For all of the listed applications there is a cleaner function in numpy (and tensorflow, right?) Vector inner product: "a,a->" (Assumes two vectors of same

For all of the listed applications there is a cleaner function in numpy (and tensorflow, right?) Vector inner product: "a,a->" (Assumes two vectors of same length) Vector element-wise product: "a,a->a" (Assumes two vectors of same length) Vector outer product: "a,b->ab" (Vectors not necessarily same length.) Matrix transposition: "ab->ba" Matrix diagonal: "ii->i" Matrix trace: "ii->" 1-D Sum: "a->" 2-D Sum: "ab->" 3-D Sum: "abc->" Matrix inner product "ab,ab->" (If you pass twice the same argument, it becomes a matrix L2 norm) Left-multiplication Matrix-Vector: "ab,b->a" Right-multiplication Vector-Matrix: "a,ab->b" Matrix Multiply: "ab,bc->ac" Batch Matrix Multiply: "Yab,Ybc->Yac" Quadratic form / Mahalanobis Distance: "a,ab,b->"