deeplabcut.pose_estimation_pytorch.config.logger

Logger configuration classes for DeepLabCut training runs.

Classes:

Name	Description
CSVLoggerConfig	Configuration for CSV logger.
LoggerConfig	Base configuration for all loggers.
WandbLoggerConfig	Configuration for Weights & Biases (wandb) logger.

CSVLoggerConfig

Bases: LoggerConfig

Configuration for CSV logger.

This logger saves training stats and metrics to a CSV file.

Attributes:

Name	Type	Description
type	Literal[CSVLogger]	Logger type (should be 'CSVLogger')
train_folder	str	The path of the folder containing training files.
log_filename	str	The name of the file in which to store training stats

Source code in deeplabcut/pose_estimation_pytorch/config/logger.py

class CSVLoggerConfig(LoggerConfig):  #
    """Configuration for CSV logger.

    This logger saves training stats and metrics to a CSV file.

    Attributes:
        type: Logger type (should be 'CSVLogger')
        train_folder: The path of the folder containing training files.
        log_filename: The name of the file in which to store training stats
    """

    type: Literal[LoggerType.CSVLogger]
    train_folder: str = ""
    log_filename: str = "learning_stats.csv"

LoggerConfig

Bases: DLCBaseConfig

Base configuration for all loggers.

Attributes:

Name	Type	Description
type	str	The type of logger to use (WandbLogger or CSVLogger)

Source code in deeplabcut/pose_estimation_pytorch/config/logger.py

class LoggerConfig(DLCBaseConfig):
    """Base configuration for all loggers.

    Attributes:
        type: The type of logger to use (WandbLogger or CSVLogger)
    """

    type: str

WandbLoggerConfig

Bases: LoggerConfig

Configuration for Weights & Biases (wandb) logger.

This logger tracks experiments and logs data to Weights & Biases. Refer to: https://docs.wandb.ai/guides for more information.

Attributes:

Name	Type	Description
type	Literal[WandbLogger]	Logger type (should be 'WandbLogger')
project_name	str	The name of the wandb project
run_name	str	The name of the wandb run
image_log_interval	int | None	How often train/test images are logged in epochs (if None, train/test inputs are never logged)
model	dict | None	The model architecture to log
train_folder	str | None	The path of the folder containing training files.
wandb_kwargs	dict | None	Additional keyword arguments to pass to wandb.init

Source code in deeplabcut/pose_estimation_pytorch/config/logger.py

class WandbLoggerConfig(LoggerConfig):  #
    """Configuration for Weights & Biases (wandb) logger.

    This logger tracks experiments and logs data to Weights & Biases.
    Refer to: https://docs.wandb.ai/guides for more information.

    Attributes:
        type: Logger type (should be 'WandbLogger')
        project_name: The name of the wandb project
        run_name: The name of the wandb run
        image_log_interval: How often train/test images are logged in epochs
            (if None, train/test inputs are never logged)
        model: The model architecture to log
        train_folder: The path of the folder containing training files.
        wandb_kwargs: Additional keyword arguments to pass to wandb.init
    """

    type: Literal[LoggerType.WandbLogger]
    project_name: str = "deeplabcut"
    run_name: str = "tmp"
    image_log_interval: int | None = None
    model: dict | None = None
    train_folder: str | None = None
    wandb_kwargs: dict | None = None