Function adapt_configs

benchmark_v2/framework/benchmark_config.py:217–252

(
    configs: list[BenchmarkConfig],
    warmup_iterations: int | list[int] = 5,
    measurement_iterations: int | list[int] = 20,
    batch_size: int | list[int] = 1,
    sequence_length: int | list[int] = 128,
    num_tokens_to_generate: int | list[int] = 128,
    gpu_monitoring: bool | list[bool] = True,
)

def adapt_configs(
    configs: list[BenchmarkConfig],
    warmup_iterations: int | list[int] = 5,
    measurement_iterations: int | list[int] = 20,
    batch_size: int | list[int] = 1,
    sequence_length: int | list[int] = 128,
    num_tokens_to_generate: int | list[int] = 128,
    gpu_monitoring: bool | list[bool] = True,
) -> list[BenchmarkConfig]:
    parameters = (
        x if isinstance(x, list) else [x]
        for x in [
            warmup_iterations,
            measurement_iterations,
            batch_size,
            sequence_length,
            num_tokens_to_generate,
            gpu_monitoring,
        ]
    )
    iterator = itertools.product(*parameters)

    adapted_configs = []
    for warmup_iters, measurement_iters, bs, seqlen, ntok, monitor in iterator:
        for config in configs:
            config = config.to_dict()
            config["warmup_iterations"] = warmup_iters
            config["measurement_iterations"] = measurement_iters
            config["batch_size"] = bs
            config["sequence_length"] = seqlen
            config["num_tokens_to_generate"] = ntok
            config["gpu_monitoring"] = monitor
            # Remove the old name so it gets re-inferred with the updated values
            config.pop("name", None)
            adapted_configs.append(BenchmarkConfig.from_dict(config))
    return adapted_configs


def get_config_by_level(level: int) -> list[BenchmarkConfig]: