Use Kaggle Models URL for downloading Perch. This allows loading Vers…

…ion 8. Also adds a convenience method for loading the model from just a version number.

PiperOrigin-RevId: 622223336

chirp/inference/models.py

@@ -32,7 +32,11 @@
 import tensorflow.compat.v1 as tf1
 import tensorflow_hub as hub
 
-PERCH_TF_HUB_URL = 'https://tfhub.dev/google/bird-vocalization-classifier'
+PERCH_TF_HUB_URL = (
+    'https://www.kaggle.com/models/google/'
+    'bird-vocalization-classifier/frameworks/TensorFlow2/'
+    'variations/bird-vocalization-classifier/versions'
+)
 
 
 def model_class_map() -> dict[str, Any]:
@@ -287,6 +291,10 @@ def from_tfhub(cls, config: config_dict.ConfigDict) -> 'TaxonomyModelTF':
       raise ValueError(
           'Exactly one of tfhub_version and model_path should be set.'
       )
+    if config.tfhub_version in (5, 6, 7):
+      # Due to SNAFUs uploading the new model version to KaggleModels,
+      # some version numbers were skipped.
+      raise ValueError('TFHub version 5, 6, and 7 do not exist.')
 
     model_url = f'{PERCH_TF_HUB_URL}/{config.tfhub_version}'
     # This model behaves exactly like the usual saved_model.
@@ -303,6 +311,20 @@ def from_tfhub(cls, config: config_dict.ConfigDict) -> 'TaxonomyModelTF':
         model=model, class_list=class_lists, batchable=batchable, **config
     )
 
+  @classmethod
+  def load_version(
+      cls, tfhub_version: int, hop_size_s: float = 5.0
+  ) -> 'TaxonomyModelTF':
+    cfg = config_dict.ConfigDict({
+        'model_path': '',
+        'sample_rate': 32000,
+        'window_size_s': 5.0,
+        'hop_size_s': hop_size_s,
+        'target_peak': 0.25,
+        'tfhub_version': tfhub_version,
+    })
+    return cls.from_tfhub(cfg)
+
   @classmethod
   def from_config(cls, config: config_dict.ConfigDict) -> 'TaxonomyModelTF':
     logging.info('Loading taxonomy model...')