code: def _merge_tp_slice_files(
      args, ds_checkpoint, slice_shapes, temp_dir
  ):
      work_chunks = list(
          _get_chunks(
              list(slice_shapes.items()), args.num_merge_workers
          )
      )
      # pprint(work_chunks)
      zero_output_folder = os.path.join(args.output_folder, "zero")
      do_work = partial(
          merge_tp_slices,
          ds_checkpoint,
          zero_output_folder,
          temp_dir,
          ds_checkpoint.tp_degree,
      )
      unmatched_patterns_lists = _do_parallel_work(
          do_work, work_chunks, args.num_merge_workers
      )
  
      # verify that all patterns were used
      # if a pattern was not used by any of the workers, then it was not used at all -> assert/alert
      sets = [set(lst) for lst in unmatched_patterns_lists]
      unmatched_patterns = list(set.intersection(*sets))
      if args.strict:
          assert (
              not unmatched_patterns
          ), f"Unused patterns={unmatched_patterns} while merging tp slices"
      elif unmatched_patterns:
          print(
              f"Warning: Unused patterns={unmatched_patterns} while merging tp slices"
          )
  
imports: from functools import partial
  import argparse
  import glob
  import itertools
  import multiprocessing
  import os
  import re
  import shutil
  import torch
  import tqdm
  from deepspeed.checkpoint import DeepSpeedCheckpoint
  from deepspeed.checkpoint import OPTIMIZER_STATE_DICT, BASE_OPTIMIZER_STATE, SINGLE_PARTITION_OF_FP32_GROUPS, PARAM_SLICE_MAPPINGS, PARAM_SHAPES, PARAM, CAT_DIM, PARAM_N_SUB_PARAMS, VOCAB_TENSOR, UNIVERSAL_CHECKPOINT_INFO, VOCABULARY_PARAMETER_PATTERNS, PIPELINE_REPLICATED_PARAMETER_PATTERNS, TP_REPLICATED_PARAMETER_PATTERNS, PARAMETER_TO_AVERAGE_PATTERNS, PARAMETER_WITH_ROW_PARALLELISM_PATTERNS, PARAMETER_WITH_2_SUB_PARAMS_CAT_DIM_0
label_desc: Use image node_id 11 for calling a global function with example usage: _merge_tp_slice_files(args, ds_checkpoint, slice_shapes, temp_dir) without return types