Attention Backend Benchmark Tool

from typing import Optional, List, Dict
import time

class AttentionBackendBenchmark:
    """
    Benchmarks LLM inference performance across different attention backends.
    """

    def __init__(self, model: str):
        """
        Initialize the benchmark tool with a model.

        Args:
            model: Model name or path to use for benchmarking
        """
        pass

    def run_with_backend(
        self,
        prompt: str,
        attention_backend: Optional[str] = None,
        max_tokens: int = 100,
        temperature: float = 0.0
    ) -> Dict[str, any]:
        """
        Run inference with a specific attention backend and return results with timing.

        Args:
            prompt: Input prompt text
            attention_backend: Attention backend name (e.g., "FLASH_ATTN", "FLASHINFER", "XFORMERS")
            max_tokens: Maximum tokens to generate
            temperature: Sampling temperature

        Returns:
            Dictionary with keys: 'output' (generated text), 'time' (generation time in seconds),
            'backend' (backend used)
        """
        pass

    def compare_backends(
        self,
        prompt: str,
        backends: List[str],
        max_tokens: int = 100
    ) -> List[Dict[str, any]]:
        """
        Compare multiple backends on the same prompt.

        Args:
            prompt: Input prompt text
            backends: List of backend names to compare
            max_tokens: Maximum tokens to generate

        Returns:
            List of result dictionaries, one per backend
        """
        pass