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# PyTorch torch.addmm Function * * Pytorch torch reference manual](#) `torch.addmm` is a function in PyTorch used to add the result of matrix multiplication to an input matrix. It performs matrix multiplication of mat1 @ mat2 and then adds the result to input. ### Function Definition torch.addmm(input, mat1, mat2, *, beta=1.0, alpha=1.0, out=None) **Parameters**: * `input` (Tensor): Input matrix, which is added to the result. * `mat1` (Tensor): First matrix with shape (n, m). * `mat2` (Tensor): Second matrix with shape (m, p). * `beta` (float, optional): Coefficient for multiplying input, default is 1.0. * `alpha` (float, optional): Coefficient for multiplying the result of mat1 @ mat2, default is 1.0. * `out` (Tensor, optional): Output tensor. **Return Value**: * `torch.Tensor`: Returns the sum of the matrix multiplication result and the input matrix with shape (n, p). * * * ## Usage Examples ## Example import torch # Create input matrix and two matrices input= torch.randn(3,3) mat1 = torch.randn(3,4) mat2 = torch.randn(4,3) # Perform addmm result = torch.addmm(input, mat1, mat2) print("Input matrix shape:",input.shape) print("Matrix 1 shape:", mat1.shape) print("Matrix 2 shape:", mat2.shape) print("Result shape:", result.shape) print(result) Output result is: Input matrix shape: torch.Size([3, 3])Matrix 1 shape: torch.Size([3, 4])Matrix 2 shape: torch.Size([4, 3])Result shape: torch.Size([3, 3]) tensor([[ 0.4692, -0.2864, -0.6013], [ 1.5525, 0.1233, -0.0182], [-0.3956, 0.6267, 0.3580]]) ## Example - Using alpha and beta parameters import torch input= torch.randn(3,3) mat1 = torch.randn(3,4) mat2 = torch.randn(4,3) # Use alpha and beta parameters result = torch.addmm(input, mat1, mat2, beta=0.5, alpha=2.0) # Equivalent to: result = 0.5 * input + 2.0 * (mat1 @ mat2) print(result) * * Pytorch torch reference manual](#)