reference/generated/torchrl.record.loggers.ProcessLogger

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ProcessLogger

torchrl.record.loggers.ProcessLogger(logger_cls: type[LoggerT], *args: Any, mp_context: str | mp.context.BaseContext | None = None, max_queue_size: int = 1000, startup_timeout: float = 60.0, **kwargs: Any) → None

Driver-owned logger service running in a dedicated process.

The concrete logger is constructed once in the child process. Worker-side clients can only submit log_* calls; only this owner can flush or stop the service.

Parameters:

• logger_cls – Concrete Logger class.

• *args – Positional arguments passed to logger_cls.

• mp_context – Multiprocessing context or start-method name. Defaults to "spawn".

• max_queue_size – Maximum number of pending logging commands. Defaults to 1000.

• startup_timeout – Seconds to wait for logger construction. Defaults to 60.

• **kwargs – Keyword arguments passed to logger_cls.

Examples

>>> from torchrl.record.loggers import CSVLogger, ProcessLogger
>>> logger = ProcessLogger(CSVLogger, exp_name="run", log_dir="/tmp")
>>> worker_logger = logger.client()
>>> worker_logger.log_scalar("loss", 1.0, step=0)
>>> logger.shutdown()