Remove num_worker from config

src/batdetect2/api_v2.py

@@ -15,7 +15,7 @@ from batdetect2.data import (
     load_dataset_from_config,
 )
 from batdetect2.data.datasets import Dataset
-from batdetect2.evaluate import DEFAULT_EVAL_DIR, build_evaluator, evaluate
+from batdetect2.evaluate import DEFAULT_EVAL_DIR, build_evaluator, run_evaluate
 from batdetect2.evaluate.types import EvaluatorProtocol
 from batdetect2.inference import process_file_list, run_batch_inference
 from batdetect2.logging import DEFAULT_LOGS_DIR
@@ -81,8 +81,8 @@ class BatDetect2API:
         self,
         train_annotations: Sequence[data.ClipAnnotation],
         val_annotations: Sequence[data.ClipAnnotation] | None = None,
-        train_workers: int | None = None,
-        val_workers: int | None = None,
+        train_workers: int = 0,
+        val_workers: int = 0,
         checkpoint_dir: Path | None = DEFAULT_CHECKPOINT_DIR,
         log_dir: Path | None = DEFAULT_LOGS_DIR,
         experiment_name: str | None = None,
@@ -113,19 +113,21 @@ class BatDetect2API:
     def evaluate(
         self,
         test_annotations: Sequence[data.ClipAnnotation],
-        num_workers: int | None = None,
+        num_workers: int = 0,
         output_dir: data.PathLike = DEFAULT_EVAL_DIR,
         experiment_name: str | None = None,
         run_name: str | None = None,
         save_predictions: bool = True,
     ) -> tuple[dict[str, float], list[list[Detection]]]:
-        return evaluate(
+        return run_evaluate(
             self.model,
             test_annotations,
             targets=self.targets,
             audio_loader=self.audio_loader,
             preprocessor=self.preprocessor,
-            config=self.config,
+            audio_config=self.config.audio,
+            evaluation_config=self.config.evaluation,
+            output_config=self.config.outputs,
             num_workers=num_workers,
             output_dir=output_dir,
             experiment_name=experiment_name,
@@ -235,7 +237,7 @@ class BatDetect2API:
     def process_files(
         self,
         audio_files: Sequence[data.PathLike],
-        num_workers: int | None = None,
+        num_workers: int = 0,
     ) -> list[ClipDetections]:
         return process_file_list(
             self.model,
@@ -251,7 +253,7 @@ class BatDetect2API:
         self,
         clips: Sequence[data.Clip],
         batch_size: int | None = None,
-        num_workers: int | None = None,
+        num_workers: int = 0,
     ) -> list[ClipDetections]:
         return run_batch_inference(
             self.model,

src/batdetect2/evaluate/__init__.py

@@ -1,5 +1,5 @@
 from batdetect2.evaluate.config import EvaluationConfig, load_evaluation_config
-from batdetect2.evaluate.evaluate import DEFAULT_EVAL_DIR, evaluate
+from batdetect2.evaluate.evaluate import DEFAULT_EVAL_DIR, run_evaluate
 from batdetect2.evaluate.evaluator import Evaluator, build_evaluator
 from batdetect2.evaluate.tasks import TaskConfig, build_task
 
@@ -9,7 +9,7 @@ __all__ = [
     "TaskConfig",
     "build_evaluator",
     "build_task",
-    "evaluate",
+    "run_evaluate",
     "load_evaluation_config",
     "DEFAULT_EVAL_DIR",
 ]

src/batdetect2/evaluate/dataset.py

@@ -67,7 +67,6 @@ class TestDataset(Dataset[TestExample]):
 
 
 class TestLoaderConfig(BaseConfig):
-    num_workers: int = 0
     clipping_strategy: ClipConfig = Field(
         default_factory=lambda: PaddedClipConfig()
     )
@@ -78,7 +77,7 @@ def build_test_loader(
     audio_loader: AudioLoader | None = None,
     preprocessor: PreprocessorProtocol | None = None,
     config: TestLoaderConfig | None = None,
-    num_workers: int | None = None,
+    num_workers: int = 0,
 ) -> DataLoader[TestExample]:
     logger.info("Building test data loader...")
     config = config or TestLoaderConfig()
@@ -94,7 +93,6 @@ def build_test_loader(
         config=config,
     )
 
-    num_workers = num_workers or config.num_workers
     return DataLoader(
         test_dataset,
         batch_size=1,

src/batdetect2/evaluate/evaluate.py

@@ -1,46 +1,47 @@
 from pathlib import Path
-from typing import TYPE_CHECKING, Dict, List, Optional, Sequence, Tuple
+from typing import Sequence
 
 from lightning import Trainer
 from soundevent import data
 
-from batdetect2.audio import build_audio_loader
+from batdetect2.audio import AudioConfig, build_audio_loader
 from batdetect2.audio.types import AudioLoader
+from batdetect2.evaluate import EvaluationConfig
 from batdetect2.evaluate.dataset import build_test_loader
 from batdetect2.evaluate.evaluator import build_evaluator
 from batdetect2.evaluate.lightning import EvaluationModule
 from batdetect2.logging import build_logger
 from batdetect2.models import Model
-from batdetect2.outputs import build_output_transform
+from batdetect2.outputs import OutputsConfig, build_output_transform
 from batdetect2.outputs.types import OutputFormatterProtocol
 from batdetect2.postprocess.types import Detection
 from batdetect2.preprocess.types import PreprocessorProtocol
 from batdetect2.targets.types import TargetProtocol
 
-if TYPE_CHECKING:
-    from batdetect2.config import BatDetect2Config
-
 DEFAULT_EVAL_DIR: Path = Path("outputs") / "evaluations"
 
 
-def evaluate(
+def run_evaluate(
     model: Model,
     test_annotations: Sequence[data.ClipAnnotation],
-    targets: Optional["TargetProtocol"] = None,
-    audio_loader: Optional["AudioLoader"] = None,
-    preprocessor: Optional["PreprocessorProtocol"] = None,
-    config: Optional["BatDetect2Config"] = None,
-    formatter: Optional["OutputFormatterProtocol"] = None,
-    num_workers: int | None = None,
+    targets: TargetProtocol | None = None,
+    audio_loader: AudioLoader | None = None,
+    preprocessor: PreprocessorProtocol | None = None,
+    audio_config: AudioConfig | None = None,
+    evaluation_config: EvaluationConfig | None = None,
+    output_config: OutputsConfig | None = None,
+    formatter: OutputFormatterProtocol | None = None,
+    num_workers: int = 0,
     output_dir: data.PathLike = DEFAULT_EVAL_DIR,
     experiment_name: str | None = None,
     run_name: str | None = None,
-) -> Tuple[Dict[str, float], List[List[Detection]]]:
-    from batdetect2.config import BatDetect2Config
+) -> tuple[dict[str, float], list[list[Detection]]]:
 
-    config = config or BatDetect2Config()
+    audio_config = audio_config or AudioConfig()
+    evaluation_config = evaluation_config or EvaluationConfig()
+    output_config = output_config or OutputsConfig()
 
-    audio_loader = audio_loader or build_audio_loader(config=config.audio)
+    audio_loader = audio_loader or build_audio_loader(config=audio_config)
 
     preprocessor = preprocessor or model.preprocessor
     targets = targets or model.targets
@@ -52,15 +53,15 @@ def evaluate(
         num_workers=num_workers,
     )
 
-    evaluator = build_evaluator(config=config.evaluation, targets=targets)
+    evaluator = build_evaluator(config=evaluation_config, targets=targets)
 
     logger = build_logger(
-        config.evaluation.logger,
+        evaluation_config.logger,
         log_dir=Path(output_dir),
         experiment_name=experiment_name,
         run_name=run_name,
     )
-    output_transform = build_output_transform(config=config.outputs.transform)
+    output_transform = build_output_transform(config=output_config.transform)
     module = EvaluationModule(
         model,
         evaluator,

src/batdetect2/inference/batch.py

@@ -28,7 +28,7 @@ def run_batch_inference(
     preprocessor: Optional["PreprocessorProtocol"] = None,
     config: Optional["BatDetect2Config"] = None,
     output_transform: Optional[OutputTransformProtocol] = None,
-    num_workers: int | None = None,
+    num_workers: int = 1,
     batch_size: int | None = None,
 ) -> List[ClipDetections]:
     from batdetect2.config import BatDetect2Config
@@ -75,7 +75,7 @@ def process_file_list(
     targets: Optional["TargetProtocol"] = None,
     audio_loader: Optional["AudioLoader"] = None,
     preprocessor: Optional["PreprocessorProtocol"] = None,
-    num_workers: int | None = None,
+    num_workers: int = 0,
 ) -> List[ClipDetections]:
     clip_config = config.inference.clipping
     clips = get_clips_from_files(

src/batdetect2/inference/dataset.py

@@ -61,7 +61,6 @@ class InferenceDataset(Dataset[DatasetItem]):
 
 
 class InferenceLoaderConfig(BaseConfig):
-    num_workers: int = 0
     batch_size: int = 8
 
 
@@ -70,7 +69,7 @@ def build_inference_loader(
     audio_loader: AudioLoader | None = None,
     preprocessor: PreprocessorProtocol | None = None,
     config: InferenceLoaderConfig | None = None,
-    num_workers: int | None = None,
+    num_workers: int = 0,
     batch_size: int | None = None,
 ) -> DataLoader[DatasetItem]:
     logger.info("Building inference data loader...")
@@ -84,12 +83,11 @@ def build_inference_loader(
 
     batch_size = batch_size or config.batch_size
 
-    num_workers = num_workers or config.num_workers
     return DataLoader(
         inference_dataset,
         batch_size=batch_size,
         shuffle=False,
-        num_workers=config.num_workers,
+        num_workers=num_workers,
         collate_fn=_collate_fn,
     )
 

src/batdetect2/train/dataset.py

@@ -143,8 +143,6 @@ class ValidationDataset(Dataset):
 
 
 class TrainLoaderConfig(BaseConfig):
-    num_workers: int = 0
-
     batch_size: int = 8
 
     shuffle: bool = False
@@ -164,7 +162,7 @@ def build_train_loader(
     labeller: ClipLabeller | None = None,
     preprocessor: PreprocessorProtocol | None = None,
     config: TrainLoaderConfig | None = None,
-    num_workers: int | None = None,
+    num_workers: int = 0,
 ) -> DataLoader:
     config = config or TrainLoaderConfig()
 
@@ -182,7 +180,6 @@ def build_train_loader(
         config=config,
     )
 
-    num_workers = num_workers or config.num_workers
     return DataLoader(
         train_dataset,
         batch_size=config.batch_size,
@@ -193,8 +190,6 @@ def build_train_loader(
 
 
 class ValLoaderConfig(BaseConfig):
-    num_workers: int = 0
-
     clipping_strategy: ClipConfig = Field(
         default_factory=lambda: PaddedClipConfig()
     )
@@ -206,7 +201,7 @@ def build_val_loader(
     labeller: ClipLabeller | None = None,
     preprocessor: PreprocessorProtocol | None = None,
     config: ValLoaderConfig | None = None,
-    num_workers: int | None = None,
+    num_workers: int = 0,
 ):
     logger.info("Building validation data loader...")
     config = config or ValLoaderConfig()
@@ -223,7 +218,6 @@ def build_val_loader(
         config=config,
     )
 
-    num_workers = num_workers or config.num_workers
     return DataLoader(
         val_dataset,
         batch_size=1,

src/batdetect2/train/labels.py

@@ -12,7 +12,7 @@ import torch
 from loguru import logger
 from soundevent import data
 
-from batdetect2.core.configs import BaseConfig, load_config
+from batdetect2.core.configs import BaseConfig
 from batdetect2.preprocess import MAX_FREQ, MIN_FREQ
 from batdetect2.targets import build_targets, iterate_encoded_sound_events
 from batdetect2.targets.types import TargetProtocol
@@ -22,7 +22,6 @@ __all__ = [
     "LabelConfig",
     "build_clip_labeler",
     "generate_heatmaps",
-    "load_label_config",
 ]
 
 
@@ -150,31 +149,3 @@ def generate_heatmaps(
         classes=class_heatmap,
         size=size_heatmap,
     )
-
-
-def load_label_config(
-    path: data.PathLike, field: str | None = None
-) -> LabelConfig:
-    """Load the heatmap label generation configuration from a file.
-
-    Parameters
-    ----------
-    path : data.PathLike
-        Path to the configuration file (e.g., YAML or JSON).
-    field : str, optional
-        If the label configuration is nested under a specific key in the
-        file, specify the key here. Defaults to None.
-
-    Returns
-    -------
-    LabelConfig
-        The loaded and validated label configuration object.
-
-    Raises
-    ------
-    FileNotFoundError
-        If the config file path does not exist.
-    pydantic.ValidationError
-        If the config file structure does not match the LabelConfig schema.
-    """
-    return load_config(path, schema=LabelConfig, field=field)

src/batdetect2/train/train.py

@@ -41,8 +41,8 @@ def run_train(
     model_config: Optional[ModelConfig] = None,
     train_config: Optional[TrainingConfig] = None,
     trainer: Trainer | None = None,
-    train_workers: int | None = None,
-    val_workers: int | None = None,
+    train_workers: int = 0,
+    val_workers: int = 0,
     checkpoint_dir: Path | None = None,
     log_dir: Path | None = None,
     experiment_name: str | None = None,