fruit_project.utils.logging

Functions

initwandb(→ wandb.sdk.wandb_run.Run)

Initializes a wandb run.

get_run_name(→ str)

Generates a run name based on the configuration.

log_images(, mean, std)

Logs a grid of images with their bounding boxes to wandb.

log_transforms(, id2lbl, transforms, mean, std)

Logs a grid of transformed images with their bounding boxes to wandb.

log_training_time(→ None)

Logs the elapsed training time.

log_model_params(→ None)

Logs the total and trainable parameters of a model.

log_class_value_counts(→ None)

Logs the class distribution of a dataset.

log_checkpoint_artifact(→ None)

Logs a model checkpoint as a wandb artifact.

log_detection_confusion_matrix(→ None)

Logs a detection confusion matrix plot to wandb.

Module Contents

fruit_project.utils.logging.initwandb(cfg: omegaconf.DictConfig) → wandb.sdk.wandb_run.Run[source]

Initializes a wandb run.

Parameters:

cfg (DictConfig) – Configuration object.

Returns:

The wandb run object.

Return type:

Run

fruit_project.utils.logging.get_run_name(cfg: omegaconf.DictConfig) → str[source]

Generates a run name based on the configuration.

Parameters:

cfg (DictConfig) – Configuration object.

Returns:

The generated run name.

Return type:

str

fruit_project.utils.logging.log_images(run: wandb.sdk.wandb_run.Run, batch: Tuple[Dict, List], id2lbl: Dict, grid_size: Tuple[int, int] = (3, 3), mean: torch.Tensor | None = None, std: torch.Tensor | None = None) → None[source]

Logs a grid of images with their bounding boxes to wandb.

Parameters:

  • run (Run) – The wandb run object.

  • batch (Tuple[Dict, List]) – A single batch of data (processed_batch, targets).

  • id2lbl (Dict) – A dictionary mapping class IDs to labels.

  • grid_size (Tuple[int, int], optional) – The grid size for displaying images. Defaults to (3, 3).

  • mean (Optional[torch.Tensor], optional) – The mean used for normalization. Defaults to None.

  • std (Optional[torch.Tensor], optional) – The standard deviation used for normalization. Defaults to None.

fruit_project.utils.logging.log_transforms(run: wandb.sdk.wandb_run.Run, batch: Tuple[Dict, List], grid_size: Tuple[int, int] = (3, 3), id2lbl: Dict | None = None, transforms: Dict | None = None, mean: torch.Tensor | None = None, std: torch.Tensor | None = None) → None[source]

Logs a grid of transformed images with their bounding boxes to wandb.

Parameters:

  • run (Run) – The wandb run object.

  • batch (Tuple[Dict, List]) – A single batch of data (processed_batch, targets).

  • grid_size (Tuple[int, int], optional) – The grid size for displaying images. Defaults to (3, 3).

  • id2lbl (Optional[Dict], optional) – A dictionary mapping class IDs to labels. Defaults to None.

  • transforms (Optional[Dict], optional) – The transforms applied. Defaults to None.

  • mean (Optional[torch.Tensor], optional) – The mean used for normalization. Defaults to None.

  • std (Optional[torch.Tensor], optional) – The standard deviation used for normalization. Defaults to None.

fruit_project.utils.logging.log_training_time(run: wandb.sdk.wandb_run.Run, start_time: float) → None[source]

Logs the elapsed training time.

Parameters:

  • run (Run) – The wandb run object.

  • start_time (float) – The start time of training.

fruit_project.utils.logging.log_model_params(run: wandb.sdk.wandb_run.Run, model: torch.nn.Module) → None[source]

Logs the total and trainable parameters of a model.

Parameters:

  • run (Run) – The wandb run object.

  • model (nn.Module) – The model.

fruit_project.utils.logging.log_class_value_counts(run: wandb.sdk.wandb_run.Run, samples: List[Tuple[str, str]], stage: str = 'Train') → None[source]

Logs the class distribution of a dataset.

Parameters:

  • run (Run) – The wandb run object.

  • samples (List[Tuple[Any, Any]]) – A list of samples (e.g., [(image, label), …]).

  • stage (str, optional) – The dataset stage (e.g., ‘Train’, ‘Test’). Defaults to “Train”.

fruit_project.utils.logging.log_checkpoint_artifact(run: wandb.sdk.wandb_run.Run, path: str, name: str, epoch: int, wait: bool = False) → None[source]

Logs a model checkpoint as a wandb artifact.

Parameters:

  • run (Run) – The wandb run object.

  • path (str) – The path to the checkpoint file.

  • name (str) – The name of the artifact.

  • epoch (int) – The epoch number.

  • wait (bool, optional) – Whether to wait for the artifact to be uploaded. Defaults to False.

fruit_project.utils.logging.log_detection_confusion_matrix(run: wandb.sdk.wandb_run.Run, cm_object: fruit_project.utils.metrics.ConfusionMatrix, class_names: List[str]) → None[source]

Logs a detection confusion matrix plot to wandb.

Parameters:

  • run (Run) – The wandb run object.

  • cm_object (ConfusionMatrix) – The confusion matrix object.

  • class_names (List[str]) – The list of class names.