Need more helpful error message than "Result element type differs from the input element types." in certain cases

The code below is incorrect because it expects a tensor result from a vector-vector multiply. It results in a confusing error message that's not always helpful.


(mlirgraphblas) pnguyen@CONDA-0584:/Users/pnguyen/code/mlir-graphblas/mlir_graphblas/src$ cat /tmp/example.mlir

#CSR64 = #sparse_tensor.encoding<{
  dimLevelType = [ "dense", "compressed" ],
  dimOrdering = affine_map<(i,j) -> (i,j)>,
  pointerBitWidth = 64,
  indexBitWidth = 64
}>

#CSC64 = #sparse_tensor.encoding<{
  dimLevelType = [ "dense", "compressed" ],
  dimOrdering = affine_map<(i,j) -> (j,i)>,
  pointerBitWidth = 64,
  indexBitWidth = 64
}>

#CV64 = #sparse_tensor.encoding<{
  dimLevelType = [ "compressed" ],
  pointerBitWidth = 64,
  indexBitWidth = 64
}>

func @matrix_multiply_plus_times(%vecA: tensor<?xf64, #CV64>, %vecB: tensor<?xf64, #CV64>, %mask: tensor<?xf64, #CV64>) -> tensor<?xf64, #CV64> {
    %answer = graphblas.matrix_multiply %vecA, %vecB, %mask { semiring = "any_pair" } : (tensor<?xf64, #CV64>, tensor<?xf64, #CV64>, tensor<?xf64, #CV64>) to tensor<?xf64, #CV64>
    return %answer : tensor<?xf64, #CV64>
}
(mlirgraphblas) pnguyen@CONDA-0584:/Users/pnguyen/code/mlir-graphblas/mlir_graphblas/src$ cat /tmp/example.mlir | ./build/bin/graphblas-opt 
<stdin>:23:15: error: Result element type differs from the input element types.
    %answer = graphblas.matrix_multiply %vecA, %vecB, %mask { semiring = "any_pair" } : (tensor<?xf64, #CV64>, tensor<?xf64, #CV64>, tensor<?xf64, #CV64>) to tensor<?xf64, #CV64>
              ^
<stdin>:23:15: note: see current operation: %0 = "graphblas.matrix_multiply"(%arg0, %arg1, %arg2) {semiring = "any_pair"} : (tensor<?xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], pointerBitWidth = 64, indexBitWidth = 64 }>>, tensor<?xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], pointerBitWidth = 64, indexBitWidth = 64 }>>, tensor<?xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], pointerBitWidth = 64, indexBitWidth = 64 }>>) -> tensor<?xf64, #sparse_tensor.encoding<{ dimLevelType = [ "compressed" ], pointerBitWidth = 64, indexBitWidth = 64 }>>
(mlirgraphblas) pnguyen@CONDA-0584:/Users/pnguyen/code/mlir-graphblas/mlir_graphblas/src$

We should make sure there's a FileCheck test for whatever better error message we come up with.

metagraph-dev / mlir-graphblas

Need more helpful error message than "Result element type differs from the input element types." in certain cases #195