Fix the issue on sd3 dreambooth w./w.t. lora training

[leisuzz]

What does this PR do?

Fixes #9237 and few more potential issues with the RuntimeError: Input type and bias type in the log validation part in the sd3 dreambooth portion with lora, lora sdxl, lora sd3, lux, and sd3

I modified the code without changing or fixing the VAE type, so any weight dtype can be implemented without affecting the result

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[leisuzz]

@sayakpaul Please proceed for reviewing this Pull Request

[sayakpaul]

Thanks!

Could you run the pytest examples on your GPU and report back?

[leisuzz]

Thanks!

Could you run the pytest examples on your GPU and report back?

I had the same issue in /examples/dreambooth/train_dreambooth_sd3.py, after this modification, the issue has been fixed. I will run on the Lora to see whether it works or not

[leisuzz]

Thanks!

Could you run the pytest examples on your GPU and report back?

Both w.t. / w. Lora works well.

`export model_name ="stable-diffusion-3-medium-diffusers"
export dataset_name ="pokemon-blip-captions"
export OUTPUT_DIR="sd3-dreambooth-lora"

accelerate launch train_dreambooth_lora_sd3.py
--pretrained_model_name_or_path=$model_name
--dataset_name=$dataset_name
--output_dir=$output_path
--instance_prompt="a photo of pokemon"
--resolution=$resolution
--train_batch_size=$batch_size
--gradient_checkpointing
--mixed_precision=$mixed_precision
--gradient_accumulation_steps=$gradient_accumulation_steps
--learning_rate=1e-06
--lr_scheduler="constant"
--lr_warmup_steps=0
--max_train_steps=$max_train_steps
--checkpointing_steps=5001
--validation_prompt="An robotic pokemon with wings"
--validation_epochs=100
--seed="0"
--output_dir=${output_path} > ${output_path}/train_${mixed_precision}_lora_sd3_dreambooth.log 2>&1 &
wait

`export model_name ="stable-diffusion-3-medium-diffusers"
export dataset_name ="pokemon-blip-captions"
export OUTPUT_DIR="sd3-dreambooth"

accelerate launch train_dreambooth_sd3.py
--pretrained_model_name_or_path=$model_name
--dataset_name=$dataset_name --caption_column="text"
--instance_prompt="a photo of pokemon"
--resolution=$resolution
--train_batch_size=$batch_size
--gradient_checkpointing
--mixed_precision=$mixed_precision
--gradient_accumulation_steps=1
--learning_rate=1e-06
--lr_scheduler="constant"
--lr_warmup_steps=0
--validation_prompt="A photo of pokemon in a bucket"
--validation_epochs=5
--max_train_steps=$max_train_steps
--checkpointing_steps=500
--output_dir=${output_path} > ${output_path}/train_${mixed_precision}_sd3_dreambooth.log 2>&1 &
wait

[sayakpaul]

Just ran the tests myself from your fork and all good! Thanks!