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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def visualize_embeddings(summary_writer, config):
 """Stores a config file used by the embedding projector. Args: summary_writer: The summary writer used for writing events. config: `tf.contrib.tensorboard.plugins.projector.ProjectorConfig` proto that holds the configuration for the projector such as paths to checkpoint files and metadata files for the embeddings. If `config.model_checkpoint_path` is none, it defaults to the `logdir` used by the summary_writer. Raises: ValueError: If the summary writer does not have a `logdir`. """

  logdir = summary_writer.get_logdir()

  # Sanity checks.
  if logdir is None:
    raise ValueError('Summary writer must have a logdir')

  # Saving the config file in the logdir.
  config_pbtxt = _text_format.MessageToString(config)
  path = os.path.join(logdir, _projector_plugin.PROJECTOR_FILENAME)
  with tf.io.gfile.GFile(path, 'w') as f:
    f.write(config_pbtxt)