YG-Soft/YG_FT_Platform
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1. 新增了日志系统

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2. 新增了添加新训练选择对应的GPU
This commit is contained in:
leokaka1
2026-01-23 11:07:09 +08:00
parent 7f64362826
commit 730ac6f460
6 changed files with 860 additions and 14 deletions
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115
web/pages/fine-tune-create.html
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@@ -225,6 +225,18 @@
<div class="mb-6">
<h3 class="text-sm font-semibold text-gray-700 mb-4 pb-2 border-b border-gray-100">训练配置</h3>
<!-- GPU硬件选择 -->
<div class="mb-6">
<label class="block text-sm text-gray-600 mb-3">
<span class="text-red-500 mr-1">*</span>GPU硬件选择
</label>
<div id="gpuSelectionArea" class="grid grid-cols-2 md:grid-cols-3 lg:grid-cols-4 gap-4">
<!-- GPU列表将通过JS动态加载 -->
<div class="text-sm text-gray-400 col-span-full">正在加载GPU设备...</div>
</div>
<p class="text-xs text-gray-400 mt-2">支持选择多个GPU进行训练（多卡训练）</p>
</div>
<!-- 训练方式 -->
<div class="mb-6">
<label class="block text-sm text-gray-600 mb-3">训练方式</label>
@@ -627,6 +639,9 @@
// 初始化训练方法参数显示
toggleTrainMethod();
// 加载GPU列表
loadGPUList();
// 设置侧边栏当前页高亮
const currentPage = 'fine-tune';
document.querySelectorAll('.nav-link').forEach(link => {
@@ -790,17 +805,113 @@
}
}
// 加载GPU列表
async function loadGPUList() {
const container = document.getElementById('gpuSelectionArea');
if (!container) return;
try {
// 模拟GPU数据 - 实际项目中可以从API获取
const gpuData = await fetchGPUs();
renderGPUList(gpuData);
} catch (error) {
console.error('加载GPU列表失败:', error);
container.innerHTML = '<div class="text-sm text-red-500 col-span-full">加载GPU设备失败，请刷新重试</div>';
}
}
// 获取GPU数据（模拟数据，实际可从API获取）
async function fetchGPUs() {
// 实际项目中可以调用后端API获取GPU信息
// const response = await fetch(`${API_BASE}/gpus`);
// return await response.json();
// 模拟GPU数据
return [
{ id: 'gpu0', name: 'NVIDIA A100 80GB', memory: '80GB', cuda_cores: 6912, available: true },
{ id: 'gpu1', name: 'NVIDIA A100 80GB', memory: '80GB', cuda_cores: 6912, available: true },
{ id: 'gpu2', name: 'NVIDIA A100 40GB', memory: '40GB', cuda_cores: 6912, available: true },
{ id: 'gpu3', name: 'NVIDIA A100 40GB', memory: '40GB', cuda_cores: 6912, available: false },
{ id: 'gpu4', name: 'NVIDIA V100 32GB', memory: '32GB', cuda_cores: 5120, available: true },
{ id: 'gpu5', name: 'NVIDIA V100 16GB', memory: '16GB', cuda_cores: 5120, available: false },
{ id: 'gpu6', name: 'NVIDIA RTX 3090', memory: '24GB', cuda_cores: 10496, available: true },
{ id: 'gpu7', name: 'NVIDIA RTX 4090', memory: '24GB', cuda_cores: 16384, available: true }
];
}
// 渲染GPU列表（点击卡片选中，无需复选框）
function renderGPUList(gpus) {
const container = document.getElementById('gpuSelectionArea');
if (!container) return;
container.innerHTML = gpus.map(gpu => `
<div id="gpu_card_${gpu.id}"
class="gpu-card ${!gpu.available ? 'opacity-50 cursor-not-allowed' : 'cursor-pointer hover:border-primary'} border rounded-lg p-3 transition-all"
onclick="toggleGPUSelection('${gpu.id}')"
${!gpu.available ? 'title="该GPU不可用"' : ''}
data-gpu-id="${gpu.id}">
<div class="flex items-center">
<i class="fa fa-microchip text-primary mr-2"></i>
<div class="flex-1">
<div class="flex items-center justify-between">
<span class="text-sm font-medium text-gray-700">${gpu.name}</span>
${gpu.available
? '<i class="fa fa-check-circle text-green-600 text-xs"></i>'
: '<i class="fa fa-times-circle text-red-500 text-xs"></i>'}
</div>
<div class="text-xs text-gray-500 mt-1">
<span class="mr-2"><i class="fa fa-floppy-o mr-1"></i>${gpu.memory}</span>
<span><i class="fa fa-cog mr-1"></i>${gpu.cuda_cores} CUDA</span>
</div>
</div>
</div>
</div>
`).join('');
}
// 切换GPU选择状态
function toggleGPUSelection(gpuId) {
const card = document.getElementById(`gpu_card_${gpuId}`);
if (!card || card.classList.contains('opacity-50')) return;
// 切换选中状态
if (card.classList.contains('border-primary')) {
// 取消选中
card.classList.remove('border-primary', 'bg-blue-50');
card.querySelector('.fa-check-circle').classList.replace('text-primary', 'text-green-600');
} else {
// 选中
card.classList.add('border-primary', 'bg-blue-50');
// 移除检查图标，添加选中标记
const icon = card.querySelector('.fa-check-circle');
if (icon) {
icon.classList.remove('fa-check-circle', 'text-green-600');
icon.classList.add('fa-check', 'text-primary');
}
}
}
// 获取选中的GPU列表
function getSelectedGPUs() {
const cards = document.querySelectorAll('.gpu-card.border-primary');
return Array.from(cards).map(card => card.dataset.gpuId);
}
// 提交表单
async function submitForm() {
const form = document.getElementById('createForm');
const formData = new FormData(form);
const validSplit = formData.get('valid_split');
// 获取选中的GPU
const selectedGPUs = getSelectedGPUs();
const data = {
name: formData.get('name'),
base_model: formData.get('base_model'),
train_type: formData.get('train_type'),
train_method: formData.get('train_method'),
gpus: selectedGPUs, // 添加GPU选择
train_dataset_id: formData.get('train_dataset_id'),
valid_split: validSplit,
valid_ratio: parseInt(formData.get('valid_ratio')) || 10,
@@ -814,6 +925,10 @@
showMessage('提示', '请输入任务名称', 'warning');
return;
}
if (selectedGPUs.length === 0) {
showMessage('提示', '请选择至少一个GPU硬件', 'warning');
return;
}
if (!data.base_model) {
showMessage('提示', '请选择基础模型', 'warning');
return;