# [REQUIRED] path to store logs/checkpoints
output_path: ~/Documents/save


# [OPTIONAL] path where pretrained models are stored
#model_path: ~/Documents/models


# global datasets
global_dataset_paths:
  imagenet1k: ~/Documents/data/imagenet1k
  cifar10: ~/Documents/data/cifar10
  ade20k: ~/Documents/data/ade20k


# [OPTIONAL] path to (fast, possible non-persistent) local storage
#   datasets are copied/unzipped/... from global_dataset_path to this path before training
#local_dataset_path: ~/Documents/data_local


# [OPTIONAL] the account name is only used to describe from which account the run was started from
#   this is more descriptive than the hostname as it also specifies who ran it
#   default: anonymous
account_name: dev


# [OPTIONAL] set environment variables
#    TORCH_HOME for storing torchhub models
#    TORCH_MODEL_ZOO for storing torchvision pretrained models
env:
  TORCH_HOME: ~/Documents/torch/home
  TORCH_MODEL_ZOO: ~/Documents/torch/model_zoo


# [OPTIONAL] how to use weights & biases for experiment tracking
#   disabled (default) -> don't use wandb
#   offline -> use wandb in offline mode
#   online -> use wandb in online mode
#default_wandb_mode: disabled


# [OPTIONAL] master port for multi-GPU setting
#   default: random master_port in [20000, 60000]
#   if int: fixed master_port -> can lead to conflicts if e.g. starting two multi-GPU runs on the same device
#   if [int, int]: master_port is sampled from this range
#master_port: 43895


# [OPTIONAL] cudnn benchmark
#   if you want reproducability: benchmark=False deterministic=True
#   if you want speed: benchmark=True deterministic=False
#   default: true
default_cudnn_benchmark: false
default_cudnn_deterministic: true


# [OPTIONAL] cuda profiling
#   cuda profiling (will introduce torch.cuda.synchronize() calls at each @profile or @named_profile call)
#   can be used to estimate runtimes of different code parts
#   WARNING: if true, this heavily slows down training due to synchronization points
#   default: false
default_cuda_profiling: false


# [OPTIONAL] replace BatchNorm layers with SyncBatchnorm layers
#   (synchronized batch statistics over GPUs in multi-GPU setting)
#   default: true
default_sync_batchnorm: true