class_docstr: Save the data in a dictionary format cache, and write to a CSV file finally.
  Typically, the data can be classification predictions, call `save` for single data
  or call `save_batch` to save a batch of data together, and call `finalize` to write
  the cached data into CSV file. If no metadata provided, use index from 0 to save data.
  Note that this saver can't support multi-processing because it reads / writes single
  CSV file and can't guarantee the data order in multi-processing situation.
docstr: Save data into the cache dictionary. The metadata should have the following key:
      - ``'filename_or_obj'`` -- save the data corresponding to file name or object.
  If meta_data is None, use the default index from 0 to save data instead.
  
  Args:
      data: target data content that save into cache.
      meta_data: the metadata information corresponding to the data.
docstr_tok: ["Save","data","into","the","cache","dictionary",".","The","metadata","should","have","the","following","key",":","-","``","'filename_or_obj","'","``","--","save","the","data","corresponding","to","file","name","or","object",".","If","meta_data","is","None",",","use","the","default","index","from","0","to","save","data","instead",".","Args",":","data",":","target","data","content","that","save","into","cache",".","meta_data",":","the","metadata","information","corresponding","to","the","data","."]
code: def save(
      self,
      data: torch.Tensor | np.ndarray,
      meta_data: dict | None = None,
  ) -> None:
      """Save data into the cache dictionary. The metadata should have the following key:
          - ``'filename_or_obj'`` -- save the data corresponding to file name or object.
      If meta_data is None, use the default index from 0 to save data instead.
  
      Args:
          data: target data content that save into cache.
          meta_data: the metadata information corresponding to the data.
  
      """
      save_key = (
          meta_data[Key.FILENAME_OR_OBJ]
          if meta_data
          else str(self._data_index)
      )
      self._data_index += 1
      if isinstance(data, torch.Tensor):
          data = data.detach().cpu().numpy()
      self._cache_dict[save_key] = np.asarray(data, dtype=float)
  
file_path: MONAI/monai/data/csv_saver.py
imports: from __future__ import annotations
  import os
  import warnings
  from collections import OrderedDict
  from pathlib import Path
  import numpy
  import torch
  from monai.config.type_definitions import PathLike
  from monai.utils import ImageMetaKey
label_desc: Use image node_id 3 for calling the CSVSaver obj's underlying member method code with example usage: obj.save(data, meta_data) without return types