Create embedding models from configurations with a from_config clas…

…smethod instead of abusing the dataclass `post_init` function.

PiperOrigin-RevId: 557267692

chirp/inference/embed_lib.py

@@ -139,9 +139,8 @@ def __init__(
 
   def setup(self):
     if self.embedding_model is None:
-      self.embedding_model = models.model_class_map()[self.model_key](
-          **self.model_config
-      )
+      model_class = models.model_class_map()[self.model_key]
+      self.embedding_model = model_class.from_config(**self.model_config)
     if hasattr(self, 'model_key'):
       del self.model_key
     if hasattr(self, 'model_config'):

chirp/inference/interface.py

@@ -20,6 +20,7 @@
 
 from chirp.taxonomy import namespace
 import librosa
+from ml_collections import config_dict
 import numpy as np
 
 LogitType = Dict[str, np.ndarray]
@@ -111,6 +112,13 @@ class EmbeddingModel:
 
   sample_rate: int
 
+  @classmethod
+  def from_config(
+      cls, model_config: config_dict.ConfigDict
+  ) -> 'EmbeddingModel':
+    """Load the model from a configuration dict."""
+    raise NotImplementedError
+
   def embed(self, audio_array: np.ndarray) -> InferenceOutputs:
     """Create InferenceOutputs from an audio array.