Sum-reduced gradient w.r.t. right operand for matmul. For the outer product case (rank-1 left operand), this computes: output = sum_s(left(:,s) (x) upstream(:,s)) = left * upstream^T using a single SGEMM call.
| Type | Intent | Optional | Attributes | Name | ||
|---|---|---|---|---|---|---|
| class(array_type), | intent(in) | :: | this | |||
| real(kind=real32), | intent(in), | dimension(:,:) | :: | upstream_grad | ||
| real(kind=real32), | intent(out), | dimension(:) | :: | output |
subroutine get_partial_matmul_right_val_sum(this, upstream_grad, output) #else pure subroutine get_partial_matmul_right_val_sum(this, upstream_grad, output) #endif !! Sum-reduced gradient w.r.t. right operand for matmul. !! For the outer product case (rank-1 left operand), this computes: !! output = sum_s(left(:,s) (x) upstream(:,s)) = left * upstream^T !! using a single SGEMM call. implicit none class(array_type), intent(in) :: this real(real32), dimension(:,:), intent(in) :: upstream_grad real(real32), dimension(:), intent(out) :: output integer :: i, j, s, m, n, num_elements, num_batches, num_upstream num_batches = size(upstream_grad, 2) if(size(this%left_operand%shape).eq.2)then ! 2D case: output = sum_s(W^T * upstream(:,s)) = W^T * sum(upstream, dim=2) m = this%left_operand%shape(1) n = this%left_operand%shape(2) if(this%left_operand%is_sample_dependent)then block real(real32), dimension(m, n) :: temp real(real32), dimension(n) :: col_result output = 0.0_real32 do s = 1, num_batches temp = reshape(this%left_operand%val(:,s), [m, n]) col_result = matmul(transpose(temp), upstream_grad(:,s)) output = output + col_result end do end block else #ifdef USE_BLAS block real(real32), pointer :: W(:,:) real(real32), dimension(size(upstream_grad,1)) :: upstream_sum W(1:m, 1:n) => this%left_operand%val(:,1) upstream_sum = sum(upstream_grad, dim=2) ! W^T * upstream_sum: sgemv with 'T' call sgemv('T', m, n, 1.0_real32, W, m, upstream_sum, 1, & 0.0_real32, output, 1) end block #else block real(real32), dimension(n, m) :: temp_t real(real32), dimension(size(upstream_grad,1)) :: upstream_sum temp_t = transpose(reshape(this%left_operand%val(:,1), [m, n])) upstream_sum = sum(upstream_grad, dim=2) output = matmul(temp_t, upstream_sum) end block #endif end if else ! Outer product case: sum_s(left(i,s) * upstream(j,s)) ! = matmul(left, upstream^T) stored column-major num_elements = size(this%left_operand%val, 1) num_upstream = size(upstream_grad, 1) if(this%left_operand%is_sample_dependent)then #ifdef USE_BLAS call sgemm('N', 'T', num_elements, num_upstream, num_batches, & 1.0_real32, this%left_operand%val, num_elements, & upstream_grad, num_upstream, & 0.0_real32, output, num_elements) #else output = 0.0_real32 do s = 1, num_batches do j = 1, num_upstream do i = 1, num_elements output((j-1)*num_elements + i) = & output((j-1)*num_elements + i) + & upstream_grad(j,s) * this%left_operand%val(i,s) end do end do end do #endif else block real(real32), dimension(num_upstream) :: upstream_sum upstream_sum = sum(upstream_grad, dim=2) do j = 1, num_upstream output((j-1)*num_elements+1:j*num_elements) = & this%left_operand%val(:, 1) * upstream_sum(j) end do end block end if end if end subroutine get_partial_matmul_right_val_sum