fix ruff errors and formatting

This commit is contained in:
yichuan520030910320
2025-07-27 02:22:54 -07:00
parent 383c6d8d7e
commit af1790395a
35 changed files with 166 additions and 107 deletions

View File

@@ -170,7 +170,11 @@ class Benchmark:
def _create_random_batch(self, batch_size: int) -> torch.Tensor:
return torch.randint(
0, 1000, (batch_size, self.config.seq_length), device=self.device, dtype=torch.long
0,
1000,
(batch_size, self.config.seq_length),
device=self.device,
dtype=torch.long,
)
def _run_inference(self, input_ids: torch.Tensor) -> float:
@@ -256,7 +260,11 @@ def run_mlx_benchmark():
"""Run MLX-specific benchmark"""
if not MLX_AVAILABLE:
print("MLX not available, skipping MLX benchmark")
return {"max_throughput": 0.0, "avg_throughput": 0.0, "error": "MLX not available"}
return {
"max_throughput": 0.0,
"avg_throughput": 0.0,
"error": "MLX not available",
}
config = BenchmarkConfig(model_path="mlx-community/all-MiniLM-L6-v2-4bit", use_mlx=True)
@@ -265,7 +273,11 @@ def run_mlx_benchmark():
results = benchmark.run()
if not results:
return {"max_throughput": 0.0, "avg_throughput": 0.0, "error": "No valid results"}
return {
"max_throughput": 0.0,
"avg_throughput": 0.0,
"error": "No valid results",
}
max_throughput = max(results[batch_size]["throughput"] for batch_size in results)
avg_throughput = np.mean([results[batch_size]["throughput"] for batch_size in results])