dot

Matrix product of two tensors.

The behavior depends on the dimensionality of the tensors as follows:

1. If both tensors are 1-dimensional, the dot product (scalar) is returned.

2. If both arguments are 2-dimensional, the matrix-matrix product is returned.

3. If the first argument is 1-dimensional and the second argument is 2-dimensional, a 1 is prepended to its dimension for the purpose of the matrix multiply. After the matrix multiply, the prepended dimension is removed.

4. If the first argument is 2-dimensional and the second argument is 1-dimensional, the matrix-vector product is returned.

5. If both arguments are at least 1-dimensional and at least one argument is N-dimensional (where N 2), then a batched matrix multiply is returned. If the first argument is 1-dimensional, a 1 is prepended to its dimension for the purpose of the batched matrix multiply and removed after. If the second argument is 1-dimensional, a 1 is appended to its dimension for the purpose of the batched matrix multiple and removed after. The non-matrix (i.e., batch) dimensions are broadcast (and thus must be broadcastable). For example, if input is a (j × 1 × n × n) tensor and other is a (k × n × n) tensor, out will be a (j × k × n × n) tensor.

For more information: https://pytorch.org/docs/stable/generated/torch.matmul.html

Return

a mathematical product of two tensors.

Parameters