CSVLogger¶

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

Bases: lightning_fabric.loggers.logger.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¶ (str) – Experiment name. Defaults to 'lightning_logs'.
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.
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: lightning_fabric.loggers.csv_logs._ExperimentWriter¶

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

Example:

self.logger.experiment.some_experiment_writer_function()

Return type: _ExperimentWriter

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.

Return type: str

property name: str¶

Gets the name of the experiment.

Return type: str
Returns: The name of the experiment.

property root_dir: str¶

Gets the save directory where the versioned CSV experiments are saved.

Return type: str

property version: Union[int, str]¶

Gets the version of the experiment.

Return type: Union[int, str]
Returns: The version of the experiment if it is specified, else the next version.