# LoRA interrogate script by @bdsqlsz

$v2 = 0 # load Stable Diffusion v2.x model / Stable Diffusion 2.x模型读取

$sd_model = "./sd-models/sd_model.safetensors" # Stable Diffusion model to load: ckpt or safetensors file | 读取的基础SD模型, 保存格式 cpkt 或 safetensors

$model = "./output/LoRA.safetensors" # LoRA model to interrogate: ckpt or safetensors file | 需要调查关键字的LORA模型, 保存格式 cpkt 或 safetensors

$batch_size = 64 # batch size for processing with Text Encoder | 使用 Text Encoder 处理时的批量大小，默认16，推荐64/128

$clip_skip = 1 # use output of nth layer from back of text encoder (n>=1) | 使用文本编码器倒数第 n 层的输出，n 可以是大于等于 1 的整数

# Activate python venv

.\venv\Scripts\activate

$Env:HF_HOME = "huggingface"

$ext_args = [System.Collections.ArrayList]::new()

if ($v2) {

[void]$ext_args.Add("--v2")

}

# run interrogate

accelerate launch --num_cpu_threads_per_process=8 "./sd-scripts/networks/lora_interrogator.py" `

--sd_model=$sd_model `

--model=$model `

--batch_size=$batch_size `

--clip_skip=$clip_skip `

$ext_args

Write-Output "Interrogate finished"

Read-Host | Out-Null ;