Hello everyone,
I am trying to run the Dreambooth training example from the diffusers repo, on Sagemaker: diffusers/examples/dreambooth at main · huggingface/diffusers · GitHub
However I am getting the following error:
AttributeError: 'SageMakerConfig' object has no attribute 'gpu_ids'
.
Here are the flags I am using:
export MODEL_NAME="CompVis/stable-diffusion-v1-4"
export INSTANCE_DIR="s3://instance-images"
export OUTPUT_DIR="/opt/ml/model"
accelerate launch train_dreambooth.py \
--aws_access_key_id="XXXXXXXXXX" \
--aws_secret_access_key="XXXXXXXX" \
--pretrained_model_name_or_path=$MODEL_NAME \
--instance_data_dir=$INSTANCE_DIR \
--output_dir=$OUTPUT_DIR \
--with_prior_preservation --prior_loss_weight=1.0 \
--instance_prompt="a photo of sks cat" \
--class_prompt="a photo of cat" \
--resolution=512 \
--train_batch_size=1 \
--gradient_accumulation_steps=1 \
--learning_rate=5e-6 \
--lr_scheduler="constant" \
--lr_warmup_steps=0 \
--num_class_images=200 \
--max_train_steps=800
and here is the output of my accelerate config file:
base_job_name: accelerate-sagemaker-1
compute_environment: AMAZON_SAGEMAKER
distributed_type: 'NO'
ec2_instance_type: ml.p3.2xlarge
iam_role_name: accelerate_sagemaker_execution_role
image_uri: null
mixed_precision: FP16
num_machines: 1
profile: null
py_version: py38
pytorch_version: 1.10.2
region: us-east-1
sagemaker_inputs_file: null
sagemaker_metrics_file: null
transformers_version: 4.17.0
use_cpu: false
Any clues on what I could be doing wrong?
To zoom out, what I am trying to achieve is fine-tune Dreambooth on Sagemaker and save the resulting artifacts on S3.
Thank you for your time and assistance!