torch-vectorized 0.0.4

A quick closed-form solution for volumetric 3x3 matrices Eigen-Decomposition with Pytorch.

Volumetric Eigen-Decomposition of 3x3 matrices

A quick closed-form solution for volumetric 3x3 matrices Eigen-Decomposition with Pytorch. Solves Eigen-Decomposition of data with shape Bx9xDxHxW, where B is the batch size, 9 is the flattened 3x3 symmetric matrices, D is the depth, H is the Height, W is the width. The goal is to accelerate the Eigen-Decomposition of multiple (>500k) small matrices (3x3) on GPU with Pytorch using an analytical solution.

Install me

pip install torch-vectorized

How to use

from torchvectorized.vlinalg import vSymeig

# Random batch of volumetric 3x3 symmetric matrices of size 16x9x32x32x32
input = sym(torch.rand(16, 9, 32, 32, 32))

# Output eig_vals with size: 16x3x32x32x32 and eig_vecs with size 16,3,3,32,32,32
eig_vals, eig_vecs = vSymeig(input, eigen_vectors=True)

def sym(self, inputs):
    # Ensure symmetry of randomly generated 3x3 matrix using (X + X.T) / 2.0
    return (inputs + inputs[:, [0, 3, 6, 1, 4, 7, 2, 5, 8], :, :, :]) / 2.0

Contributing

How to contribute ?

• Create a branch by feature and/or bug fix
• Get the code
• Commit and push
• Create a pull request

Branch naming

Feature branch

feature/ [Short feature description] [Issue number]

Bug branch

fix/ [Short fix description] [Issue number]

Commits syntax:

Adding code:

+ Added [Short Description] [Issue Number]

Deleting code:

- Deleted [Short Description] [Issue Number]

Modifying code:

* Changed [Short Description] [Issue Number]

Merging code:

Y Merged [Short Description] [Issue Number]

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