[mlir] vector.type_cast: disallow memrefs with layout in verifier

[ftynse]

Summary

These are not supported by any of the code using type_cast. In the general
case, such casting would require memrefs to handle a non-contiguous vector
representation or misaligned vectors (e.g., if the offset of the source memref
is not divisible by vector size, since offset in the target memref is expressed
in the number of elements).

mlir/lib/Dialect/Vector/VectorOps.cpp

 
 static void print(OpAsmPrinter &p, TypeCastOp op) {
   auto type = op.getOperand().getType().cast<MemRefType>();
   p << op.getOperationName() << ' ' << op.memref() << " : " << type << " to "
     << inferVectorTypeCastResultType(type);
 }
 
 static LogicalResult verify(TypeCastOp op) {
+  MemRefType canonicalType = canonicalizeStridedLayout(op.getMemRefType());
+  if (!canonicalType.getAffineMaps().empty())
+    return op.emitOpError("expects operand to be a memref with no layout");
+
   auto resultType = inferVectorTypeCastResultType(op.getMemRefType());
   if (op.getResultMemRefType() != resultType)
     return op.emitOpError("expects result type to be: ") << resultType;
   return success();
 }
 
 //===----------------------------------------------------------------------===//
 // TupleOp

mlir/test/Dialect/Vector/invalid.mlir

 }
 
 // -----
 
 func @reduce_unsupported_rank(%arg0: vector<4x16xf32>) -> f32 {
   // expected-error@+1 {{'vector.reduction' op unsupported reduction rank: 2}}
   %0 = vector.reduction "add", %arg0 : vector<4x16xf32> into f32
 }
+
+// -----
+
+func @type_cast_layout(%arg0: memref<4x3xf32, affine_map<(d0, d1)[s0, s1, s2] -> (d0 * s0 + d1 * s1 + s2)>>) {
+  // expected-error@+1 {{expects operand to be a memref with no layout}}
+  %0 = vector.type_cast %arg0: memref<4x3xf32, affine_map<(d0, d1)[s0, s1, s2] -> (d0 * s0 + d1 * s1 + s2)>> to memref<vector<4x3xf32>>
+}