feat: handling wrong model type

hfgl/model.py

@@ -11,6 +11,7 @@
     dynamic_range_compression_torch,
     get_spectral_transform,
 )
+from loguru import logger
 from torch.nn import AvgPool1d, Conv1d, Conv2d, ConvTranspose1d
 from torch.nn.utils import spectral_norm
 from torch.nn.utils.parametrizations import weight_norm
@@ -454,8 +455,21 @@ class HiFiGANGenerator(pl.LightningModule):
 
     def __init__(self, config: dict | VocoderConfig):
         super().__init__()
+
         if not isinstance(config, VocoderConfig):
-            config = VocoderConfig(**config)
+            from pydantic import ValidationError
+
+            try:
+                config = VocoderConfig(**config)
+            except ValidationError:
+                # TODO: should we print the following message only if there are more than X validation errors?
+                # e.error_count() > X
+                error = TypeError(
+                    "Unable to load config.  Are you certain it is a VocoderConfig config?"
+                )
+                logger.error(error.args)
+                raise error
+
         self.config = config
         self.generator = Generator(self.config)