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