class_docstr: A MapOperator implementation that executes tasks on a task pool.
docstr: Create an TaskPoolMapOperator instance.
  
  Args:
      transform_fn: The function to apply to each ref bundle input.
      input_op: Operator generating input data for this op.
      name: The name of this operator.
      target_max_block_size: The target maximum number of bytes to
          include in an output block.
      min_rows_per_bundle: The number of rows to gather per batch passed to the
          transform_fn, or None to use the block size. Setting the batch size is
          important for the performance of GPU-accelerated transform functions.
          The actual rows passed may be less if the dataset is small.
      ray_remote_args: Customize the ray remote args for this op's tasks.
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code: def __init__(
      self,
      map_transformer: MapTransformer,
      input_op: PhysicalOperator,
      target_max_block_size: Optional[int],
      name: str = "TaskPoolMap",
      min_rows_per_bundle: Optional[int] = None,
      ray_remote_args: Optional[Dict[str, Any]] = None,
  ):
      """Create an TaskPoolMapOperator instance.
  
      Args:
          transform_fn: The function to apply to each ref bundle input.
          input_op: Operator generating input data for this op.
          name: The name of this operator.
          target_max_block_size: The target maximum number of bytes to
              include in an output block.
          min_rows_per_bundle: The number of rows to gather per batch passed to the
              transform_fn, or None to use the block size. Setting the batch size is
              important for the performance of GPU-accelerated transform functions.
              The actual rows passed may be less if the dataset is small.
          ray_remote_args: Customize the ray remote args for this op's tasks.
      """
      super().__init__(
          map_transformer,
          input_op,
          name,
          target_max_block_size,
          min_rows_per_bundle,
          ray_remote_args,
      )
  
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 1 to create a new TaskPoolMapOperator object from inherited base classes: MapOperator with example: obj = TaskPoolMapOperator(map_transformer, input_op, target_max_block_size, name, min_rows_per_bundle, ray_remote_args)