87 lines
2.8 KiB
PowerShell
87 lines
2.8 KiB
PowerShell
# This powershell script will create a model using the fine tuning dreambooth method. It will require landscape,
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# portrait and square images.
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#
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# Adjust the script to your own needs
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# Sylvia Ritter
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# variable values
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$pretrained_model_name_or_path = "D:\models\v1-5-pruned-mse-vae.ckpt"
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$data_dir = "D:\test\squat"
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$train_dir = "D:\test\"
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$resolution = "512,512"
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$image_num = Get-ChildItem $data_dir -Recurse -File -Include *.png | Measure-Object | %{$_.Count}
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Write-Output "image_num: $image_num"
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$learning_rate = 1e-6
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$dataset_repeats = 40
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$train_batch_size = 8
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$epoch = 1
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$save_every_n_epochs=1
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$mixed_precision="fp16"
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$num_cpu_threads_per_process=6
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# You should not have to change values past this point
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$output_dir = $train_dir + "\model"
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$repeats = $image_num * $dataset_repeats
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$mts = [Math]::Ceiling($repeats / $train_batch_size * $epoch)
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Write-Output "Repeats: $repeats"
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.\venv\Scripts\activate
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accelerate launch --num_cpu_threads_per_process $num_cpu_threads_per_process train_db.py `
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--pretrained_model_name_or_path=$pretrained_model_name_or_path `
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--train_data_dir=$data_dir `
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--output_dir=$output_dir `
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--resolution=$resolution `
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--train_batch_size=$train_batch_size `
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--learning_rate=$learning_rate `
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--max_train_steps=$mts `
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--use_8bit_adam `
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--xformers `
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--mixed_precision=$mixed_precision `
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--cache_latents `
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--save_every_n_epochs=$save_every_n_epochs `
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--fine_tuning `
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--dataset_repeats=$dataset_repeats `
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--save_precision="fp16"
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# 2nd pass at half the dataset repeat value
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accelerate launch --num_cpu_threads_per_process $num_cpu_threads_per_process train_db.py `
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--pretrained_model_name_or_path=$output_dir"\last.ckpt" `
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--train_data_dir=$data_dir `
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--output_dir=$output_dir"2" `
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--resolution=$resolution `
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--train_batch_size=$train_batch_size `
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--learning_rate=$learning_rate `
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--max_train_steps=$([Math]::Ceiling($mts/2)) `
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--use_8bit_adam `
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--xformers `
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--mixed_precision=$mixed_precision `
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--cache_latents `
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--save_every_n_epochs=$save_every_n_epochs `
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--fine_tuning `
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--dataset_repeats=$([Math]::Ceiling($dataset_repeats/2)) `
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--save_precision="fp16"
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accelerate launch --num_cpu_threads_per_process $num_cpu_threads_per_process train_db.py `
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--pretrained_model_name_or_path=$output_dir"\last.ckpt" `
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--train_data_dir=$data_dir `
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--output_dir=$output_dir"2" `
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--resolution=$resolution `
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--train_batch_size=$train_batch_size `
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--learning_rate=$learning_rate `
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--max_train_steps=$mts `
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--use_8bit_adam `
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--xformers `
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--mixed_precision=$mixed_precision `
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--cache_latents `
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--save_every_n_epochs=$save_every_n_epochs `
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--fine_tuning `
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--dataset_repeats=$dataset_repeats `
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--save_precision="fp16"
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