Update docs and verifiers

Signed-off-by: hanhanW <[email protected]>

Author: hanhanW

mlir/include/mlir/Dialect/Linalg/IR/LinalgRelayoutOps.td

@@ -150,9 +150,10 @@ def Linalg_PackOp : Linalg_RelayoutOp<"pack", [
 
     `padding_value` specifies a padding value at the boundary on non-perfectly
     divisible dimensions. Padding is optional:
-    - If absent, it is UB if the tile does not perfectly divide the dimension.
+    - If absent, it assumes the tile perfectly divides the dimension.
     - If present, it will pad along high dimensions (high-padding) to make the
-      tile complete.
+      tile complete. Note that it is not allowed to have artificial padding that
+      is not strictly required by linalg.pack.
 
     Example:
     ```mlir
@@ -167,6 +168,15 @@ def Linalg_PackOp : Linalg_RelayoutOp<"pack", [
     //
     // Note: Only tiled dimensions can be padded.
     ```
+
+    Invalid example that has artificial padding:
+    ```mlir
+    %0 = linalg.pack %src padding_value(%cst : f32) inner_dims_pos = [0]
+        inner_tiles = [8] into %dest
+        : tensor<9xf32> -> tensor<3x8xf32>
+    //                             \
+    //            expect tensor<2x8xf32> because CeilDiv(9, 8) = 2
+    ```
   }];
   let arguments = (ins AnyRankedTensor:$source,
                        AnyRankedTensor:$dest,

mlir/lib/Dialect/Linalg/IR/LinalgOps.cpp

@@ -32,6 +32,7 @@
 #include "mlir/IR/OpImplementation.h"
 #include "mlir/IR/OperationSupport.h"
 #include "mlir/IR/PatternMatch.h"
+#include "mlir/IR/TypeUtilities.h"
 #include "mlir/Interfaces/InferTypeOpInterface.h"
 #include "mlir/Interfaces/SideEffectInterfaces.h"
 
@@ -4599,22 +4600,6 @@ static bool isInvalidPackingPosSpecification(ArrayRef<int64_t> dimsPos,
   });
 }
 
-/// Returns true if the dimension of `sourceShape` is smaller than the dimension
-/// of the `limitShape`.
-static bool isCompatibleShape(ArrayRef<int64_t> sourceShape,
-                              ArrayRef<int64_t> limitShape) {
-  assert(
-      sourceShape.size() == limitShape.size() &&
-      "expected source shape rank, and limit of the shape to have same rank");
-  return llvm::all_of(
-      llvm::zip(sourceShape, limitShape), [](std::tuple<int64_t, int64_t> it) {
-        int64_t sourceExtent = std::get<0>(it);
-        int64_t limit = std::get<1>(it);
-        return ShapedType::isDynamic(sourceExtent) ||
-               ShapedType::isDynamic(limit) || sourceExtent == limit;
-      });
-}
-
 template <typename OpTy>
 static LogicalResult commonVerifierPackAndUnPackOp(OpTy packOrUnPack) {
   static_assert(llvm::is_one_of<OpTy, PackOp, UnPackOp>::value,
@@ -4689,10 +4674,10 @@ static LogicalResult commonVerifierPackAndUnPackOp(OpTy packOrUnPack) {
     return op->emitError("mismatch in inner tile sizes specified and shaped of "
                          "tiled dimension in the packed type");
   }
-  if (!isCompatibleShape(expectedPackedType.getShape(),
-                         packedType.getShape())) {
-    return op->emitError("the shape of output is not large enough to hold the "
-                         "packed data. Expected at least ")
+  if (failed(verifyCompatibleShape(expectedPackedType.getShape(),
+                                   packedType.getShape()))) {
+    return op->emitError("the shape of unpacked domain value is not large "
+                         "enough to hold the packed data. Expected at least ")
            << expectedPackedType << ", got " << packedType;
   }
   return success();

mlir/test/Dialect/Linalg/invalid.mlir

@@ -1828,23 +1828,23 @@ func.func @unpack_invalid_outer_dims_perm(%source: tensor<128x256xf32>, %dest: t
 // The outer dims in the output tensor are incorrectly/unexpectedly transposed.
 // This could be fixed by adding `outer_dims_perm = [1, 0]` (the default value assumes no transpose).
 func.func @pack_invalid_result_shape(%input: tensor<256x128xf32>, %output: tensor<4x16x32x16xf32>) -> tensor<4x16x32x16xf32> {
-  // expected-error@+1 {{the shape of output is not large enough to hold the packed data. Expected at least 'tensor<16x4x32x16xf32>', got 'tensor<4x16x32x16xf32>'}}
+  // expected-error@+1 {{the shape of unpacked domain value is not large enough to hold the packed data. Expected at least 'tensor<16x4x32x16xf32>', got 'tensor<4x16x32x16xf32>'}}
   %0 = linalg.pack %input inner_dims_pos = [1, 0] inner_tiles = [32, 16] into %output : tensor<256x128xf32> -> tensor<4x16x32x16xf32>
   return %0 : tensor<4x16x32x16xf32>
 }
 
 // -----
 
 func.func @pack_invalid(%input: tensor<256x128xf32>, %output: tensor<8x7x16x32xf32>) -> tensor<8x7x16x32xf32> {
-  // expected-error@+1 {{the shape of output is not large enough to hold the packed data. Expected at least 'tensor<8x8x16x32xf32>', got 'tensor<8x7x16x32xf32>'}}
+  // expected-error@+1 {{the shape of unpacked domain value is not large enough to hold the packed data. Expected at least 'tensor<8x8x16x32xf32>', got 'tensor<8x7x16x32xf32>'}}
   %0 = linalg.pack %input inner_dims_pos = [1, 0] inner_tiles = [16, 32] into %output : tensor<256x128xf32> -> tensor<8x7x16x32xf32>
   return %0 : tensor<8x7x16x32xf32>
 }
 
 // -----
 
 func.func @unpack_invalid(%output: tensor<256x128xf32>, %input: tensor<8x8x4x32xf32>) -> tensor<256x128xf32> {
-  // expected-error@+1 {{the shape of output is not large enough to hold the packed data. Expected at least 'tensor<8x32x4x32xf32>', got 'tensor<8x8x4x32xf32>'}}
+  // expected-error@+1 {{the shape of unpacked domain value is not large enough to hold the packed data. Expected at least 'tensor<8x32x4x32xf32>', got 'tensor<8x8x4x32xf32>'}}
   %0 = linalg.unpack %input inner_dims_pos = [1, 0] inner_tiles = [4, 32] into %output : tensor<8x8x4x32xf32> -> tensor<256x128xf32>
   return %0 : tensor<256x128xf32>
 }