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app.py

@@ -45,6 +45,8 @@ def _encode_decode(audio_path: str, levels: tuple) -> dict:
     """Reconstruct `audio_path` once per weight-quantization level, scoring each result."""
     ref, sr = core.load_audio(audio_path, SAMPLE_RATE, MAX_SECONDS)
     sig = torch.from_numpy(ref).unsqueeze(0).cuda()
+    with torch.inference_mode():  # untimed warmup so the first row's RTF isn't inflated
+        codec.sig_to_sig(sig)
     rows, reconstructed = [], {}
     for level in levels:
         codec.load_state_dict(BASE_STATE if level == "fp32" else core.quantize_state(BASE_STATE, level))
@@ -60,6 +62,10 @@ def _encode_decode(audio_path: str, levels: tuple) -> dict:
     return {"input": (sr, ref), "rows": rows, "audio": reconstructed}
 
 
+def _table(rows: list[dict]) -> list[list]:
+    return [[row[header] for header in HEADERS] for row in rows]
+
+
 _CACHE: dict[str, dict] = {}
 
 
@@ -99,14 +105,14 @@ def playground(audio_path: str, level: str):
     return (
         rec,
         core.spectrogram_figure(result["input"][1], rec[1], SAMPLE_RATE, level),
-        [result["rows"][0]],
+        _table(result["rows"]),
     )
 
 
 def benchmark(audio_path: str):
     """Score every quantization level on one input: metrics table plus summary chart."""
     result = run(audio_path, QUANT_LEVELS)
-    return result["rows"], core.metrics_figure(result["rows"])
+    return _table(result["rows"]), core.metrics_figure(result["rows"])
 
 
 HEADER = f"""# ⚡ FocalCodec 12.5 Hz — weight quantization lab
@@ -123,7 +129,7 @@ The bitrate never changes — **{core.BITRATE_KBPS:g} kbps** (12.5 tokens/s × 1
 FOOTER = """Audio examples from the [FocalCodec repository](https://github.com/lucadellalib/focalcodec)
 (LibriSpeech, VoiceBank, MagicData). Model and method by Luca Della Libera et al., Apache-2.0."""
 
-with gr.Blocks(title="FocalCodec quantization lab", theme=gr.themes.Soft()) as demo:
+with gr.Blocks(title="FocalCodec quantization lab") as demo:
     gr.Markdown(HEADER)
 
     with gr.Tab("Compare"):
@@ -190,4 +196,4 @@ with gr.Blocks(title="FocalCodec quantization lab", theme=gr.themes.Soft()) as d
 
     gr.Markdown(FOOTER)
 
-demo.launch(mcp_server=True)
+demo.launch(mcp_server=True, theme=gr.themes.Soft())