CSVLogger

class pytorch_lightning.loggers.CSVLogger(save_dir, name='default', version=None, prefix='')[source]

Bases: pytorch_lightning.loggers.base.LightningLoggerBase

Log to local file system in yaml and CSV format.

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

Example

>>> from pytorch_lightning import Trainer
>>> from pytorch_lightning.loggers import CSVLogger
>>> logger = CSVLogger("logs", name="my_exp_name")
>>> trainer = Trainer(logger=logger)

Parameters

save_dir (str) – Save directory
name (Optional[str]) – Experiment name. Defaults to 'default'.
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.

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 containing the hyperparameters
args – Optional positional arguments, depends on the specific logger being used
kwargs – Optional keywoard arguments, depends on the specific logger being used

Return type

None

log_metrics(metrics, step=None)[source]

Records metrics. This method logs metrics as as soon as it received them. If you want to aggregate metrics for one specific step, use the agg_and_log_metrics() method.

Parameters

metrics (Dict[str, 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: pytorch_lightning.loggers.csv_logs.ExperimentWriter

Actual ExperimentWriter object. To use ExperimentWriter features in your LightningModule 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: Return the experiment name.

property root_dir: str: Parent directory for all checkpoint subdirectories. If the experiment name parameter is None or the empty string, no experiment subdirectory is used and the checkpoint will be saved in “save_dir/version_dir”

property save_dir: Optional[str]: Return the root directory where experiment logs get saved, or None if the logger does not save data locally.

property version: int: Return the experiment version.