Define vector outer product (nnMatrixMulOuter), which removes the need to transpose layer inputs during training.

1 files changed, 10 insertions, 3 deletions

diff --git a/src/lib/include/neuralnet/matrix.h b/src/lib/include/neuralnet/matrix.h
index f80b985..4cb0d25 100644
--- a/src/lib/include/neuralnet/matrix.h
+++ b/src/lib/include/neuralnet/matrix.h
@@ -56,13 +56,20 @@ void nnMatrixInitConstant(nnMatrix*, R value);
 /// Multiply two matrices.
 void nnMatrixMul(const nnMatrix* left, const nnMatrix* right, nnMatrix* out);
 
-/// Multiply two matrices, row variant.
+/// Multiply two matrices, row-by-row variant.
 ///
-/// This function multiples two matrices row-by-row instead of row-by-column.
-/// nnMatrixMul(A, B, O) == nnMatrixMulRows(A, B^T, O).
+/// This function multiples two matrices row-by-row instead of row-by-column,
+/// which is equivalent to regular multiplication after transposing the right
+/// hand matrix.
+///
+///     nnMatrixMul(A, B, O) == nnMatrixMulRows(A, B^T, O).
 void nnMatrixMulRows(
     const nnMatrix* left, const nnMatrix* right, nnMatrix* out);
 
+/// Compute the outer product of two vectors.
+void nnMatrixMulOuter(
+    const nnMatrix* left, const nnMatrix* right, nnMatrix* out);
+
 /// Matrix multiply-add.
 ///
 /// out = left + (right * scale)