make rnn.fsx example device agnostic.#428
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nhirschey wants to merge 1 commit intoDiffSharp:devfrom
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dsyme
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Oct 11, 2022
| if File.Exists(modelFileName) then | ||
| printfn "Resuming training from existing model params found: %A" modelFileName | ||
| languageModel.state <- dsharp.load(modelFileName) | ||
| languageModel.move(Device.Default) |
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Shouldn't the load happen on the default device in any case? Is this a problem with dsharp.load?
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Yes, I think dsharp.load loading into the default device makes sense, and that's what seems to be the goal of PR #430.
Pytorch is a little different, it would torch.load into whatever device the tensor was saved from: "They are first deserialized on the CPU and are then moved to the device they were saved from" (link).
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Some minor changes that will allow rnn.fsx to run if the dsharp.config is changed to GPU.
Thanks for your incredible work this past month to incorporate my change requests into the dev branch! I'm looking forward to using the new version once it's released on the nuget feed.