Sweep on accelerate script

I’m using Huggingface Accelerate library and also using Wandb to trace everything.
I use a script regulated by Accelerate to start my python script, where I create a wandb_tracker using accelerator inside. How can I sweep over a hyperparamter that I set in config.yaml, and keep logging everything onto wandb?

accelerate launch \
    --gpu_ids 0 \
    my_script_with_accelerator_and_wandb.py \
    --config_file config.yaml

Here is how I interact with Wandb

    accelerator = Accelerator(
        # device_placement='auto',  
        log_with= 'wandb', 
        mixed_precision='bf16', # turn on bf16
        wandb_tracker = accelerator.get_tracker("wandb")

Hello, This a reply from our support bot designed to assist you with your Weights & Biases related queries. To reach a human please reply to this message.

To integrate Hugging Face Accelerate with Weights & Biases for hyperparameter sweeping and configure a W&B sweep using a config.yaml file, follow these steps:

  1. Define Your Sweep Configuration: First, you need to define your sweep configuration in a YAML file. This file will specify the hyperparameters you want to sweep over, the method of sweeping (e.g., grid, random), and any other sweep settings.

    Example sweep_config.yaml:

    method: random  # or grid, bayes
      name: val_loss
      goal: minimize
        min: 0.0001
        max: 0.1
        values: [16, 32, 64]
  2. Initialize the Sweep: Use the W&B CLI to initialize the sweep. This step creates the sweep on the W&B server and gives you a sweep ID.

    wandb sweep sweep_config.yaml

    After running this command, you’ll receive a sweep ID, something like: abc123.

  3. Modify Your Script for W&B and Accelerate: Ensure your script is set up to use both W&B and Accelerate. When using Accelerate, you typically initialize it as shown in your question. To integrate W&B sweeps, you’ll need to fetch the sweep configuration from W&B inside your script and use those values to set up your model, data, etc.

    Example snippet to integrate W&B sweep config with Accelerate:

    import wandb
    from accelerate import Accelerator
    def main():
        # Initialize a W&B run
        # Access the sweep parameters
        config = wandb.config
        # Your model, training, and validation code here
        # Use config parameters, e.g., config.learning_rate, config.batch_size
        accelerator = Accelerator(
            # Other Accelerator arguments
        wandb_tracker = accelerator.get_tracker("wandb")
        # Example: using config parameters
        # model = MyModel(learning_rate=config.learning_rate)
        # Don't forget to log metrics to W&B
        # wandb.log({"metric_name": metric_value})
    if __name__ == "__main__":
  4. Launch the Sweep: Use the accelerate launch command along with the W&B agent command to start your sweep. You’ll need to replace sweep_id with the ID you received when you initialized the sweep.

    accelerate launch --gpu_ids 0 my_script_with_accelerator_and_wandb.py --config_file config.yaml

    To automate the process of joining the sweep for multiple runs, you can incorporate the W&B agent command into your script or a separate script that calls accelerate launch.

Troubleshooting Tips:

  • Ensure your config.yaml is correctly formatted and includes all necessary hyperparameters.
  • Check that your script correctly uses the hyperparameters from wandb.config.
  • If you encounter issues with re-initializing the Accelerator, ensure you’re not inadvertently creating multiple instances within a single run or across sweeps.

For more detailed guidance on setting up sweeps and integrating with Hugging Face Accelerate, refer to the Weights & Biases documentation on sweeps and the Hugging Face Accelerate documentation.

To reach a human please reply to this message.

-WandBot :robot:

Hi WandBot,

Thanks for trying to reply but that doesn’t solve my problem. My main concern is that wandb sweep agents should be started via CLI, but now my CLI needs to be used to start an Accelerate agent.

Hi @kerkathy! Thank you so much for elaborating! We do have an option of creating a sweep and calling it using the Python SDK. We have our docs on it here. Would this fit your workflow?

Hi there, I wanted to follow up on this request. Please let us know if we can be of further assistance or if your issue has been resolved.

Hi, since we have not heard back from you, we are going to close this request. If you would like to reopen the conversation, please let us know! Unfortunately, at the moment, we do not receive notifications if a thread reopens on Discourse. So, please feel free to create a new ticket regarding your concern if you’d like to continue the conversation.