[Mlir-commits] [mlir] [mlir][tosa] Disallow inferable dim in reshape/slice validation (PR #182472)

[Sayan Saha]

================
@@ -1214,6 +1215,47 @@ LogicalResult checkErrorIfPad(Operation *op) {
   return success();
 }
 
+LogicalResult checkErrorIfReshape(Operation *op) {
+  auto reshapeOp = dyn_cast<tosa::ReshapeOp>(op);
+  if (!reshapeOp)
+    return success();
+
+  constexpr int64_t kInferableDim = -1;
+  SmallVector<int64_t> shapeValues;
+  if (!tosa::getConstShapeValues(reshapeOp.getShape().getDefiningOp(),
+                                 shapeValues))
+    return success();
+
+  if (llvm::is_contained(shapeValues, kInferableDim))
+    return op->emitOpError("shape input contains inferable dimension (-1) "
+                           "which does not conform to the TOSA specification");
+
+  return success();
+}
+
+LogicalResult checkErrorIfSlice(Operation *op) {
+  auto sliceOp = dyn_cast<tosa::SliceOp>(op);
+  if (!sliceOp)
+    return success();
+
+  constexpr int64_t kInferableDim = -1;
+  SmallVector<int64_t> startValues;
+  SmallVector<int64_t> sizeValues;
+  const bool hasStartValues = tosa::getConstShapeValues(
+      sliceOp.getStart().getDefiningOp(), startValues);
+  const bool hasSizeValues =
+      tosa::getConstShapeValues(sliceOp.getSize().getDefiningOp(), sizeValues);
+
+  if (hasStartValues && llvm::is_contained(startValues, kInferableDim))
+    return op->emitOpError("start input contains inferable dimension (-1) "
+                           "which does not conform to the TOSA specification");
+  if (hasSizeValues && llvm::is_contained(sizeValues, kInferableDim))
+    return op->emitOpError("size input contains inferable dimension (-1) which "
----------------
sahas3 wrote:

This is a breaking change for us too. 

Source IR:
```
func.func @slice_nofold(%arg0: tensor<?x4xf32>) -> tensor<?x2xf32> {
  %0 = tosa.const_shape {values = dense<[0, 0]> : tensor<2xindex>} : () -> !tosa.shape<2>
  %1 = tosa.const_shape {values = dense<[-1, 2]> : tensor<2xindex>} : () -> !tosa.shape<2>
  %3 = tosa.slice %arg0, %0, %1 : (tensor<?x4xf32>, !tosa.shape<2>, !tosa.shape<2>) -> tensor<?x2xf32>
  return %3 : tensor<?x2xf32>
}
```

when lowered to `tensor` produces:
```
mlir-opt --tosa-to-tensor
func.func @slice_nofold(%arg0: tensor<?x4xf32>) -> tensor<?x2xf32> {
    %c0 = arith.constant 0 : index
    %dim = tensor.dim %arg0, %c0 : tensor<?x4xf32>
    %c0_0 = arith.constant 0 : index
    %0 = arith.subi %dim, %c0_0 : index
    %extracted_slice = tensor.extract_slice %arg0[0, 0] [%0, 2] [1, 1] : tensor<?x4xf32> to tensor<?x2xf32>
    return %extracted_slice : tensor<?x2xf32>
}
```

https://github.com/llvm/llvm-project/pull/182472