff,
0xffff01ff01ff0101, 0xffff01ff01ff01ff, 0xffff01ff01ffff01, 0xffff01ff01ffffff,
0xffff01ffff010101, 0xffff01ffff0101ff, 0xffff01ffff01ff01, 0xffff01ffff01ffff,
0xffff01ffffff0101, 0xffff01ffffff01ff, 0xffff01ffffffff01, 0xffff01ffffffffff,
0xffffff0101010101, 0xffffff01010101ff, 0xffffff010101ff01, 0xffffff010101ffff,
0xffffff0101ff0101, 0xffffff0101ff01ff, 0xffffff0101ffff01, 0xffffff0101ffffff,
0xffffff01ff010101, 0xffffff01ff0101ff, 0xffffff01ff01ff01, 0xffffff01ff01ffff,
0xffffff01ffff0101, 0xffffff01ffff01ff, 0xffffff01ffffff01, 0xffffff01ffffffff,
0xffffffff01010101, 0xffffffff010101ff, 0xffffffff0101ff01, 0xffffffff0101ffff,
0xffffffff01ff0101, 0xffffffff01ff01ff, 0xffffffff01ffff01, 0xffffffff01ffffff,
0xffffffffff010101, 0xffffffffff0101ff, 0xffffffffff01ff01, 0xffffffffff01ffff,
0xffffffffffff0101, 0xffffffffffff01ff, 0xffffffffffffff01, 0xffffffffffffffff,
};
struct SignHelper {
IQK_ALWAYS_INLINE void apply_signs_1x(uint8x16_t * b, const uint8_t * sign_bits) const {
auto s = vreinterpretq_s8_u64(uint64x2_t{kall_signs[sign_bits[0]], kall_signs[sign_bits[1]]});
// Normally we would expect this to be faster, but it isn't.
// auto aux = vcombine_u8(vdup_n_u8(sign_bits[0]), vdup_n_u8(sign_bits[1]));
// auto s = vreinterpretq_s8_u8(vorrq_u8(vceqq_u8(vandq_u8(aux, smask), smask), m1));
b[0] = vreinterpretq_u8_s8(vmulq_s8(vreinterpretq_s8_u8(b[0]), s));
}
// We would need these two if we weren't loading from the unpacked sign table.
//const uint8x16_t smask = vreinterpretq_u8_u64(vdupq_n_u64(0x8040201008040201));
//const uint8x16_t m1 = vdupq_n_u8(1);
};
struct DequantizerIQ2S final : public BaseDequantizer<block_iq2_s> {
DequantizerIQ2S(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 16; }
constexpr static bool should_scale_quants() { return false; }
SimpleBits bits;
float d;
inline int32x4x4_t new_block(int i) {
d = 0.125f * GGML_FP16_TO_FP32(x[i].d);
prepare_internal(i, 0, bits);
return prepare_4bit_scales16(x[i].scales);
}
inline void prepare(int i, int j) {
if (j == 1) prepare_internal(i, 1, bits);
}
private:
static void make4(const SignHelper& sh, const uint8_t * sign_bits, const uint8_t * qs, const uint8_t * qh, uint8x16_t * b) {
uint32_t aux32[2];
const uint16_t * aux16 = (const uint16_t *)aux32;
for (int k = 0; k < 2; ++k) {
aux32[1] = (qh[k] << 4) | (qh[k] << 18);
aux32[0] = (aux32[1] << 4) & 0x03000300;
aux32[1] &= 0x03000300;
b[2*k+0] = vcombine_u8(vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+0] | aux16[0]))),
vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+1] | aux16[1]))));
b[2*k+1] = vcombine_u8(vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+2] | aux16[2]))),
vld1_u8((const uint8_t *)(iq2s_grid + (qs[4*k+3] | aux16[3]))));
sh.apply_signs_1x(b+2*k+0, sign_bits); sign_bits += 2;
sh.apply_signs_1x(b+2*k+1, sign_bits); sign_bits += 2;
}
}
void prepare_internal(int i, int j, SimpleBits& sb) {
const auto * qs = x[i].qs + 16*j;
const auto * qh = x[i].qh + 4*j;
const auto * sign_bits = qs + QK_K/8;
make4(sh, sign_bits+0, qs+0, qh+0, sb.b1.val);
make4(sh, sign_bits+8, qs+8, qh+2, sb.b2.val);
}
SignHelper sh;
};
struct DequantizerIQ3XXS final : public BaseDequantizer<block_iq3_xxs> {
DequantizerIQ3XXS(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
IQK_ALWAYS_INLINE float new_block(int i) const { return 0.25f * GGML_FP16_TO_FP32(x[i].d); }
inline int32x4_t unpack(int i, int j, uint8x16_t * q) const {
auto q3data = vld1q_u8_x2(x[i].qs + 32*j);
auto gas = vld1q_u32((const uint32_t *)(x[i].qs + QK_K/4 + 16*j));
prepare_block((const uint8_t *)q3data.val, (const uint32_t *)&gas, q);
return prepare_scales_8(gas);
}
private:
inline static void make2(const uint8_t * q3, const uint32_t sidx, uint8x16_t * b) {
b[0] = vreinterpretq_u8_u32(uint32x4_t{iq3xxs_grid[q3[0]], iq3xxs_grid[q3[1]], iq3xxs_grid[q3[2]], iq3xxs_grid[q3[3]]});
b[1] = vreinterpretq_u8_u32(uint32x4_t{iq3xxs_grid[q3[4]], iq3xxs_grid[q3[5]], iq3xxs_grid[q3[6]], iq3xxs_grid[q3[7]]});
apply_signs_2(b, keven_signs, sidx);
}
inline static void prepare_block(const uint8_t * q3, const uint32_t * signs, uint8x16_t * quants) {
make2(q3+ 0, signs[0], quants + 0);
make2(q3+ 8, signs[1], quants + 2);
make2(q3+16, signs[2], quants + 4);
make2(q3+24, signs[3], quants + 6);
}
};
struct DequantizerIQ3S final : public BaseDequantizer<block_iq3_s> {
DequantizerIQ3S(const void * vx, size_t bx, int nrc) : BaseDequantizer(vx, bx, nrc) {}
constexpr static int num_blocks() { return 8; }
constexpr static bool should_scale_quants() { return false; }
SimpleBits bits;
float d;
inline int32x4x2_t new_block(int i) {
d = GGML_FP16_TO_FP32(x[i].d);
uint32_t scales32[2];
auto qs = vld1q_u8_x2(x[i].qs);
auto signs = vld1q_u8(x[i].signs);
prepare_block((const uint8_t *)qs.val, x[i].qh, (const uint8_t *)&signs);
std::memcpy(scales32, x[i].scales, 4);
scales32[1] = (((scales32[0] >> 4) & 0x0f0f0f0f) << 1) | 0x01010101;
scales32[0] = ((scales32[0] & 0x0f0f0f0f) << 1) | 0x01010101;
auto scales8 = vld1_u8((const uint8_t *)scales32); // 0, 2, 4, 6, 1, 3, 5, 7
scales8 = vtbl1_u8(scales8, vreinterpret_u8_u64(vdup_n_u64(0x0703060205010400)));
auto scales16 = vreinterpretq_s16_u16(vmovl_u8(scales8));
int32x4x2_t scales;
scales.val[0] = vmovl_s16(vget_low_s16(scales16));
scales.val[1] = vmovl_s16(vget_high_s16(scales16));
return scales;
}
inline void prepare(int i, int j) {
if (j == 1) {
auto qs = vld1q_u8_x2(x[i].qs + 32);
auto signs = vld1q_u8(x[i].signs + 16);
prepare_block((const uint8_t *)qs.val, x[i].qh + 4, (const uint8_t *)&signs);
}
}
private:
static inline void make2(const SignHelper& sh, const uint8_t * sign_bits, const uint16x8_t& idx_l, uint8_t qh,
const int16x8_t& hshift, uint8x16_t * b) {
auto vindex = vorrq_u16(idx_l, vandq_u16(vshlq_u16(vdupq_n_u16(qh), hshift), vdupq_n_u16(256)));
const uint16_t * idx = (const uint16_t *)&vindex;
b[0] = vreinterpretq_u8_u32(uint32x4_t{iq3s_grid[idx[0]], iq3s_grid[idx[1]], iq3s_grid[idx[2]], iq3s_grid[idx[3]]});
sh.apply_signs_1x(b+0, sign_bits+0);
b[1] = vreinterpretq_u8_u32(uint32x4_t{iq3s_grid[idx[4]], iq3s_grid[idx[5]], iq3s_grid[idx[6]], iq3s_grid[idx[7]]});
sh.apply_signs_1x(b+1, sign_bits+2);
}
static inline void make4(const SignHelper& sh, const uint8_t * sign_bits, const uint8_t * qs, const uint8_t * qh,
const int16x8_t& hshift, uint8x16_t * b) {
auto idx_l = vld1q_u8(qs);
make2(sh, sign_bits+0, vmovl_u8(vget_low_u8 (idx_l)), qh[0], hshift, b+0);
make2(sh, sign_bits+4, vmovl_u8(vget_high_u8(idx_l)), qh[1], hshift, b+2);
}
static int16x8_t load_shift() {
static const int16_t k_shift[8] = {8, 7, 6, 5, 4, 3, 2, 1};
return vld1q_s16(k_shift);
}
inline void prepare_block(const uint8_t * qs, const uint8_t * qh, const uint8_t * sign_bits) {
auto signs = vld1q_u8(sign_bits);
auto s = (const uint8_t *)&signs;
make4(sh, s + 0, qs+ 0, qh+0, hshift, bits.b1.val);
make4(sh, s + 8, qs+16, qh+2, hshift, bits.b2.val);
}
SignHelper sh;
const int16x8_t hshift = load_shift();
};
template <int nrc_y, typename Dequantizer>
IQK_NOINLINE void mul_mat_qX_K_q8_K_IQXXS(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
assert(n % QK_K == 0);
const int nb = n / QK_K;
Q8<nrc_y, block_q8_K> q8(info);
Dequantizer deq(vx, bx, nrc_y);
uint8x16_t qx[8];
int32x4_t sumi[nrc_y];
float32x4_t acc[nrc_y];
for (int ix = 0; ix < nrc_x; ++ix) {
deq.new_row(ix);
for (int iy = 0; iy < nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
for (int i = 0; i < nb; ++i) {
float d = deq.new_block(i);
auto scales = deq.unpack(i, 0, qx);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
sumi[iy] = vdupq_n_s32(0);
compute_8_blocks((const int8x16_t *)qx, q8, scales, iy, i, 0, sumi[iy]);
}
scales = deq.unpack(i, 1, qx);
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
compute_8_blocks((const int8x16_t *)qx, q8, scales, iy, i, 1, sumi[iy]);
acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*q8.scale(iy, i)), vcvtq_f32_s32(sumi[iy]));
}
}
#pragma GCC unroll 8
for (int iy = 0; iy < nrc_y; ++iy) {
info.store(ix, iy, vaddvq_f32(acc[iy]));
}
}
}
// =========================================== Legacy quants
template <typename Block>
inline float16x4_t load_scales_q0(const Block * x, ggml_half * aux) {
for (int k = 0; k < 4; ++k) aux[k] = x[k].d;
return vld1_f16((const float16_t *)aux);
}
template <typename Block>
inline float16x8_t load_scales_q1(const Block * x, ggml_half * aux) {
if constexpr (std::is_same_v<Block, block_q8_1>) {
for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].s; }
} else {
for (int k = 0; k < 4; ++k) { aux[k] = x[k].d; aux[k+4] = x[k].m; }
}
return vld1q_f16((const float16_t *)aux);
}
struct Q4LegacyBits {
template <typename Block>
inline void prepare(const Block * x) {
for (int i = 0; i < 4; ++i) {
auto q4bits = vld1q_u8(x[i].qs);
b[2*i+0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b));
b[2*i+1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4));
}
}
inline void prepare1(const uint8_t * qs, int8x16_t * q) const {
auto q4bits = vld1q_u8(qs);
q[0] = vreinterpretq_s8_u8(vandq_u8(q4bits, m4b));
q[1] = vreinterpretq_s8_u8(vshrq_n_u8(q4bits, 4));
}
inline void prepare1(const uint8_t * qs) {
prepare1(qs, b);
}
const uint8x16_t m4b = vdupq_n_u8(0xf);
int8x16_t b[8];
};
// One would think this commented out version would do better than the one below
// because it offers more opportunities to execute instructions in parallel.
// Instead, it runs significantly slower. Why? If the compiler is running out of vector registers
// cannot it just do the sequential version below on its own?
//inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) {
// const auto q8b_1 = vld1q_s8_x2(qs + 0);
// auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b_1.val[0]), b[1], q8b_1.val[1]);
// const auto q8b_2 = vld1q_s8_x2(qs + 32);
// auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b_2.val[0]), b[3], q8b_2.val[1]);
// auto p1234 = vpaddq_s32(p12, p34);
// const auto q8b_3 = vld1q_s8_x2(qs + 64);
// auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b_3.val[0]), b[5], q8b_3.val[1]);
// const auto q8b_4 = vld1q_s8_x2(qs + 96);
// auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b_4.val[0]), b[7], q8b_4.val[1]);
// return vpaddq_s32(p1234, vpaddq_s32(p56, p78));
//}
inline int32x4_t sum_4_blocks(const int8x16_t * b, const int8_t * qs) {
auto q8b = vld1q_s8_x2(qs + 0);
auto p12 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[0], q8b.val[0]), b[1], q8b.val[1]);
q8b = vld1q_s8_x2(qs + 32);
auto p34 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[2], q8b.val[0]), b[3], q8b.val[1]);
auto p1234 = vpaddq_s32(p12, p34);
q8b = vld1q_s8_x2(qs + 64);
auto p56 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[4], q8b.val[0]), b[5], q8b.val[1]);
q8b = vld1q_s8_x2(qs + 96);
auto p78 = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), b[6], q8b.val[0]), b[7], q8b.val[1]);
return vpaddq_s32(p1234, vpaddq_s32(p56, p78));
}
template <int nrc> struct Q80 {
constexpr static int nrc_y = nrc;
Q80(const DataInfo& info) {
for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_0 *)info.src1_row(iy);
}
inline const int8_t * quant_data(int iy, int i) const {
const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i;
return y4->qs;
}
inline float16x4_t load_scales(int iy, int i) const {
const block_q8_0_x4 * y4 = (const block_q8_0_x4 *)y[iy] + i;
return vld1_f16((const float16_t *)y4->d);
}
template <typename Dequantizer>
inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * /*acc*/) const {
auto qx_scales = deq.new_block(i);
for (int iy = 0; iy < nrc; ++iy) {
auto q8_scales = load_scales(iy, i);
sc16[iy] = vmul_f16(qx_scales, q8_scales);
}
}
template <typename Dequantizer>
inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const {
deq.prepare1(i);
float d = GGML_FP16_TO_FP32(deq.x[i].d);
for (int iy = 0; iy < nrc; ++iy) {
auto q8b = vld1q_s8_x2(y[iy][i].qs);
auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]);
acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p));
}
}
const block_q8_0 * y[nrc_y];
};
template <int nrc> struct Q81 {
constexpr static int nrc_y = nrc;
Q81(const DataInfo& info) {
for (int iy = 0; iy < nrc_y; ++iy) y[iy] = (const block_q8_1 *)info.src1_row(iy);
}
inline const int8_t * quant_data(int iy, int i) const {
const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i;
return y4->qs;
}
inline float16x8_t load_scales(int iy, int i) const {
const block_q8_1_x4 * y4 = (const block_q8_1_x4 *)y[iy] + i;
return vld1q_f16((const float16_t *)y4->d);
}
template <typename Dequantizer>
inline void process_scales(int i, Dequantizer& deq, float16x4_t * sc16, float32x4_t * acc) const {
auto qx_scales = deq.new_block(i);
for (int iy = 0; iy < nrc; ++iy) {
auto q8_scales = load_scales(iy, i);
auto m = vmul_f16(vget_high_f16(qx_scales), vget_high_f16(q8_scales));
acc[iy] = vaddq_f32(acc[iy], vcvt_f32_f16(m));
sc16[iy] = vmul_f16(vget_low_f16(qx_scales), vget_low_f16(q8_scales));
}
}
template <typename Dequantizer>
inline void process_1_block(int i, Dequantizer& deq, float32x4_t * acc) const {
deq.prepare1(i);
float d = GGML_FP16_TO_FP32(deq.x[i].d), m = 0.25f*GGML_FP16_TO_FP32(deq.x[i].m);
for (int iy = 0; iy < nrc; ++iy) {
auto q8b = vld1q_s8_x2(y[iy][i].qs);
auto p = ggml_vdotq_s32(ggml_vdotq_s32(vdupq_n_s32(0), deq.bits.b[0], q8b.val[0]), deq.bits.b[1], q8b.val[1]);
acc[iy] = vmlaq_f32(acc[iy], vdupq_n_f32(d*GGML_FP16_TO_FP32(y[iy][i].d)), vcvtq_f32_s32(p));
acc[iy] = vaddq_f32(acc[iy], vdupq_n_f32(m*GGML_FP16_TO_FP32(y[iy][i].s)));
}
}
const block_q8_1 * y[nrc_y];
};
template <typename block_q>
struct BaseLegacyDequantizer {
BaseLegacyDequantizer(const void * vx, size_t bx) : vx(vx), x(nullptr), bx(bx) {}
inline void new_row(int ix) { x = (const block_q *)((const char *)vx + bx*ix); }
Q4LegacyBits bits;
const void * vx;
const block_q * x;
size_t bx;
};
struct DequantizerQ40 final : public BaseLegacyDequantizer<block_q4_0> {
DequantizerQ40(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
inline void prepare1(int i, int8x16_t * q) const {
bits.prepare1(x[i].qs, q);
q[0] = vaddq_s8(q[0], m8);
q[1] = vaddq_s8(q[1], m8);
}
inline void prepare1(int i) {
prepare1(i, bits.b);
}
inline float16x4_t new_block(int i) {
ggml_half aux[4];
for (int k = 0; k < 4; ++k) {
aux[k] = x[4*i+k].d;
prepare1(4*i+k, bits.b + 2*k);
}
return vld1_f16((const float16_t *)aux);
}
const int8x16_t m8 = vdupq_n_s8(-8);
//ggml_half aux[4];
};
struct DequantizerQ41 : public BaseLegacyDequantizer<block_q4_1> {
DequantizerQ41(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
inline void prepare1(int i) {
bits.prepare1(x[i].qs);
}
inline float16x8_t new_block(int i) {
uint32_t aux32[4];
const uint32_t * s32 = (const uint32_t *)&x[4*i].d;
for (int k = 0; k < 4; ++k) {
aux32[k] = *s32; s32 += sizeof(block_q4_1)/4;
bits.prepare1(x[4*i+k].qs, bits.b + 2*k);
}
return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle)));
}
// Leaving this commented out attempt to be reminded that I already tried this.
// It has basically the same performance as the version above.
//inline float16x8_t new_block(int i) {
// uint32x4_t scales = {};
// const block_q4_1 * xi = x + 4*i;
// const uint32_t * s32 = (const uint32_t *)&xi->d;
// scales = vsetq_lane_u32(*s32, scales, 0); s32 += sizeof(block_q4_1)/4;
// bits.prepare1(xi[0].qs, bits.b + 0);
// scales = vsetq_lane_u32(*s32, scales, 1); s32 += sizeof(block_q4_1)/4;
// bits.prepare1(xi[1].qs, bits.b + 2);
// scales = vsetq_lane_u32(*s32, scales, 2); s32 += sizeof(block_q4_1)/4;
// bits.prepare1(xi[2].qs, bits.b + 4);
// scales = vsetq_lane_u32(*s32, scales, 3);
// bits.prepare1(xi[3].qs, bits.b + 6);
// return vreinterpretq_f16_u8(vqtbl1q_u8(vreinterpretq_u8_u32(scales), vreinterpretq_u8_u64(shuffle)));
//}
const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302};
};
struct HighBit5Legacy {
inline uint8x16_t to_bytes(const uint8_t * qh) const {
uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle);
return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vreinterpretq_u8_u64(mask));
}
inline uint8x16_t to_negated_bytes(const uint8_t * qh) const {
uint8x16_t h = vqtbl1q_u8(vreinterpretq_u8_u16(vdupq_n_u16(*(const uint16_t *)qh)), shuffle);
return vceqq_u8(vandq_u8(h, vreinterpretq_u8_u64(mask)), vdupq_n_u8(0));
}
const uint64x2_t mask = vdupq_n_u64(0x8040201008040201);
const uint8x16_t shuffle = vcombine_u8(vdup_n_u8(0), vdup_n_u8(1));
};
struct DequantizerQ50 final : public BaseLegacyDequantizer<block_q5_0> {
DequantizerQ50(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
inline void prepare1(int i, int8x16_t * q) const {
bits.prepare1(x[i].qs, q);
auto qh = x[i].qh;
q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_negated_bytes(qh+0))));
q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_negated_bytes(qh+2))));
}
inline void prepare1(int i) {
prepare1(i, bits.b);
}
inline float16x4_t new_block(int i) {
ggml_half aux[4];
for (int k = 0; k < 4; ++k) {
aux[k] = x[4*i+k].d;
prepare1(4*i+k, bits.b + 2*k);
}
return vld1_f16((const float16_t *)aux);
}
HighBit5Legacy hbits;
const uint8x16_t mh = vdupq_n_u8(0xf0);
};
struct DequantizerQ80 final : public BaseLegacyDequantizer<block_q8_0> {
DequantizerQ80(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
inline void prepare1(int i) {
bits.b[0] = vld1q_s8(x[i].qs);
bits.b[1] = vld1q_s8(x[i].qs+16);
}
inline float16x4_t new_block(int i) {
ggml_half aux[4];
for (int k = 0; k < 4; ++k) {
aux[k] = x[4*i+k].d;
bits.b[2*k+0] = vld1q_s8(x[4*i+k].qs);
bits.b[2*k+1] = vld1q_s8(x[4*i+k].qs+16);
}
return vld1_f16((const float16_t *)aux);
}
};
struct DequantizerQ51 final : public BaseLegacyDequantizer<block_q5_1> {
DequantizerQ51(const void * vx, size_t bx) : BaseLegacyDequantizer(vx, bx) {}
inline void prepare1(int i, int8x16_t * q) const {
bits.prepare1(x[i].qs, q);
auto qh = x[i].qh;
q[0] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[0]), vandq_u8(mh, hbits.to_bytes(qh+0))));
q[1] = vreinterpretq_s8_u8(vorrq_u8(vreinterpretq_u8_s8(q[1]), vandq_u8(mh, hbits.to_bytes(qh+2))));
}
inline void prepare1(int i) {
bits.prepare1(x[i].qs, bits.b);
}
inline float16x8_t new_block(int i) {
uint32_t aux32[4];
const uint32_t * s32 = (const uint32_t *)&x[4*i].d;
for (int k = 0; k < 4; ++k) {
aux32[k] = *s32; s32 += sizeof(block_q5_1)/4;
prepare1(4*i+k, bits.b + 2*k);
}
return vreinterpretq_f16_u8(vqtbl1q_u8(vld1q_u8((const uint8_t *)aux32), vreinterpretq_u8_u64(shuffle)));
}
HighBit5Legacy hbits;
const uint8x16_t mh = vdupq_n_u8(0x10);
const uint64x2_t shuffle = {0x0d0c090805040100, 0x0f0e0b0a07060302};
};
template <typename Dequantizer, typename Q8>
inline void sum_4(int i, Dequantizer& deq, const Q8& q8, const float16x4_t * sc16, float32x4_t * acc) {
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
auto pall = sum_4_blocks(deq.bits.b, q8.quant_data(iy, i));
auto scale = vcvt_f32_f16(sc16[iy]);
acc[iy] = vmlaq_f32(acc[iy], scale, vcvtq_f32_s32(pall));
}
}
template <typename Dequantizer, typename Q8>
inline void mul_mat_qX_Y_q8_Y(int n, Dequantizer& deq, Q8& q8, const DataInfo& info, int nrc_x) {
const int nb = n / QK4_1;
float16x4_t sc16[Q8::nrc_y];
for (int ix = 0; ix < nrc_x; ++ix) {
deq.new_row(ix);
float32x4_t acc[Q8::nrc_y];
for (int iy = 0; iy < Q8::nrc_y; ++iy) acc[iy] = vdupq_n_f32(0.f);
for (int i = 0; i < nb/4; ++i) {
q8.process_scales(i, deq, sc16, acc);
sum_4(i, deq, q8, sc16, acc);
}
for (int i = 4*(nb/4); i < nb; ++i) {
q8.process_1_block(i, deq, acc);
}
for (int iy = 0; iy < Q8::nrc_y; ++iy) {
info.store(ix, iy, vaddvq_f32(acc[iy]));
}
}
}
template <typename Dequantizer, typename Q8>
inline void mul_mat_qX_Y_q8_Y_1(int n, Dequantizer& deq1, Dequantizer& deq2, Q8& q8, const DataInfo& info, int nrc_x) {
const int nb = n / QK4_1;
float16x4_t sc16[2];
for (int ix = 0; ix < nrc_x; ++ix) {
deq1.new_row(ix);
deq2.new_row(ix);
float32x4_t acc[2] = { vdupq_n_f32(0.f), vdupq_n_f32(0.f) };
for (int i = 0; i < nb/8; ++i) {
q8.process_scales(2*i+0, deq1, sc16+0, acc+0);
q8.process_scales(2*i+1, deq2, sc16+1, acc+1);
sum_4(2*i+0, deq1, q8, sc16+0, acc+0);
sum_4(2*i+1, deq2, q8, sc16+1, acc+1);
}
for (int i = 2*(nb/8); i < nb/4; ++i) {
q8.process_scales(i, deq1, sc16, acc);
sum_4(i, deq1, q8, sc16, acc);
}
for (int i = 4*(nb/4); i < nb; ++i) {
q8.process_1_block(i, deq1, acc);
}
info.store(ix, 0, vaddvq_f32(vaddq_f32(acc[0], acc[1])));
}
}
template <typename Dequantizer, int nrc_y>
static void IQK_NOINLINE mul_mat_qX_1_q8_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
Q81<nrc_y> q8(info);
if constexpr (nrc_y == 1) {
Dequantizer deq1(vx, bx), deq2(vx, bx);
mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
} else {
Dequantizer deq(vx, bx);
mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x);
}
}
template <typename Dequantizer, int nrc_y>
static void IQK_NOINLINE mul_mat_qX_0_q8_0(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
Q80<nrc_y> q8(info);
if constexpr (nrc_y == 1) {
Dequantizer deq1(vx, bx), deq2(vx, bx);
mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
} else {
Dequantizer deq(vx, bx);
mul_mat_qX_Y_q8_Y(n, deq, q8, info, nrc_x);
}
}
template <typename Dequantizer>
static void IQK_NOINLINE mul_mat_qX_1_q8_1_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
Dequantizer deq1(vx, bx), deq2(vx, bx);
Q81<1> q8(info);
mul_mat_qX_Y_q8_Y_1(n, deq1, deq2, q8, info, nrc_x);
}
template <typename Dequantizer>
static void IQK_NOINLINE mul_mat_qX_0_q8_0_1(int n, const void * vx, size_t bx, const DataInfo& info, int nrc_x) {
Dequantizer deq1(vx, bx), deq2(vx, bx);
Q80<1> q8(info);
mul_mat_qX_Y_q8_Y(n, deq1, deq2, q8, info, nrc_x);
}
template <typename Dequantizer> void MulMat::set_functions(MulMat& m) {
if constexpr (std::is_same_v<Dequantizer, DequantizerQ40> || std::is_same_v<Dequantizer, DequantizerQ50> ||
std::is_same_v<Dequantizer, DequantizerQ80>) {
m.funcs[0] = mul_mat_qX_0_q8_0<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_0_q8_0<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_0_q8_0<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_0_q8_0<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_0_q8_0<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_0_q8_0<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_0_q8_0<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_0_q8_0<Dequantizer, 8>;
}
else if constexpr (std::is_same_v<Dequantizer, DequantizerQ41> || std::is_same_v<Dequantizer, DequantizerQ51>) {
m.funcs[0] = mul_mat_qX_1_q8_1<Dequantizer, 1>;
m.funcs[1] = mul_mat_qX_1_q8_1<Dequantizer, 2>;
m.funcs[2] = mul_mat_qX_1_q8_1<Dequantizer, 3>;
m.funcs[3] = mul_mat_qX_1_q8_1<Dequantizer, 4>;
m.funcs[4] = mul_mat_qX_1_q8_1<Dequantizer, 5>;
m.funcs[5] = mul_mat_qX_1_q8_1<Dequantizer, 6>;
m.funcs[6] = mul_mat_qX_1_q8_1<Dequantizer, 7>;
m.funcs[7] = mul_mat_qX_1_q8_1<Dequantizer, 8>;
}
else if constexpr (std::is_same_v<Dequantizer, DequantizerIQ2XXS> || std::is_same_v<Dequantizer, DequantizerIQ3XXS>) {
m.funcs[0] = mul_mat_qX_K_q8_K_IQXXS<1, Dequantizer>;
m.funcs[1] = mul_mat_qX_K_q8_K_IQXXS<2, Dequantizer>;
m.funcs[2] = mul_mat_qX_K_q8_K_IQXXS<3, Dequantizer>;
m.funcs[3] = mul_mat_qX_K_q8_K_IQXXS<4, Dequantizer>;
m.funcs[4] = mul_mat_qX_K_q8_K_IQXXS<5, Dequantizer>;
m.funcs[5] = mul_mat_qX_K_q8_K_IQXXS<6, Dequantizer>;
m.funcs[6] = mul_mat_qX_K_q8_K_IQXXS<7, Dequantizer>;
m.funcs[7] = mul_mat_qX_K_q8_K_IQXXS<8, Dequantizer>;
}
else if constexpr (std::is_same_v<Dequantizer, DequantizerIQ2S> ||
std::is_same_v<Dequantizer, DequantizerIQ3S> ||
std::is_same_v<Dequantizer, DequantizerIQ2XS>) {
m.funcs[0] = mul_mat_qX_K_q8_K_IQ<1, Dequantizer>;
m.funcs[1] = mul_mat_qX_K_q8_K_IQ<2, Dequantizer>;
m.funcs[2] = mul_mat_qX_K_q8_K_IQ<3, Dequantizer>;
m.funcs[3] = mul_mat_qX_K_q8_K_IQ<4, Dequantizer>;
m.funcs[4] = mul_mat_qX_K_q8_K_IQ<5, Dequantizer>;
m.funcs[5] = mul_mat_qX_K_q8_K_IQ<6, Dequantizer>;
m.funcs[6] = mul_mat_qX_K_q8_K_IQ<7, Dequantizer>;
m.funcs[7] = mul_mat_qX_K_q8_K_IQ<8, Dequantizer>;
}
else {
m.funcs[0] = mul_mat_qX_K_q8_K_T<1, Dequantizer>;
m.funcs[1] = mul_mat_qX_K_q8_K_T<2, Dequantizer>;
m.funcs[2] = mul_mat_qX_K_q8_K_T<3, Dequantizer>;
m.funcs[3] = mul_mat_qX_K_q8_K_T<4, Dequantizer>;
m.funcs[4] = mul_mat_qX_K_q8_K_T<5, Dequantizer>;
m.funcs[5] = mul_mat_qX_K_q8_K_T<6, Dequantizer>;
m.funcs[6] = mul_mat_qX_K_q8_K_T<7, Dequantizer>;
m.funcs[7] = mul_mat_qX_K_q8_K_T<8, Dequantizer>;
}
}
bool MulMat::set_mul_mat(int typeA, int ne00, MulMat& m, int& row_size_q8, int Ny) {
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_K, ne00);
(void)Ny;
// Uncommenting out this would disable iqk_mul_mat for matrix x vector multiplications.
//if (Ny == 1 && (typeA == GGML_TYPE_IQ2_XXS || typeA == GGML_TYPE_IQ2_XS || typeA == GGML_TYPE_IQ2_S ||
// typeA == GGML_TYPE_IQ3_XXS || typeA == GGML_TYPE_IQ3_S)) return false;
switch (typeA) {
case GGML_TYPE_Q2_K:
MulMat::set_functions<DequantizerQ2K>(m);
break;
case GGML_TYPE_Q3_K:
MulMat::set_functions<DequantizerQ3K>(m);
break;
case GGML_TYPE_Q4_K:
MulMat::set_functions<DequantizerQ4K>(m);
break;
case GGML_TYPE_Q5_K:
MulMat::set_functions<DequantizerQ5K>(m);
break;
case GGML_TYPE_Q6_K:
MulMat::set_functions<DequantizerQ6K>(m);
break;
case GGML_TYPE_IQ4_XS:
MulMat::set_functions<DequantizerIQ4XS>(m);
break;
case GGML_TYPE_IQ3_S:
MulMat::set_functions<DequantizerIQ3S>(m);
break;
case GGML_TYPE_IQ3_XXS:
MulMat::set_functions<DequantizerIQ3XXS>(m);
break;
case GGML_TYPE_IQ2_S:
MulMat::set_functions<DequantizerIQ2S>(m);
break;
case GGML_TYPE_IQ2_XS:
MulMat::set_functions<DequantizerIQ2XS>(m);
break;
case GGML_TYPE_IQ2_XXS:
MulMat::set_functions<DequantizerIQ2XXS>(m);
break;
case GGML_TYPE_Q4_0:
MulMat::set_functions<DequantizerQ40>(m);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
break;
case GGML_TYPE_Q4_1:
MulMat::set_functions<DequantizerQ41>(m);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
break;
case GGML_TYPE_Q5_0:
MulMat::set_functions<DequantizerQ50>(m);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
break;
case GGML_TYPE_Q5_1:
MulMat::set_functions<DequantizerQ51>(m);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_1, ne00);
break;
case GGML_TYPE_Q8_0:
MulMat::set_functions<DequantizerQ80>(m);
row_size_q8 = ggml_row_size(GGML_TYPE_Q8_0, ne00);
break;
default:
return false;
}
return true;
}
}
#endif // __x86_64__ or __aarch64__
third_party/llamafile/iqk_mul_mat_amd_avx2.cpp 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/iqk_mul_mat_amd_avx2.cpp
// Copyrigth 2024 Iwan Kawrakow.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
#ifdef __x86_64__
#include "iqk_mul_mat.inc"
#endif // __x86_64__
third_party/llamafile/iqk_mul_mat_amd_zen4.cpp 0 → 100644
View file @ 18c42e67
// Adapted from
// https://github.com/Mozilla-Ocho/llamafile/blob/0.8.8/llamafile/iqk_mul_mat_amd_zen4.cpp
// Copyrigth 2024 Iwan Kawrakow.
// Copyright(c) 2024 by KVCache.AI, All Rights Reserved.
#ifdef __x86_64__
#define iqk_mul_mat iqk_mul_mat_zen4
#define iqk_mul_mat_moe iqk_mul_mat_moe_zen4
#include "iqk_mul_mat.inc"
#endif // __x86_64__
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