Silence expected inference-only checkpoint load diagnostics

inference.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import argparse
+import logging
 import re
 import sys
 from pathlib import Path
@@ -83,7 +84,13 @@ class InflectTTS:
             self.hps.train.segment_size // self.hps.data.hop_length,
             **self.hps.model,
         ).to(self.device).eval()
-        utils.load_checkpoint(str(self.root / "model.pth"), self.model, None)
+        root_logger = logging.getLogger()
+        previous_level = root_logger.level
+        try:
+            root_logger.setLevel(logging.WARNING)
+            utils.load_checkpoint(str(self.root / "model.pth"), self.model, None)
+        finally:
+            root_logger.setLevel(previous_level)
         self.sample_rate = int(self.hps.data.sampling_rate)
 
     def _tokens(self, text: str) -> tuple[torch.Tensor, torch.Tensor]:

release_manifest.json

@@ -27,8 +27,8 @@
     },
     {
       "path": "inference.py",
-      "bytes": 6019,
-      "sha256": "91943b432ab3fd3568658eff8f51301409f26f147041e46915db0b350e0efd98"
+      "bytes": 6252,
+      "sha256": "11f45c95cd1eb9eaa1814b464fcf290a8bc1a93158743fa2ac01dc4b0181c0a1"
     },
     {
       "path": "inflect_nano_v2_frontend.py",