[mlir][tensor] Enhance the verifier of pack and unpack op.

[hanchung]

Summary

The outer_dims_perm must be a permutation or empty.

mlir/lib/Dialect/Tensor/IR/TensorOps.cpp

ShapedType unpackedType = (std::is_same<OpTy, PackOp>::value)
                                 : packOrUnPack.getDestType();
   size_t unpackedRank = unpackedType.getRank();
   ArrayRef<int64_t> innerDimsPos = packOrUnPack.getInnerDimsPos();
   ArrayRef<int64_t> outerDimPerm = packOrUnPack.getOuterDimsPerm();
   if (isInvalidPackingPosSpecification(innerDimsPos, unpackedRank))
     return op->emitError("invalid inner_dims_pos vector");
   if (isInvalidPackingPosSpecification(outerDimPerm, unpackedRank))
     return op->emitError("invalid outer_dims_perm vector");
+  if (!outerDimPerm.empty() && outerDimPerm.size() != unpackedRank)
+    return op->emitError("outer_dims_perm must be a permutation or empty");
 
   // Tiling factors must be less than or equal to the input rank for pack (or
   // output rank for unpack), and must match the number of `inner_dims_pos`.
   if (mixedTiles.size() > unpackedRank) {
     return op->emitError("tiling factors must be less than or equal to the "
                          "input rank for pack or output rank for unpack");
   }
   if (mixedTiles.size() != innerDimsPos.size()) {

mlir/test/Dialect/Tensor/invalid.mlir

 func.func @unpack_invalid_out_of_bound_outer_perm(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> {
   // expected-error@+1 {{invalid outer_dims_perm vector}}
   %0 = tensor.unpack %output outer_dims_perm = [2, 1] inner_dims_pos = [0, 1] inner_tiles = [2, 2] into %input : tensor<8x8x32x16xf32> -> tensor<256x128xf32>
   return %0 : tensor<256x128xf32>
 }
 
 // -----
 
+func.func @pack_invalid_outer_dims_perm(%source: tensor<128x256xf32>, %dest: tensor<16x4x32x16xf32>) -> tensor<16x4x32x16xf32> {
+  // expected-error@+1 {{outer_dims_perm must be a permutation or empty}}
+  %0 = tensor.pack %source outer_dims_perm = [0] inner_dims_pos = [0, 1] inner_tiles = [32, 16] into %dest : tensor<128x256xf32> -> tensor<16x4x32x16xf32>
+  return %0 : tensor<16x4x32x16xf32>
+}
+
+// -----
+
+func.func @unpack_invalid_outer_dims_perm(%source: tensor<128x256xf32>, %dest: tensor<16x4x32x16xf32>) -> tensor<128x256xf32> {
+  // expected-error@+1 {{outer_dims_perm must be a permutation or empty}}
+  %0 = tensor.unpack %dest outer_dims_perm = [1] inner_dims_pos = [0, 1] inner_tiles = [32, 16] into %source : tensor<16x4x32x16xf32> -> tensor<128x256xf32>
+  return %0 : tensor<128x256xf32>
+}
+
+// -----
+
 func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x8x32x16xf32>) -> tensor<8x8x32x16xf32> {
   // expected-error@+1 {{the shape of output is not large enough to hold the packed data. Expected at least 'tensor<8x8x16x32xf32>', got 'tensor<8x8x32x16xf32>'}}
   %0 = tensor.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 32] into %output : tensor<256x128xf32> -> tensor<8x8x32x16xf32>
   return %0 : tensor<8x8x32x16xf32>
 }
 
 // -----