CSVLogger

class lightning.fabric.loggers.CSVLogger(root_dir, name='lightning_logs', version=None, prefix='', flush_logs_every_n_steps=100)[source]

Bases: Logger

Log to the local file system in CSV format.

Logs are saved to os.path.join(root_dir, name, version).

Parameters:

root_dir (Union[str, Path]) – The root directory in which all your experiments with different names and versions will be stored.
name (Optional[str]) – Experiment name. Defaults to 'lightning_logs'. If name is None, logs (versions) will be stored to the save dir directly.
version (Union[int, str, None]) – Experiment version. If version is not specified the logger inspects the save directory for existing versions, then automatically assigns the next available version. If the version is specified, and the directory already contains a metrics file for that version, it will be overwritten.
prefix (str) – A string to put at the beginning of metric keys.
flush_logs_every_n_steps (int) – How often to flush logs to disk (defaults to every 100 steps).

Example:

from lightning.fabric.loggers import CSVLogger

logger = CSVLogger("path/to/logs/root", name="my_model")
logger.log_metrics({"loss": 0.235, "acc": 0.75})
logger.finalize("success")

finalize(status)[source]

Do any processing that is necessary to finalize an experiment.

Parameters:: status (str) – Status that the experiment finished with (e.g. success, failed, aborted)
Return type:: None

log_hyperparams(params)[source]

Record hyperparameters.

Parameters:

params (Union[dict[str, Any], Namespace]) – Namespace or Dict containing the hyperparameters
args – Optional positional arguments, depends on the specific logger being used
kwargs – Optional keyword arguments, depends on the specific logger being used

Return type:

None

log_metrics(metrics, step=None)[source]

Records metrics. This method logs metrics as soon as it received them.

Parameters:

metrics (dict[str, Union[Tensor, float]]) – Dictionary with metric names as keys and measured quantities as values
step (Optional[int]) – Step number at which the metrics should be recorded

Return type:

None

save()[source]

Save log data.

Return type:: None

property experiment: _ExperimentWriter

Actual ExperimentWriter object. To use ExperimentWriter features anywhere in your code, do the following.

Example:

self.logger.experiment.some_experiment_writer_function()

property log_dir: str

The log directory for this run.

By default, it is named 'version_${self.version}' but it can be overridden by passing a string value for the constructor’s version parameter instead of None or an int.

property name: str

Gets the name of the experiment.

Returns:: The name of the experiment.

property root_dir: str: Gets the save directory where the versioned CSV experiments are saved.

property version: Union[int, str]

Gets the version of the experiment.

Returns:: The version of the experiment if it is specified, else the next version.