RuntimeError: mat1 dim 1 must match mat2 dim 0

This error message occurs when trying to perform matrix multiplication using the torch.matmul() function in PyTorch, and the dimensions of the input matrices are incompatible.

In particular, the error message indicates that the dimensionality of the first matrix (mat1) along the first axis (dim 1) must match the dimensionality of the second matrix (mat2) along the second axis (dim 0) for matrix multiplication to be possible.

To fix this error, you should ensure that the dimensions of the input matrices are compatible for matrix multiplication. This may involve reshaping or transposing the matrices to ensure that their dimensions match appropriately.

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RuntimeError: mat1 and mat2 shapes cannot be multiplied (24576x6 and 4608x2048)

This error occurs when trying to perform matrix multiplication between two matrices where the number of columns in the first matrix does not match the number of rows in the second matrix. In this case, mat1 has 24576 rows and 6 columns, while mat2 has 4608 rows and 2048 columns. To perform matrix multiplication, the number of columns in mat1 must match the number of rows in mat2.

To fix this error, you need to make sure that the matrices being multiplied have compatible shapes. You can either transpose one of the matrices or reshape them so that their dimensions match. Alternatively, you can modify the code to perform a different operation that is compatible with the current shapes of the matrices.

RuntimeError: mat1 and mat2 shapes cannot be multiplied (8x2352 and 784x8)

This error occurs because the number of columns in the first matrix (mat1) is not equal to the number of rows in the second matrix (mat2). In order to perform matrix multiplication, the number of columns in the first matrix must match the number of rows in the second matrix.

In this case, mat1 has 8 rows and 2352 columns, while mat2 has 784 rows and 8 columns. Since the number of columns in mat1 (2352) is not equal to the number of rows in mat2 (784), the matrices cannot be multiplied together.

To fix this error, you will need to ensure that the matrices have compatible shapes for multiplication. This could involve reshaping or transposing one or both matrices so that the number of columns in the first matrix matches the number of rows in the second matrix.