208 lines
7.7 KiB
Bash
Executable File
208 lines
7.7 KiB
Bash
Executable File
#!/bin/bash
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BASE_DIR="$(cd "$(dirname "$0")" && pwd)"
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# 自动检测 conda 安装路径（优先用环境变量，其次用 conda info --base）
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if [ -z "$CONDA_BASE" ]; then
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if command -v conda >/dev/null 2>&1; then
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CONDA_BASE="$(conda info --base 2>/dev/null)"
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fi
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fi
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CONDA_BASE="${CONDA_BASE:-$HOME/miniconda3}"
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# 初始化 conda（脚本中需要 source 才能用 conda activate）
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if [ -f "$CONDA_BASE/etc/profile.d/conda.sh" ]; then
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source "$CONDA_BASE/etc/profile.d/conda.sh"
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else
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echo "WARNING: 未找到 conda.sh，请确认 CONDA_BASE=$CONDA_BASE 正确"
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fi
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echo "=== 换发型项目部署脚本 ==="
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echo "BASE_DIR: $BASE_DIR"
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echo "CONDA_BASE: $CONDA_BASE"
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echo ""
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ERRORS=()
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# 0. 自动解压网盘文件（如果 cloud_packages/ 存在）
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CLOUD_DIR="$BASE_DIR/cloud_packages"
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if [ -d "$CLOUD_DIR" ] && [ "$(ls -A "$CLOUD_DIR")" ]; then
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echo "[0/9] 自动解压网盘文件..."
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# conda 环境
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for pkg in my_hair.tar.gz sdwebui.tar.gz kohya.tar.gz; do
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if [ -f "$CLOUD_DIR/$pkg" ]; then
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echo " 解压 $pkg..."
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tar -xzf "$CLOUD_DIR/$pkg" -C "$BASE_DIR/conda_envs/"
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echo " ✓ $pkg"
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fi
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done
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# SD 底模
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if [ -f "$CLOUD_DIR/sd_base_models.tar.gz" ]; then
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echo " 解压 sd_base_models.tar.gz..."
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mkdir -p "$BASE_DIR/stable-diffusion-webui/models/Stable-diffusion"
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tar -xzf "$CLOUD_DIR/sd_base_models.tar.gz" -C "$BASE_DIR/stable-diffusion-webui/models/Stable-diffusion/"
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echo " ✓ sd_base_models.tar.gz"
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fi
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# LoRA 模型
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mkdir -p "$BASE_DIR/stable-diffusion-webui/models/Lora"
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for pkg in lora_0-9.tar.gz lora_h.tar.gz lora_n.tar.gz lora_t.tar.gz; do
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if [ -f "$CLOUD_DIR/$pkg" ]; then
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echo " 解压 $pkg..."
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tar -xzf "$CLOUD_DIR/$pkg" -C "$BASE_DIR/stable-diffusion-webui/models/Lora/"
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echo " ✓ $pkg"
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fi
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done
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# 换发算法权重
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if [ -f "$CLOUD_DIR/weights.tar.gz" ]; then
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echo " 解压 weights.tar.gz..."
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tar -xzf "$CLOUD_DIR/weights.tar.gz" -C "$BASE_DIR/hair_service_sd/"
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echo " ✓ weights.tar.gz"
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fi
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# kohya 训练环境
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if [ -f "$CLOUD_DIR/kohya_local.tar.gz" ]; then
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echo " 解压 kohya_local.tar.gz..."
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tar -xzf "$CLOUD_DIR/kohya_local.tar.gz" -C "$BASE_DIR/kohya_ss_home/"
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echo " ✓ kohya_local.tar.gz"
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fi
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if [ -f "$CLOUD_DIR/kohya_code.tar.gz" ]; then
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echo " 解压 kohya_code.tar.gz..."
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tar -xzf "$CLOUD_DIR/kohya_code.tar.gz" -C "$BASE_DIR/kohya_ss_home/"
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echo " ✓ kohya_code.tar.gz"
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fi
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# 业务数据
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if [ -f "$CLOUD_DIR/data.tar.gz" ]; then
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echo " 解压 data.tar.gz..."
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tar -xzf "$CLOUD_DIR/data.tar.gz" -C "$BASE_DIR/"
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echo " ✓ data.tar.gz"
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fi
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# WebUI 扩展
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mkdir -p "$BASE_DIR/stable-diffusion-webui/extensions"
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if [ -f "$CLOUD_DIR/webui_controlnet.tar.gz" ]; then
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echo " 解压 webui_controlnet.tar.gz..."
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tar -xzf "$CLOUD_DIR/webui_controlnet.tar.gz" -C "$BASE_DIR/stable-diffusion-webui/extensions/"
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echo " ✓ webui_controlnet.tar.gz"
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fi
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if [ -f "$CLOUD_DIR/webui_repositories.tar.gz" ]; then
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echo " 解压 webui_repositories.tar.gz..."
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tar -xzf "$CLOUD_DIR/webui_repositories.tar.gz" -C "$BASE_DIR/stable-diffusion-webui/"
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echo " ✓ webui_repositories.tar.gz"
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fi
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echo " ✓ 网盘文件解压完成"
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else
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echo "[0/9] cloud_packages/ 目录不存在或为空，跳过自动解压"
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fi
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echo ""
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# 1. 检查前提条件
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echo "[1/9] 检查前提条件..."
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command -v git >/dev/null || { echo " ✗ git 未安装"; ERRORS+=("git"); }
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command -v conda >/dev/null || { echo " ✗ conda 未安装"; ERRORS+=("conda"); }
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nvidia-smi >/dev/null 2>&1 || { echo " ✗ NVIDIA 驱动未安装"; ERRORS+=("nvidia-smi"); }
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if [ ${#ERRORS[@]} -eq 0 ]; then
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echo " ✓ 前提条件满足"
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fi
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# 2. 生成 configure.ini
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echo "[2/9] 生成 configure.ini..."
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sed "s|__BASE_DIR__|$BASE_DIR|g" "$BASE_DIR/hair_service_sd/config/configure.ini.template" > "$BASE_DIR/hair_service_sd/config/configure.ini"
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echo " ✓ configure.ini 已生成"
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# 3. 恢复 conda 环境（conda-pack）
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echo "[3/9] 恢复 conda 环境（my_hair, sdwebui, kohya）..."
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for env_name in my_hair sdwebui kohya; do
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if [ -f "$BASE_DIR/conda_envs/${env_name}.tar.gz" ]; then
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echo " 恢复 $env_name ..."
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rm -rf "$CONDA_BASE/envs/$env_name"
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mkdir -p "$CONDA_BASE/envs/$env_name"
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tar -xzf "$BASE_DIR/conda_envs/${env_name}.tar.gz" -C "$CONDA_BASE/envs/$env_name"
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conda activate "$env_name" 2>/dev/null
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conda-unpack 2>/dev/null # 修复打包后的硬编码路径
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conda deactivate 2>/dev/null
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echo " ✓ $env_name 已恢复"
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else
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echo " ✗ conda_envs/${env_name}.tar.gz 不存在，请从网盘下载"
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ERRORS+=("conda_envs/${env_name}.tar.gz")
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fi
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done
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# 4. 创建 py310 环境（从 yml）
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echo "[4/9] 创建 py310 环境（从 yml）..."
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if [ -f "$BASE_DIR/conda_envs/py310.yml" ]; then
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conda env create -f "$BASE_DIR/conda_envs/py310.yml" -n py310 2>/dev/null && echo " ✓ py310 已创建" || echo " ℹ py310 环境已存在，跳过"
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else
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echo " ✗ conda_envs/py310.yml 不存在"
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ERRORS+=("conda_envs/py310.yml")
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fi
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# 5. 检查模型/数据目录
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echo "[5/9] 检查模型和数据目录..."
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for dir in hair_service_sd/weights stable-diffusion-webui/models/Lora stable-diffusion-webui/models/Stable-diffusion stable-diffusion-webui/extensions/sd-webui-controlnet stable-diffusion-webui/repositories kohya_ss_home/.local kohya_ss_home/kohya_ss data/ref_hairstyle; do
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if [ -d "$BASE_DIR/$dir" ]; then
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echo " ✓ $dir"
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else
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echo " ✗ $dir 缺失，请从网盘下载"
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ERRORS+=("$dir")
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fi
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done
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# 6. 检查训练底模
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echo "[6/9] 检查训练底模 v1-5-pruned-emaonly..."
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if [ -f "$BASE_DIR/stable-diffusion-webui/models/Stable-diffusion/v1-5-pruned-emaonly.safetensors" ]; then
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echo " ✓ v1-5-pruned-emaonly.safetensors 已存在"
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else
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echo " ✗ v1-5-pruned-emaonly.safetensors 缺失，请从网盘下载 models/ 目录"
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ERRORS+=("v1-5-pruned-emaonly.safetensors")
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fi
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# 7. 创建运行时目录
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echo "[7/9] 创建运行时目录..."
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mkdir -p "$BASE_DIR/logs"
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mkdir -p "$BASE_DIR/data/tmp" "$BASE_DIR/data/res_dir" "$BASE_DIR/data/userImage" "$BASE_DIR/data/user_info"
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mkdir -p "$BASE_DIR/kohya_ss_home/train_material"
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echo " ✓ 运行时目录已创建"
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# 8. 验证 kohya 训练环境
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echo "[8/9] 验证 kohya 训练环境..."
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KOHYA_PYTHON="$CONDA_BASE/envs/kohya/bin/python"
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KOHYA_LOCAL="$BASE_DIR/kohya_ss_home/.local/lib/python3.10/site-packages"
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if [ -f "$KOHYA_PYTHON" ] && [ -d "$KOHYA_LOCAL" ]; then
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echo " 测试 torch/accelerate 加载..."
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if PYTHONPATH="$KOHYA_LOCAL" "$KOHYA_PYTHON" -c "
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import torch, accelerate, bitsandbytes, diffusers
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print(f' torch={torch.__version__} cuda={torch.cuda.is_available()}')
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print(f' accelerate={accelerate.__version__}')
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print(' ✓ 训练环境验证通过')
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" 2>/dev/null; then
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true
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else
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echo " ✗ 训练环境验证失败，请检查 kohya 环境和 .local 目录"
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ERRORS+=("kohya验证")
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fi
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else
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echo " ✗ kohya Python 或 .local 目录不存在，跳过验证"
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ERRORS+=("kohya环境")
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fi
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echo ""
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echo "=== 部署结果 ==="
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if [ ${#ERRORS[@]} -eq 0 ]; then
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echo "✓ 所有检查通过，部署完成！"
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else
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echo "⚠ 有 ${#ERRORS[@]} 个问题需要处理："
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for err in "${ERRORS[@]}"; do
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echo " - $err"
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done
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echo ""
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echo "请从网盘下载缺失的文件后重新运行 ./setup.sh"
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fi
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echo ""
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echo "启动服务: ./start_all_services.sh"
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