pipeline_stable_diffusion.py trys to encode the prompt when there is no prompt and `prompt_embeds` and `negative_prompt_embeds` are given

[CaffreyR]

Describe the bug

pipeline_stable_diffusion.py trys to encode the prompt when there is no prompt and prompt_embeds and negative_prompt_embeds are given.

Reproduction

Use --pre_compute_text_embeddings when train a dreambooth scripts. Use #6135 by @sayakpaul updating the train_dreambooth_lora.py. Even if prompt_embeds and negative_prompt_embeds are proven to pipeline, it still wants to find prompt to encode and return Nonetype. So --pre_compute_text_embeddings can be used only in IF.

Logs

No response

System Info

• diffusers version: 0.24.0
• Platform: Linux-5.15.0-56-generic-x86_64-with-glibc2.31
• Python version: 3.9.18
• PyTorch version (GPU?): 1.11.0+cu115 (True)
• Huggingface_hub version: 0.19.4
• Transformers version: 4.36.1
• Accelerate version: 0.25.0
• xFormers version: not installed
• Using GPU in script?: Yes
• Using distributed or parallel set-up in script?: No

Who can help?

@yiyixuxu @DN6 @sayakpaul @patrickvonplaten

[CaffreyR]

Pull request regarding this #6202

[CaffreyR]

Hi @patrickvonplaten, if the modification of #6202 is wrong. Please see
https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth_lora.py#L1239
when prompt_embeds is given, the model does not give prompt to the pipeline. And it will return error when running it.

[CaffreyR]

Hi @sayakpaul , any ideas about it?

[DN6]

@CaffreyR Could you please provide a code example of the command you're running that produces the error.

[CaffreyR]

Hi @DN6 , please see https://github.com/huggingface/diffusers/blob/main/examples/dreambooth/train_dreambooth.py#L164
if args.pre_compute_text_embeddings , there is no "prompt" in the pipeline_args, so when pipeline_args to the pipeline, it report error.

[DN6]

@CaffreyR I meant could you please share the exact command you are running in your terminal that produces this error. It is hard to reproduce this with just a link to line in the training file.

[CaffreyR]

Hi @DN6 , please follow the instruction of https://github.com/huggingface/diffusers/tree/main/examples/dreambooth
and use the code below to get dataset

from huggingface_hub import snapshot_download

local_dir = "./dog"
snapshot_download(
    "diffusers/dog-example",
    local_dir=local_dir, repo_type="dataset",
    ignore_patterns=".gitattributes",
)

and after that please use

export MODEL_NAME="runwayml/stable-diffusion-v1-5"
export INSTANCE_DIR="dog"
export OUTPUT_DIR="path-to-save-model"

accelerate launch train_dreambooth.py \
  --pretrained_model_name_or_path=$MODEL_NAME  \
  --instance_data_dir=$INSTANCE_DIR \
  --output_dir=$OUTPUT_DIR \
  --instance_prompt="a photo of sks dog" \
  --resolution=512 \
  --train_batch_size=1 \
  --gradient_accumulation_steps=1 \
  --learning_rate=5e-6 \
  --lr_scheduler="constant" \
  --lr_warmup_steps=0 \
  --max_train_steps=400 \
  --validation_prompt="a photo of sks dog on the beach" \
  --seed="0" \
  --push_to_hub \
  --pre_compute_text_embeddings \
  --num_validation_images=50

it uses --pre_compute_text_embeddings and error in validation function of "runwayml/stable-diffusion-v1-5"
and when it comes to validation, it will report

Traceback (most recent call last):
  File "/data2/gw723/1/train_dreambooth.py", line 1429, in <module>
    main(args)
  File "/data2/gw723/1/train_dreambooth.py", line 1353, in main
    images = log_validation(
  File "/data2/gw723/1/train_dreambooth.py", line 176, in log_validation
    image = pipeline(**pipeline_args, num_inference_steps=25, generator=generator).images[0]
  File "/data2/gw723/anaconda3/envs/tmp/lib/python3.9/site-packages/torch/utils/_contextlib.py", line 115, in decorate_context
    return func(*args, **kwargs)
  File "/data2/gw723/1/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py", line 933, in __call__
    prompt_embeds, negative_prompt_embeds = self.encode_prompt(
  File "/data2/gw723/1/diffusers/src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py", line 489, in encode_prompt
    unscale_lora_layers(self.text_encoder, lora_scale)
  File "/data2/gw723/1/diffusers/src/diffusers/utils/peft_utils.py", line 131, in unscale_lora_layers
    for module in model.modules():
AttributeError: 'NoneType' object has no attribute 'modules'

[CaffreyR]

Hi @DN6 , any ideas about it?

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