logger

logger#

Source code: tianshou/highlevel/logger.py

class LoggerFactory[source]#

Bases: ToStringMixin, ABC

abstract create_logger(log_dir: str, experiment_name: str, run_id: str | None, config_dict: dict | None = None) → BaseLogger[source]#

Creates the logger.

Parameters:

log_dir – path to the directory in which log data is to be stored
experiment_name – the name of the job, which may contain os.path.delimiter
run_id – a unique name, which, depending on the logging framework, may be used to identify the logger
config_dict – a dictionary with data that is to be logged

Returns:

the logger

abstract get_logger_class() → type[BaseLogger][source]#: Returns the class of the logger that is to be created.

class LoggerFactoryDefault(logger_type: Literal['tensorboard', 'wandb', 'pandas'] = 'tensorboard', wand_entity: str | None = None, wandb_project: str | None = None, group: str | None = None, job_type: str | None = None, save_interval: int | None = None)[source]#

Bases: LoggerFactory

Parameters:: save_interval – the interval size (in env steps) after which the checkpoint and end of epoch related logs will be saved.

create_logger(log_dir: str, experiment_name: str, run_id: str | None, config_dict: dict | None = None) → BaseLogger[source]#