code: def _construct_other_pipelines(
      main_pipeline: PassPipeline, convert_from: Text, convert_to: Text
  ) -> Tuple[PassPipeline, PassPipeline]:
      """
      Construct other pipelines based on the main pipeline. It includes:
      - The frontend pipeline which will run in the frontend converter
      - The backend pipeline which will run in the backend converter
      As the main pipeline could have passes which also exists in the frontend/backend passes, we
      need to make sure the pass options are set properly in all pipelines.
      For example, if users set options to skip some vars in `const_elimination` pass, we want to make
      sure those vars are skipped not only in main_pipeline, but also in other pipelines wherever the
      `const_elimination` pass runs.
  
      TODO: rdar://106046237 ([Infra] Expose Backend and Frontend Pipeline to External Users)
      Currently users only control the passes in the main pipeline by passing `pass_pipeline` param.
      There are two reasons why we don't expose the frontend/backend pipelines at the current stage:
      - The frontend and backend specific passes need to be well documented.
      - The interface need more carefully design, as we don't want to provide too many params such as
        ct.convert(..., frontend_pipeline=xxx, backend_pipelien=xxx, main_pipeline=xxx) to overwhelm
        users.
      """
      # Set the main pipeline options specified by the user in frontend/backend pipeline.
      frontend_pipeline = PassPipeline.get_pipeline(
          f"frontend_{convert_from.lower()}"
      )
      frontend_pipeline.set_options_by_another_pipeline(main_pipeline)
      backend_pipeline = PassPipeline.get_pipeline(
          f"backend_{convert_to.lower()}"
      )
      backend_pipeline.set_options_by_another_pipeline(main_pipeline)
  
      # If a pass is skipped in the main pipeline, we also skip it in the frontend/backend pipeline.
      default_main_pipeline = PassPipeline.get_pipeline("default")
      passes_skipped_in_main = set(default_main_pipeline.passes) - set(
          main_pipeline.passes
      )
      frontend_pipeline.remove_passes(passes_skipped_in_main)
      backend_pipeline.remove_passes(passes_skipped_in_main)
  
      return frontend_pipeline, backend_pipeline
  
imports: import tempfile
  import warnings
  from typing import Optional, Text, Tuple
  from coremltools.converters._profile_utils import _profile
  from coremltools.converters.mil import Program
  from coremltools.converters.mil.mil import Builder
  from coremltools.converters.mil.mil.types.symbolic import k_num_internal_syms, k_used_symbols
  from coremltools.models import MLModel
  from coremltools.models.model import _create_mlpackage
  from .None import ImageType, InputType
  from .mil.passes.pass_pipeline import PassPipeline, PassPipelineManager
label_desc: Use image node_id 5 for calling a global function with example usage: _construct_other_pipelines(main_pipeline, convert_from, convert_to) and returns: frontend_pipeline,  backend_pipeline