Add num workers to cli

batdetect2/cli/train.py

@@ -44,7 +44,7 @@ DEFAULT_CONFIG_FILE = Path("config.yaml")
     default=DEFAULT_CONFIG_FILE,
 )
 @click.option(
-    "--train-field",
+    "--train-config-field",
     type=str,
     default="train",
 )
@@ -108,6 +108,16 @@ DEFAULT_CONFIG_FILE = Path("config.yaml")
     type=str,
     default="model",
 )
+@click.option(
+    "--train-workers",
+    type=int,
+    default=0,
+)
+@click.option(
+    "--val-workers",
+    type=int,
+    default=0,
+)
 def train_command(
     train_examples: Path,
     val_examples: Optional[Path] = None,
@@ -122,6 +132,8 @@ def train_command(
     postprocess_config_field: str = "postprocess",
     model_config: Path = DEFAULT_CONFIG_FILE,
     model_config_field: str = "model",
+    train_workers: int = 0,
+    val_workers: int = 0,
 ):
     logger.info("Starting training!")
 
@@ -176,15 +188,27 @@ def train_command(
             targets=targets,
             config=postprocess_config_loaded,
         )
+        logger.debug(
+            "Loaded postprocessor from file {path}",
+            path=train_config,
+        )
     except IOError:
+        logger.debug(
+            "Could not load postprocessor config from file. Using default"
+        )
         postprocessor = build_postprocessor(targets=targets)
 
     try:
         train_config_loaded = load_train_config(
             path=train_config, field=train_config_field
         )
+        logger.debug(
+            "Loaded training config from file {path}",
+            path=train_config,
+        )
     except IOError:
         train_config_loaded = TrainingConfig()
+        logger.debug("Could not load training config from file. Using default")
 
     train_files = list_preprocessed_files(train_examples)
 
@@ -212,4 +236,6 @@ def train_command(
                 ]
             )
         ],
+        train_workers=train_workers,
+        val_workers=val_workers,
     )

batdetect2/configs.py

@@ -88,7 +88,7 @@ def get_object_field(obj: dict, current_key: str) -> Any:
     KeyError: 'x'
     """
     if "." not in current_key:
-        return obj[current_key]
+        return obj.get(current_key, {})
 
     current_key, rest = current_key.split(".", 1)
     subobj = obj[current_key]

batdetect2/targets/__init__.py

@@ -24,6 +24,7 @@ object is via the `build_targets` or `load_targets` functions.
 from typing import List, Optional
 
 import numpy as np
+from pydantic import Field
 from soundevent import data
 
 from batdetect2.configs import BaseConfig, load_config
@@ -157,7 +158,9 @@ class TargetConfig(BaseConfig):
 
     filtering: Optional[FilterConfig] = None
     transforms: Optional[TransformConfig] = None
-    classes: ClassesConfig
+    classes: ClassesConfig = Field(
+        default_factory=lambda: DEFAULT_CLASSES_CONFIG
+    )
     roi: Optional[ROIConfig] = None
 
 
@@ -438,6 +441,84 @@ class Targets(TargetProtocol):
         return self._roi_mapper.recover_roi(pos, dims)
 
 
+DEFAULT_CLASSES = [
+    TargetClass(
+        tags=[TagInfo(value="Myotis mystacinus")],
+        name="myomys",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Myotis alcathoe")],
+        name="myoalc",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Eptesicus serotinus")],
+        name="eptser",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Pipistrellus nathusii")],
+        name="pipnat",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Barbastellus barbastellus")],
+        name="barbar",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Myotis nattereri")],
+        name="myonat",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Myotis daubentonii")],
+        name="myodau",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Myotis brandtii")],
+        name="myobra",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Pipistrellus pipistrellus")],
+        name="pippip",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Myotis bechsteinii")],
+        name="myobec",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Pipistrellus pygmaeus")],
+        name="pippyg",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Rhinolophus hipposideros")],
+        name="rhihip",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Nyctalus leisleri")],
+        name="nyclei",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Rhinolophus ferrumequinum")],
+        name="rhifer",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Plecotus auritus")],
+        name="pleaur",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Nyctalus noctula")],
+        name="nycnoc",
+    ),
+    TargetClass(
+        tags=[TagInfo(value="Plecotus austriacus")],
+        name="pleaus",
+    ),
+]
+
+
+DEFAULT_CLASSES_CONFIG: ClassesConfig = ClassesConfig(
+    classes=DEFAULT_CLASSES,
+    generic_class=[TagInfo(value="Bat")],
+)
+
+
 DEFAULT_TARGET_CONFIG: TargetConfig = TargetConfig(
     filtering=FilterConfig(
         rules=[
@@ -455,79 +536,7 @@ DEFAULT_TARGET_CONFIG: TargetConfig = TargetConfig(
             ),
         ]
     ),
-    classes=ClassesConfig(
+    classes=DEFAULT_CLASSES_CONFIG,
-        classes=[
-            TargetClass(
-                tags=[TagInfo(value="Myotis mystacinus")],
-                name="myomys",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Myotis alcathoe")],
-                name="myoalc",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Eptesicus serotinus")],
-                name="eptser",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Pipistrellus nathusii")],
-                name="pipnat",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Barbastellus barbastellus")],
-                name="barbar",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Myotis nattereri")],
-                name="myonat",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Myotis daubentonii")],
-                name="myodau",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Myotis brandtii")],
-                name="myobra",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Pipistrellus pipistrellus")],
-                name="pippip",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Myotis bechsteinii")],
-                name="myobec",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Pipistrellus pygmaeus")],
-                name="pippyg",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Rhinolophus hipposideros")],
-                name="rhihip",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Nyctalus leisleri")],
-                name="nyclei",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Rhinolophus ferrumequinum")],
-                name="rhifer",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Plecotus auritus")],
-                name="pleaur",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Nyctalus noctula")],
-                name="nycnoc",
-            ),
-            TargetClass(
-                tags=[TagInfo(value="Plecotus austriacus")],
-                name="pleaus",
-            ),
-        ],
-        generic_class=[TagInfo(value="Bat")],
-    ),
 )
 
 

batdetect2/train/train.py

@@ -38,6 +38,8 @@ def train(
     config: Optional[TrainingConfig] = None,
     callbacks: Optional[List[Callback]] = None,
     model_path: Optional[data.PathLike] = None,
+    train_workers: int = 0,
+    val_workers: int = 0,
     **trainer_kwargs,
 ) -> None:
     config = config or TrainingConfig()
@@ -85,6 +87,7 @@ def train(
         train_dataset,
         batch_size=config.batch_size,
         shuffle=True,
+        num_workers=train_workers,
     )
 
     val_dataloader = None
@@ -97,6 +100,7 @@ def train(
             val_dataset,
             batch_size=config.batch_size,
             shuffle=False,
+            num_workers=val_workers,
         )
 
     trainer.fit(