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## š Feature Discussion
**The question is whether solve-like functions need to support batch broadcasting for _b_ of shape `(n,)`.**
PyTorch currently includes several functions for problems of ā¦
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The following script:
https://github.com/Jammy2211/autofit_workspace/blob/release/scripts/howtofit/chapter_graphical_models/tutorial_3_expectation_propagation.py
The following errors are printedā¦
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### š Describe the bug
Not sure where this should be filed under. But I noticed that, in the most recent version of pytorch `1.11.0+cu102`, when using `torch.cholesky`, it says it's deprecated in fā¦
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### š Describe the bug
From https://discuss.pytorch.org/t/torch-function-runtime-dependent-on-scipy-call/139483:
I've noticed that certain PyTorch functions run slower when I make calls to `scipy.ā¦
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### Description
Singular matrix with linearly dependent columns have infinitely many LU factorisations.
However, the lax implementation of LU factorisation will return a factorisation regardless.ā¦
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Currently, Matrix_double_dense inherits from Matrix_dense and Matrix_double_sparse from Matrix_sparse. However numerical matrices share a lot compared to other matrices and should probably have a coā¦
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Hello, I followed the steps in the tutorial to complete the initial setup, but I got the following error when I ran this function:
Output = FastMM_singleGeneKO(model);
Warning: FastMM_singleGeneā¦
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Hi,
I'm using a two-layer deep GP with Poisson likelihood. With the default zero mean function, there is no problem for step:
history = model.fit({"inputs": x_train, "targets": y_train}, batch_siā¦
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I am applying SuperLU_MT Ā (version 3.1) which is supported by Amesos2 to calculate preconditioner. It is found that the SuperLU_MT has great parallel performance in LU decomposition. However, when I uā¦
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### š Describe the bug
With `jiterator` machinery now available, we can use it to remove the ahead of time compilation cost and decrease the CUDA context size introduced by complex dtypes wherever poā¦