code: def test_map_estimated_blocks_split():
      # Test read output splitting
      def yield_five(
          block_iter: Iterable[Block], ctx
      ) -> Iterable[Block]:
          for i in range(5):
              yield pd.DataFrame({"id": [i]})
  
      min_rows_per_bundle = 10
      input_op = InputDataBuffer(
          make_ref_bundles([[i] for i in range(100)])
      )
      op = MapOperator.create(
          create_map_transformer_from_block_fn(yield_five),
          input_op=input_op,
          name="TestEstimatedNumBlocksSplit",
          min_rows_per_bundle=min_rows_per_bundle,
      )
      op.set_additional_split_factor(2)
  
      op.start(ExecutionOptions())
      while input_op.has_next():
          op.add_input(input_op.get_next(), 0)
          if op.metrics.num_inputs_received % min_rows_per_bundle == 0:
              # enough inputs for a task bundle
              run_op_tasks_sync(op)
              assert op._estimated_output_blocks == 100
  
      op.all_inputs_done()
      # Each output block is split in 2, so the number of blocks double.
      assert op._estimated_output_blocks == 100
  
imports: import collections
  import random
  import time
  from typing import Any, Iterable, List
  from unittest.mock import MagicMock
  import numpy
  import pandas
  import pytest
  import ray
  from ray._private.test_utils import wait_for_condition
  from ray.data._internal.compute import ActorPoolStrategy, TaskPoolStrategy
  from ray.data._internal.execution.interfaces import ExecutionOptions, PhysicalOperator, RefBundle
  from ray.data._internal.execution.operators.actor_pool_map_operator import ActorPoolMapOperator
  from ray.data._internal.execution.operators.base_physical_operator import AllToAllOperator
  from ray.data._internal.execution.operators.input_data_buffer import InputDataBuffer
  from ray.data._internal.execution.operators.limit_operator import LimitOperator
  from ray.data._internal.execution.operators.map_operator import MapOperator, _BlockRefBundler
  from ray.data._internal.execution.operators.map_transformer import create_map_transformer_from_block_fn
  from ray.data._internal.execution.operators.output_splitter import OutputSplitter
  from ray.data._internal.execution.operators.task_pool_map_operator import TaskPoolMapOperator
  from ray.data._internal.execution.operators.union_operator import UnionOperator
  from ray.data._internal.execution.util import make_ref_bundles
  from ray.data.block import Block
  from ray.data.context import DataContext
  from ray.data.tests.util import run_one_op_task, run_op_tasks_sync
  from ray.tests.conftest import *
label_desc: Use image node_id 27 for calling a global function with example usage: test_map_estimated_blocks_split() without return types