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Incorporated an alg argument for GD which can be set to SDD(fast, unstable) or SVD(slow, stable) #175
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…nstable) or SDD(slow, stable)
Codecov ReportAll modified and coverable lines are covered by tests ✅
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I think you swapped SDD (fast, unstable) with SVD (slower, stable). |
I removed the explicit mention of SVD() and SDD() from the documentation.
Formatting
@lkdvos I updated everything according to your input. |
Ok, this has been resolved. For later reference, I had to make sure VSCode had the correct workspace loaded (so that .JuliaFormatter.toml was in my working directory) and then just run the normal formatter :) |
If you want, you can always manually run the formatter on the entire repository: using JuliaFormatter
format("src") |
@Jutho , @lkdvos what is the status here ? |
Again, apologies for the late response here too. With my suggestions for the TensorKitManifolds.jl, I don't think this is necessary anymore. I agree this approach is nicer, and so maybe this PR can stay open, but this only makes sense after a larger TensorKitManifolds.jl overhaul. As mentioned TensorKitManifolds.jl, there are also different retraction schemes possible for Grassmann, and the |
Ok. I personally don't mind the specific implementation as long as I have access to the stable SVD through some option in either MPSKit or TensorKitManifolds 👍 |
Given the recent discussions, I will close this for now. There is definitely some clean up work that can be done for the entire Grassman part of the code, but this will probably be for a different PR... |
Together with Jutho/TensorKitManifolds.jl#11 this implements functionality that allows the user to choose which SVD algorithm is being used internally in the gradient descent gradient calculation.
The options are SDD(fast but potentially unstable) vs SVD(slow but stable).
These two PR should fix the issue : #109