There is no technical difficulty to support includeValue option, looks like we are just missing it on the API level.

See SO question

Similar to dask/dask#7800, we can replace our tmpfile context manager

https://github.com/dask/distributed/blob/5e5b9835a5e6929bb97acf94f0a2eecccc0b6a2f/distributed/utils.py#L862-L863

with tempfile.TemporaryFile from the standard library.

It seems that the number of joining clients (not the num of computing clients) is fixed in fedml_api/data_preprocessing/**/data_loader and cannot be changed except CIFAR10 datasets.

Here I mean that it seems the total clients is decided by the datasets, rather the input from run_fedavg_distributed_pytorch.sh.

https://github.com/FedML-AI/FedML/blob/3d9fda8d149c95f25ec4898e31df76f035a33b5d/fed

Summary

What change needs making?
Example script on how to use created secret successfully.
I have tried myself using the following code from test
It creates a secret successfully but fails to echo the secrets value.

Use Cases

When would you use this?
when I n

If enter_data() is called with the same train_path twice in a row and the data itself hasn't changed, a new Dataset does not need to be created.

We should add a column which stores some kind of hash of the actual data. When a Dataset would be created, if the metadata and data hash are exactly the same as an existing Dataset, nothing should be added to the ModelHub database and the existing