code: def _dumps_partitions(partitions, row_key_type):
      parts_type = partitions.dtype
      if not (
          isinstance(parts_type, hl.tarray)
          and isinstance(parts_type.element_type, hl.tinterval)
      ):
          raise ValueError(
              f"partitions type invalid: {parts_type} must be array of intervals"
          )
  
      point_type = parts_type.element_type.point_type
  
      f1, t1 = next(iter(row_key_type.items()))
      if point_type == t1:
          partitions = hl.map(
              lambda x: hl.interval(
                  start=hl.struct(**{f1: x.start}),
                  end=hl.struct(**{f1: x.end}),
                  includes_start=x.includes_start,
                  includes_end=x.includes_end,
              ),
              partitions,
          )
      else:
          if not isinstance(point_type, hl.tstruct):
              raise ValueError(
                  f"partitions has wrong type: {point_type} must be struct or type of first row key field"
              )
          if not point_type._is_prefix_of(row_key_type):
              raise ValueError(
                  f"partitions type invalid: {point_type} must be prefix of {row_key_type}"
              )
  
      s = json.dumps(
          partitions.dtype._convert_to_json(hl.eval(partitions))
      )
      return s, partitions.dtype
  
imports: import atexit
  import datetime
  import difflib
  import json
  import os
  import re
  import secrets
  import shutil
  import string
  import tempfile
  from collections import defaultdict, Counter
  from contextlib import contextmanager
  from io import StringIO
  from typing import Optional, Literal
  from urllib.parse import urlparse
  import hail
  import hail
  from hail.typecheck import enumeration, typecheck, nullable
  from hail.utils.java import Env, error
label_desc: Use image node_id 34 for calling a global function with example usage: _dumps_partitions(partitions, row_key_type) and returns: s,  partitions