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# This powershell script will create a model using the fine tuning dreambooth method. It will require landscape,
# portrait and square images.
#
# Adjust the script to your own needs
# variable values
$pretrained_model_name_or_path = "D:\models\v1-5-pruned-mse-vae.ckpt"
$data_dir = "D:\dreambooth\silvery_trait\raw_data\all-images-v3"
$train_dir = "D:\dreambooth\silvery_trait\"
$resolution = "768,576"
$logging_dir = "D:\dreambooth\silvery_trait\training_logs"
$image_num = Get-ChildItem $data_dir -Recurse -File -Include *.png, *.jpg, *.webp | Measure-Object | %{$_.Count}
Write-Output "image_num: $image_num"
$learning_rate = 1e-6
$dataset_repeats = 40
$train_batch_size = 6
$epoch = 4
$save_every_n_epochs=1
$mixed_precision="fp16"
$num_cpu_threads_per_process=6
# You should not have to change values past this point
$output_dir = $train_dir + "\finetuned_model"
$repeats = $image_num * $dataset_repeats
$mts = [Math]::Ceiling($repeats / $train_batch_size * $epoch)
Write-Output "Repeats: $repeats"
.\venv\Scripts\activate
accelerate launch --num_cpu_threads_per_process $num_cpu_threads_per_process train_db_fixed.py `
--pretrained_model_name_or_path=$pretrained_model_name_or_path `
--train_data_dir=$data_dir `
--output_dir=$output_dir `
--resolution=$resolution `
--train_batch_size=$train_batch_size `
--learning_rate=$learning_rate `
--max_train_steps=$mts `
--use_8bit_adam `
--xformers `
--mixed_precision=$mixed_precision `
--cache_latents `
--save_every_n_epochs=$save_every_n_epochs `
--fine_tuning `
--enable_bucket `
--dataset_repeats=$dataset_repeats `
--logging_dir=$logging_dir `
--save_precision="fp16"
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