Release NVIDIA WakeWord Trainer v20

VERSION

@@ -1 +1 @@
-19
+20

WHATS_NEW.md

@@ -1,3 +1,3 @@
-- Fixed first-run Parakeet ONNX setup failing when its empty model directory was mistaken for a complete offline model.
-- Parakeet now downloads or resumes the required INT8 snapshot before loading through ONNX ASR.
-- Complete local snapshots are reused without Hub access, preserving offline startup after the initial download.
+- Fixed the v19 container startup failure caused by malformed indentation in the Parakeet ONNX loader.
+- Preserved automatic download, resume, and offline reuse of the required Parakeet INT8 model snapshot.
+- Revalidated both CUDA and CPU Parakeet provider paths with the complete trainer test suite.

trainer_server.py

@@ -957,11 +957,11 @@ def _load_parakeet_onnx_model():
         cached = PARAKEET_ONNX_MODEL_CACHE.get(cache_key)
         if cached is not None:
             return cached
-    suffix = (
-        f".{DEFAULT_PARAKEET_ONNX_QUANTIZATION}"
-        if DEFAULT_PARAKEET_ONNX_QUANTIZATION
-        else ""
-    )
+        suffix = (
+            f".{DEFAULT_PARAKEET_ONNX_QUANTIZATION}"
+            if DEFAULT_PARAKEET_ONNX_QUANTIZATION
+            else ""
+        )
         model_patterns = [
             "config.json",
             "vocab.txt",
@@ -988,10 +988,10 @@ def _load_parakeet_onnx_model():
         os.environ["HUGGINGFACE_HUB_CACHE"] = str(AUTO_TRAIN_MODEL_DIR / "hub")
         try:
             snapshot_root = AUTO_TRAIN_MODEL_DIR
-    if not all(
-        (AUTO_TRAIN_MODEL_DIR / filename).is_file()
-        for filename in required_model_files
-    ):
+            if not all(
+                (AUTO_TRAIN_MODEL_DIR / filename).is_file()
+                for filename in required_model_files
+            ):
                 from huggingface_hub import snapshot_download
 
                 snapshot_root = Path(