class_docstr: Dataset class for NCF
class_docstr_tok: ["Dataset","class","for","NCF"]
code: def _release_shuffle_buffer(
      self, shuffle_buffer, batch_size, yield_id, write_to=None
  ):
      prepare_batch = (
          self._prepare_batch_with_id
          if yield_id
          else self._prepare_batch_without_id
      )
      shuffle_buffer_df = pd.concat(shuffle_buffer)
      shuffle_buffer_df = shuffle_buffer_df.sample(
          shuffle_buffer_df.shape[0]
      )  # shuffle the buffer
      for batch in self._split_into_batches(
          shuffle_buffer_df, batch_size
      ):
          if batch.shape[0] == batch_size:
              if write_to:
                  batch.to_csv(
                      write_to, mode="a", header=False, index=False
                  )
              yield prepare_batch(batch)
          else:
              return batch
  
imports: import os
  from collections import OrderedDict
  import random
  import numpy
  import pandas
  import csv
  import logging
  from tqdm import tqdm
  from recommenders.utils.constants import DEFAULT_ITEM_COL, DEFAULT_USER_COL, DEFAULT_RATING_COL
label_desc: Use image node_id 7 for calling the Dataset obj's underlying member method code with example usage: obj._release_shuffle_buffer(shuffle_buffer, batch_size, yield_id, write_to) and returns: batch