# @package _global_

defaults:
  - override /logger: null

# default debugging setup, runs 1 full epoch
# other debugging configs can inherit from this one

# overwrite task name so debugging logs are stored in separate folder
task_name: "debug"

extras:
  ignore_warnings: False
  enforce_tags: False

# sets level of all command line loggers to 'DEBUG'
# https://hydra.cc/docs/tutorials/basic/running_your_app/logging/
hydra:
  job_logging:
    root:
      level: DEBUG
  # use the below to also set hydra loggers to 'DEBUG'
  verbose: True

# Print example ID before forward pass
callbacks:
  print_example_id_before_forward_pass:
      _target_: modelhub.callbacks.train_logging.PrintExampleIDBeforeForwardPassCallback

dataloader:
  train:
    dataloader_params: 
      batch_size: 1
      num_workers: 0  # debuggers don't like multiprocessing -- work on main thread
      pin_memory: False  # disable gpu memory pin
      prefetch_factor: null # must be null for num_workers=0
    n_fallback_retries: 0 # disable fallback retries for debugging

  val:
    dataloader_params:
      batch_size: 1
      num_workers: 0
      pin_memory: False
      prefetch_factor: null # must be null for num_workers=0


datasets:
  crop_size: 100  # set small crop size for quick debugging
  diffusion_batch_size_train: 1
  diffusion_batch_size_inference: 1
  n_recycles_train: 1
  n_recycles_validation: 1
  n_msa: 128
  key_to_balance: null # otherwise big examples will be processed first

trainer:
  devices_per_node: 1
  limit_train_batches: 1
  limit_val_batches: 1
  validate_every_n_epochs: 1

# Set tags to help identify debugging runs
tags:
  - debug