codes.utils.utils

Functions

check_training_status(config)	Check if the training is already completed by looking for a completion marker file.
create_model_dir([base_dir, subfolder, ...])	Create a directory based on a unique identifier inside a specified subfolder of the base directory.
get_progress_bar(tasks)	Create a progress bar with a specific description.
load_and_save_config([config_path, save])	Load configuration from a YAML file and save a copy to the specified directory.
load_task_list(filepath)	Load a list of tasks from a JSON file.
make_description(mode, device, metric, ...)	Create a formatted description for the progress bar that ensures consistent alignment.
nice_print(message[, width])	Print a message in a nicely formatted way with a fixed width.
read_yaml_config(config_path)
save_task_list(tasks, filepath)	Save a list of tasks to a JSON file.
set_random_seeds(seed)	Set random seeds for reproducibility.
time_execution(func)	Decorator to time the execution of a function and store the duration as an attribute of the function.
worker_init_fn(worker_id)	Initialize the random seed for each worker in PyTorch DataLoader.