flash-attention/training/configs/mode/profile.yaml

# @package _global_
# Run the Pytorch profiler

trainer:
  profiler:
    _target_: pytorch_lightning.profilers.PyTorchProfiler
    dirpath: ${hydra.run.dir}
    schedule:
      _target_: torch.profiler.schedule
      wait: 5
      warmup: 5
      active: 5
    use_cuda: True
  max_steps: 20

logger:
  wandb:
    mode: disabled

callbacks:
  model_checkpoint: null
  model_checkpoint_progress: null
  early_stopping: null

hydra:
  # sets output paths for all file logs to 'logs/profile/'
  run:
    dir: ${oc.env:RESULT_DIR,${work_dir}/logs}/profile/${now:%Y-%m-%d}/${now:%H-%M-%S}
  sweep:
    dir: ${oc.env:RESULT_DIR,${work_dir}/logs}/profile/multirun_${now:%Y-%m-%d_%H-%M-%S}
    subdir: ${hydra.job.num}