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# LinearTransformation

class torchvision.transforms.v2.LinearTransformation(transformation_matrix: Tensor, mean_vector: Tensor)

  [BETA] Transform a tensor image or video with a square transformation matrix and a mean_vector computed offline.

  Note

  The LinearTransformation transform is in Beta stage, and while we do not expect disruptive breaking changes, some APIs may slightly change according to user feedback. Please submit any feedback you may have in this issue: https://github.com/pytorch/vision/issues/6753.

  This transform does not support PIL Image. Given transformation_matrix and mean_vector, will flatten the torch.*Tensor and subtract mean_vector from it which is then followed by computing the dot product with the transformation matrix and then reshaping the tensor to its original shape.

  Applications:

    whitening transformation: Suppose X is a column vector zero-centered data. Then compute the data covariance matrix [D x D] with torch.mm(X.t(), X), perform SVD on this matrix and pass it as transformation_matrix.

  Parameters:

    - transformation_matrix (Tensor) – tensor [D x D], D = C x H x W

    - mean_vector (Tensor) – tensor [D], D = C x H x W

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