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WMLA EDT: Customization, Minimal Example & Documentation
Client asks how to use and customize the elastic distributed training (EDT) feature of WML-A. They explicitly complained about the lack of a detailed documentation (being aware of WMLA/Spectrum Conductor documentation in the knowledge center & the learning path page). In particular, they already inspected the ModelFabric code and complained that only loss functions with 2 parameters are supported.
Environment: - WMLA 1.2.2 - AC922
What is needed: 1. a way to customize train/test functions of the FabricModel, e.g., beyond 2 parameters in the loss function 2. an exhaustive API documentation of FabricModel 3. a minimal example that shows how to make a model use EDT (the client wishes for models.resnet50(pretrained=False) from torchvision) 4. a documentation (tutorial/blog post) describing point 3
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