code: def _generate_large_pipeline_steps(input_data: object):
      steps = []
      for i in range(2000):
          steps.append(
              CustomStep(name=f"MyStep{i}", input_data=input_data)
          )
      return steps
  
imports: from __future__ import absolute_import
  import copy
  import json
  import pytest
  from mock import Mock, call, patch
  from sagemaker import s3
  from sagemaker.remote_function.job import _JobSettings
  from sagemaker.session_settings import SessionSettings
  from sagemaker.workflow.condition_step import ConditionStep
  from sagemaker.workflow.conditions import ConditionEquals
  from sagemaker.workflow.execution_variables import ExecutionVariables
  from sagemaker.workflow.function_step import DelayedReturn, step
  from sagemaker.workflow.functions import JsonGet, Join
  from sagemaker.workflow.parameters import ParameterString
  from sagemaker.workflow.pipeline import Pipeline, PipelineGraph, _replace_pipeline_name_in_json_get_s3_uri
  from sagemaker.workflow.pipeline_context import _PipelineConfig
  from sagemaker.workflow.pipeline_definition_config import PipelineDefinitionConfig
  from sagemaker.workflow.pipeline_experiment_config import PipelineExperimentConfig, PipelineExperimentConfigProperties
  from sagemaker.workflow.step_collections import StepCollection
  from tests.unit.sagemaker.workflow.helpers import ordered, CustomStep, CustomFunctionStep
  from sagemaker.local.local_session import LocalSession
  from botocore.exceptions import ClientError
  from sagemaker.workflow.selective_execution_config import SelectiveExecutionConfig
label_desc: Use image node_id 27 for calling a global function with example usage: _generate_large_pipeline_steps(input_data) and returns: steps