Environment settingsΒΆ
Environment settings are designed to set basic parameters of running environment.
gpu_id (int or str)
: The id of GPU device. Defaults to0
.use_gpu (bool)
: Whether or not to use GPU. If True, using GPU, else using CPU. Defaults toTrue
.seed (int)
: Random seed. Defaults to2020
.state (str)
: Logging level. Defaults to'INFO'
. Range in['INFO', 'DEBUG', 'WARNING', 'ERROR', 'CRITICAL']
.encoding (str)
: Encoding to use for reading atomic files. Defaults to'utf-8'
. The available encoding can be found in here.reproducibility (bool)
: If True, the tool will use deterministic convolution algorithms, which makes the result reproducible. If False, the tool will benchmark multiple convolution algorithms and select the fastest one, which makes the result not reproducible but can speed up model training in some case. Defaults toTrue
.data_path (str)
: The path of input dataset. Defaults to'dataset/'
.checkpoint_dir (str)
: The path to save checkpoint file. Defaults to'saved/'
.show_progress (bool)
: Show the progress of training epoch and evaluate epoch. Defaults toTrue
.save_dataset (bool)
: Whether or not save filtered dataset. If True, save filtered dataset, otherwise it will not be saved. Defaults toFalse
.dataset_save_path (str)
: The path of saved dataset. The tool will attempt to load the dataset from this path. If it equals toNone
, the tool will try to load the dataset from{checkpoint_dir}/{dataset}-{dataset_class_name}.pth
. If the config of saved dataset is not equal to current config, the tool will create dataset from scratch. Defaults toNone
.save_dataloaders (bool)
: Whether or not save split dataloaders. If True, save split dataloaders, otherwise they will not be saved. Defaults toFalse
.dataloaders_save_path (str)
: The path of saved dataloaders. The tool will attempt to load the dataloaders from this path. If it equals toNone
, the tool will try to load the dataloaders from{checkpoint_dir}/{dataset}-for-{model}-dataloader.pth
. If the config of saved dataloaders is not equal to current config, the tool will create dataloaders from scratch. Defaults toNone
.log_wandb (bool)
: Whether or not use Weights & Biases(W&B). If True, use W&B to visualize configs and metrics of different experiments, otherwise it will not be used. Defaults toFalse
.wandb_project (str)
: The project to conduct experiment in W&B. Defaults to'recbole'
.