Update landmarkdiff/benchmark.py to v0.3.2

landmarkdiff/benchmark.py

@@ -63,19 +63,17 @@ class InferenceBenchmark:
         if throughput_fps == 0.0 and latency_ms > 0:
             throughput_fps = 1000.0 / latency_ms * batch_size
 
-        self.results.append(
-            BenchmarkResult(
-                config_name=config_name,
-                latency_ms=latency_ms,
-                throughput_fps=throughput_fps,
-                vram_gb=vram_gb,
-                batch_size=batch_size,
-                resolution=resolution,
-                num_inference_steps=num_inference_steps,
-                device=device,
-                metadata=metadata,
-            )
-        )
+        self.results.append(BenchmarkResult(
+            config_name=config_name,
+            latency_ms=latency_ms,
+            throughput_fps=throughput_fps,
+            vram_gb=vram_gb,
+            batch_size=batch_size,
+            resolution=resolution,
+            num_inference_steps=num_inference_steps,
+            device=device,
+            metadata=metadata,
+        ))
 
     def mean_latency(self, config_name: str | None = None) -> float:
         """Mean latency in ms, optionally filtered by config."""
@@ -89,8 +87,9 @@ class InferenceBenchmark:
         results = self._filter(config_name)
         if not results:
             return float("nan")
+        import math
         sorted_latencies = sorted(r.latency_ms for r in results)
-        idx = max(0, int(len(sorted_latencies) * 0.99) - 1)
+        idx = min(len(sorted_latencies) - 1, math.ceil(len(sorted_latencies) * 0.99) - 1)
         return sorted_latencies[idx]
 
     def mean_throughput(self, config_name: str | None = None) -> float:
@@ -126,10 +125,7 @@ class InferenceBenchmark:
         if not configs:
             return "No benchmark results."
 
-        header = (
-            f"{'Config':>20s} | {'Mean(ms)':>10s} | {'P99(ms)':>10s}"
-            f" | {'FPS':>8s} | {'VRAM(GB)':>8s} | {'N':>4s}"
-        )
+        header = f"{'Config':>20s} | {'Mean(ms)':>10s} | {'P99(ms)':>10s} | {'FPS':>8s} | {'VRAM(GB)':>8s} | {'N':>4s}"
         lines = [
             f"Inference Benchmark: {self.model_name}",
             header,