Method run

tests/benchmark/benchmark_store.py:151–167

(
        self, train_dataset: Optional[agl.Dataset[Any]] = None, val_dataset: Optional[agl.Dataset[Any]] = None
    )

        self.concurrency = concurrency

    async def run(
        self, train_dataset: Optional[agl.Dataset[Any]] = None, val_dataset: Optional[agl.Dataset[Any]] = None
    ):
        if self.mode == "batch":
            assert self.batch_size is not None
            await self.algorithm_batch(self.total_tasks, self.batch_size)
        elif self.mode == "batch_partial":
            assert self.batch_size is not None
            assert self.remaining_tasks is not None
            await self.algorithm_batch_with_completion_threshold(
                self.total_tasks, self.batch_size, self.remaining_tasks
            )
        elif self.mode == "single":
            assert self.concurrency is not None
            await self.algorithm_batch_single(self.total_tasks, self.concurrency)
        else:
            raise ValueError(f"Invalid mode: {self.mode}")

    async def algorithm_batch(self, total_tasks: int, batch_size: int):
        """