Refine training config

batdetect2/train/clips.py

@@ -11,7 +11,7 @@ DEFAULT_TRAIN_CLIP_DURATION = 0.513
 DEFAULT_MAX_EMPTY_CLIP = 0.1
 
 
-class ClipperConfig(BaseConfig):
+class ClipingConfig(BaseConfig):
     duration: float = DEFAULT_TRAIN_CLIP_DURATION
     random: bool = True
     max_empty: float = DEFAULT_MAX_EMPTY_CLIP
@@ -69,8 +69,8 @@ class Clipper(ClipperProtocol):
         )
 
 
-def build_clipper(config: Optional[ClipperConfig] = None) -> ClipperProtocol:
-    config = config or ClipperConfig()
+def build_clipper(config: Optional[ClipingConfig] = None) -> ClipperProtocol:
+    config = config or ClipingConfig()
     return Clipper(
         duration=config.duration,
         max_empty=config.max_empty,

batdetect2/train/config.py

@@ -4,6 +4,11 @@ from pydantic import Field
 from soundevent.data import PathLike
 
 from batdetect2.configs import BaseConfig, load_config
+from batdetect2.train.augmentations import (
+    DEFAULT_AUGMENTATION_CONFIG,
+    AugmentationsConfig,
+)
+from batdetect2.train.clips import ClipingConfig
 from batdetect2.train.losses import LossConfig
 
 __all__ = [
@@ -20,9 +25,17 @@ class OptimizerConfig(BaseConfig):
 
 class TrainingConfig(BaseConfig):
     batch_size: int = 32
+
     loss: LossConfig = Field(default_factory=LossConfig)
+
     optimizer: OptimizerConfig = Field(default_factory=OptimizerConfig)
 
+    augmentations: AugmentationsConfig = Field(
+        default_factory=lambda: DEFAULT_AUGMENTATION_CONFIG
+    )
+
+    cliping: ClipingConfig = Field(default_factory=ClipingConfig)
+
 
 def load_train_config(
     path: PathLike,

batdetect2/train/dataset.py

@@ -4,15 +4,10 @@ from typing import List, Optional, Sequence, Tuple
 import numpy as np
 import torch
 import xarray as xr
-from pydantic import Field
 from soundevent import data
 from torch.utils.data import Dataset
 
-from batdetect2.configs import BaseConfig
-from batdetect2.train.augmentations import (
-    Augmentation,
-    AugmentationsConfig,
-)
+from batdetect2.train.augmentations import Augmentation
 from batdetect2.train.types import ClipperProtocol, TrainExample
 
 __all__ = [
@@ -20,19 +15,6 @@ __all__ = [
 ]
 
 
-class SubclipConfig(BaseConfig):
-    duration: Optional[float] = None
-    width: int = 512
-    random: bool = False
-
-
-class DatasetConfig(BaseConfig):
-    subclip: SubclipConfig = Field(default_factory=SubclipConfig)
-    augmentation: AugmentationsConfig = Field(
-        default_factory=AugmentationsConfig
-    )
-
-
 class LabeledDataset(Dataset):
     def __init__(
         self,