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Showing content from https://docs.pytorch.org/docs/stable/generated/torch.sparse.addmm.html below:

torch.sparse.addmm — PyTorch 2.7 documentation

torch.sparse.addmm(mat, mat1, mat2, *, beta=1., alpha=1.) → Tensor¶

This function does exact same thing as torch.addmm() in the forward, except that it supports backward for sparse COO matrix mat1. When mat1 is a COO tensor it must have sparse_dim = 2. When inputs are COO tensors, this function also supports backward for both inputs.

Supports both CSR and COO storage formats.

Note

This function doesn’t support computing derivaties with respect to CSR matrices.

Parameters

• mat (Tensor) – a dense matrix to be added

• mat1 (Tensor) – a sparse matrix to be multiplied

• mat2 (Tensor) – a dense matrix to be multiplied

• beta (Number, optional) – multiplier for mat ( β \beta β)

• alpha (Number, optional) – multiplier for m a t 1 @ m a t 2 mat1 @ mat2 mat1@mat2 ( α \alpha α)

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