[mlir][vector] Disable vector.flat_transpose for scalable vectors (#115338)

Disables `vector.flat_transpose` for scalable vectors. As per the docs:

>  This is the counterpart of llvm.matrix.transpose in MLIR

I'm not aware of any use of any matrix-multiply intrinsics in the
context of scalable vectors, hence disabling.

Note, this is a follow-on for #102573 in which I disabled
`vector.matrix_multiply`.

Author: banach-space

mlir/include/mlir/Dialect/Vector/IR/VectorOps.td

@@ -2770,11 +2770,11 @@ def Vector_FlatTransposeOp : Vector_Op<"flat_transpose", [Pure,
                  TCresVTEtIsSameAsOpBase<0, 0>>]>,
     Arguments<(
       // TODO: tighten vector element types that make sense.
-      ins VectorOfRankAndType<[1],
+      ins FixedVectorOfRankAndType<[1],
             [AnySignlessInteger, AnySignedInteger, Index, AnyFloat]>:$matrix,
           I32Attr:$rows, I32Attr:$columns)>,
     Results<(
-      outs VectorOfRankAndType<[1],
+      outs FixedVectorOfRankAndType<[1],
              [AnySignlessInteger, AnySignedInteger, Index, AnyFloat]>:$res)> {
   let summary = "Vector matrix transposition on flattened 1-D MLIR vectors";
   let description = [{
@@ -2789,7 +2789,9 @@ def Vector_FlatTransposeOp : Vector_Op<"flat_transpose", [Pure,
     a 2-D matrix with <rows> rows and <columns> columns, and returns the
     transposed matrix in flattened form in 'res'.
 
-    Also see:
+    Note, the corresponding LLVM intrinsic, `@llvm.matrix.transpose.*`, does not
+    support scalable vectors. Hence, this Op is only available for fixed-width
+    vectors. Also see:
 
     http://llvm.org/docs/LangRef.html#llvm-matrix-transpose-intrinsic
 

mlir/test/Dialect/Vector/invalid.mlir

@@ -1900,3 +1900,12 @@ func.func @matrix_multiply_scalable(%a: vector<[4]xf64>, %b: vector<4xf64>) {
 
   return
 }
+
+// -----
+
+func.func @flat_transpose_scalable(%arg0: vector<[16]xf32>) -> vector<[16]xf32> {
+  // expected-error @+1 {{'vector.flat_transpose' op operand #0 must be fixed-length vector of signless integer or signed integer or index or floating-point values of ranks 1, but got 'vector<[16]xf32>'}}
+  %0 = vector.flat_transpose %arg0 { rows = 4: i32, columns = 4: i32 }
+     : vector<[16]xf32> -> vector<[16]xf32>
+  return %0 : vector<[16]xf32>
+}