class_docstr: A MapOperator implementation that executes tasks on a task pool.
code: def current_resource_usage(self) -> ExecutionResources:
      num_active_workers = self.num_active_tasks()
      return ExecutionResources(
          cpu=self._ray_remote_args.get("num_cpus", 0)
          * num_active_workers,
          gpu=self._ray_remote_args.get("num_gpus", 0)
          * num_active_workers,
          object_store_memory=self.metrics.obj_store_mem_cur,
      )
  
file_path: ray/python/ray/data/_internal/execution/operators/task_pool_map_operator.py
imports: from typing import Any, Dict, Optional
  import ray
  from ray.data._internal.execution.interfaces import ExecutionResources, PhysicalOperator, RefBundle, TaskContext
  from ray.data._internal.execution.operators.map_operator import MapOperator, _map_task
  from ray.data._internal.execution.operators.map_transformer import MapTransformer
  from ray.data._internal.remote_fn import cached_remote_fn
  from ray.data.context import DataContext
label_desc: Use image node_id 6 for calling the TaskPoolMapOperator obj's underlying member method code with example usage: obj.current_resource_usage() and returns: ExecutionResources