什么决定了 TensorBoard 的嵌入选项卡中的运行顺序？

Question

一些例子：

Answer 1

TensorBoard 嵌入项目后端 serves the runs 作为 Python dict 对象中的键列表：

@wrappers.Request.application
def _serve_runs(self, request):
  """Returns a list of runs that have embeddings."""
  return Respond(request, list(self.configs.keys()), 'application/json')

引用 Python documentation for Dictionaries:

Performing list(d.keys()) on a dictionary returns a list of all the keys used in the dictionary, in arbitrary order (if you want it sorted, just use sorted(d.keys()) instead).

Answer 2

2020 年 10 月更新：

现在按 run-time 排序进行实验： https://github.com/tensorflow/tensorboard/blob/538eaeb53076943408d8026a7194ddb50168a77d/tensorboard/plugins/core/core_plugin.py#L171

我希望有一个选项可以根据自己的选择对它进行排序 alphabetically/run-time，等等...

什么决定了 TensorBoard 的嵌入选项卡中的运行顺序？

What determine the order of the runs in TensorBoard's embeddings tab?

python

tensorflow

embedding

tensorboard