FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
The fedml-he example as implemented here does not seem to encrypt the model weights (torch tensors are communicated instead of ciphertext) even when the enable_fhe flag is true in the config file.
I checked the source code here and found that on line 29, the line should be:
if self.is_enabled:
return
Is that a mistake or did I interpret the code wrong ?
The fedml-he example as implemented here does not seem to encrypt the model weights (torch tensors are communicated instead of ciphertext) even when the
enable_fheflag istruein the config file.I checked the source code here and found that on line 29, the line should be:
Is that a mistake or did I interpret the code wrong ?