Make HF-dependent Tests Skip Cleanly When Model Download is Unavailable

tada/modules/aligner_test.py

@@ -4,7 +4,7 @@
 import torch
 import torchaudio
 
-from ..utils.test_utils import get_sample_dir
+from ..utils.test_utils import get_sample_dir, skip_if_hub_model_unavailable
 from .aligner import Aligner
 
 
@@ -17,6 +17,7 @@
 )
 def test_aligner(model_name_or_path: str):
     device = "cpu"
+    skip_if_hub_model_unavailable(model_name_or_path, subfolder="aligner")
     aligner = Aligner.from_pretrained(model_name_or_path, subfolder="aligner").to(device)
     audio, sample_rate = torchaudio.load(os.path.join(get_sample_dir(), "ljspeech.wav"))
     audio = audio.to(device)

tada/modules/decoder_test.py

@@ -4,7 +4,7 @@
 import torch
 import torchaudio
 
-from ..utils.test_utils import get_sample_dir
+from ..utils.test_utils import get_sample_dir, skip_if_hub_model_unavailable
 from .decoder import Decoder, DecoderConfig
 from .encoder import Encoder, EncoderConfig
 
@@ -23,6 +23,8 @@ def test_decoder(model_name_or_path: str | None):
         encoder = Encoder(EncoderConfig())
         decoder = Decoder(DecoderConfig())
     else:
+        skip_if_hub_model_unavailable(model_name_or_path, subfolder="encoder")
+        skip_if_hub_model_unavailable(model_name_or_path, subfolder="decoder")
         encoder = Encoder.from_pretrained(model_name_or_path, subfolder="encoder").to(device)
         decoder = Decoder.from_pretrained(model_name_or_path, subfolder="decoder").to(device)
     audio, sample_rate = torchaudio.load(os.path.join(get_sample_dir(), "ljspeech.wav"))

tada/modules/encoder_test.py

@@ -3,11 +3,12 @@
 import torch
 import torchaudio
 
-from ..utils.test_utils import get_sample_dir
+from ..utils.test_utils import get_sample_dir, skip_if_hub_model_unavailable
 from .encoder import Encoder
 
 
 def test_encoder(model_name_or_path: str = "HumeAI/tada-codec", device: str = "cuda"):
+    skip_if_hub_model_unavailable(model_name_or_path, subfolder="encoder")
     encoder = Encoder.from_pretrained(model_name_or_path, subfolder="encoder").to(device)
     audio, sample_rate = torchaudio.load(os.path.join(get_sample_dir(), "ljspeech.wav"))
     audio = audio.to(device)
@@ -22,6 +23,7 @@ def test_token_values_are_local(model_name_or_path: str = "HumeAI/tada-codec", d
     """Test that token values are local.
     A change in one audio sample should only affect the immediately preceding and following token values.
     """
+    skip_if_hub_model_unavailable(model_name_or_path, subfolder="encoder")
     encoder = Encoder.from_pretrained(model_name_or_path, subfolder="encoder").to(device)
     encoder.eval()
     torch.manual_seed(42)

tada/modules/tada_test.py

@@ -4,7 +4,7 @@
 import torch
 import torchaudio
 
-from ..utils.test_utils import get_sample_dir
+from ..utils.test_utils import get_sample_dir, skip_if_hub_model_unavailable
 from .encoder import Encoder, EncoderConfig
 from .tada import TadaConfig, TadaForCausalLM
 
@@ -26,6 +26,8 @@ def test_tada_for_causal_lm(model_name_or_path: str | None):
         )
         model = TadaForCausalLM(config)
     else:
+        skip_if_hub_model_unavailable(model_name_or_path, subfolder="encoder")
+        skip_if_hub_model_unavailable(model_name_or_path, subfolder="llm")
         encoder = Encoder.from_pretrained("HumeAI/TADA", subfolder="encoder").to(device)
         model = TadaForCausalLM.from_pretrained(model_name_or_path, subfolder="llm").to(device)
     encoder.to(device).eval()

tada/utils/test_utils.py

@@ -1,6 +1,8 @@
 import os
 
+import pytest
 import torch
+from huggingface_hub import hf_hub_download
 
 
 def get_sample_dir() -> str:
@@ -18,3 +20,11 @@ def get_default_device() -> torch.device:
         return torch.device("mps")
     else:
         return torch.device("cpu")
+
+
+def skip_if_hub_model_unavailable(repo_id: str, subfolder: str | None = None, filename: str = "config.json") -> None:
+    """Skip integration tests when model artifacts cannot be fetched from Hugging Face Hub."""
+    try:
+        hf_hub_download(repo_id=repo_id, filename=filename, subfolder=subfolder)
+    except Exception as exc:  # pragma: no cover - best effort network check
+        pytest.skip(f"Hugging Face model '{repo_id}' is unavailable in this environment: {exc}")