csv_logs¶

Classes

`CSVLogger`	Log to local file system in yaml and CSV format.
`ExperimentWriter`	Experiment writer for CSVLogger.

CSV logger¶

CSV logger for basic experiment logging that does not require opening ports

class lightning.pytorch.loggers.csv_logs.CSVLogger(save_dir, name='lightning_logs', version=None, prefix='', flush_logs_every_n_steps=100)[source]¶

Bases: Logger, CSVLogger

Log to local file system in yaml and CSV format.

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

Example

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

Parameters

save_dir¶ (Union[str, Path]) – Save directory
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).

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

property experiment: _ExperimentWriter¶

Actual _ExperimentWriter object. To use _ExperimentWriter features in your LightningModule 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 root_dir: str¶

Parent directory for all checkpoint subdirectories.

If the experiment name parameter is an empty string, no experiment subdirectory is used and the checkpoint will be saved in “save_dir/version”

Return type: str

property save_dir: str¶

The current directory where logs are saved.

Return type: str
Returns: The path to current directory where logs are saved.

class lightning.pytorch.loggers.csv_logs.ExperimentWriter(log_dir)[source]¶

Bases: _ExperimentWriter

Experiment writer for CSVLogger.

Currently, supports to log hyperparameters and metrics in YAML and CSV format, respectively.

Parameters: log_dir¶ (str) – Directory for the experiment logs

log_hparams(params)[source]¶

Record hparams.

Return type: None

save()[source]¶

Save recorded hparams and metrics into files.

Return type: None