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distributed-computing
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🚀 Feature Request
ENUMs for the catalyst-based conventions.
As an example, I will use scope
.
Motivation
We have a lot of callbacks that used scope
and maybe some other parameter that has only in catalyst-based meaning.
And every time we need to do something like that:
if isinstance(scope, str) and scope in [
"on_batch_end",
"on_batch_start",
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As a dask maintainer, I want to trust the code coverage report.
Our coverage badge is a bit misleading showing coverage below 90%. This is due to us not collecting coverage in a few places. Also, we simply have a few modules which are only there for debugging and/or historical reasons
The most relevant parts (scheduler, worker, etc.) do have quite good coverage. I believe the <90% batch does
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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
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the query!()
macro accepts the QueryFilter
which is a union of each of the field in the QueryFilter struct.
Right now, you can only specify one variant of the HeaderType
enum in the header_type() method for QueryFilter
.
This may not be necessary (because we can filter HeaderType in zome_fn level against what is returned from query macro), but may be nice to have if the header_type
fiel
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Avoid controlling endless loop with exception in
loadAnonymousClasses
, e.g. by extracting loading class to the method:https://sonarcloud.io/project