/// size. Otherwise, abort.
int64_t getNumDynamicDims() const;
- /// If `dim` is a dynamic dim, return its relative index among the dynamic
- /// dims. Otherwise, abort. The result is guaranteed to be nonnegative.
- int64_t getRelativeIndexOfDynamicDim(unsigned dim) const;
-
/// If this is ranked type, return the size of the specified dimension.
/// Otherwise, abort.
int64_t getDimSize(unsigned idx) const;
LogicalResult matchAndRewrite(T alloc,
PatternRewriter &rewriter) const override {
if (llvm::any_of(alloc->getUsers(), [&](Operation *op) {
- if (auto storeOp = dyn_cast<StoreOp>(op))
- return storeOp.value() == alloc;
- return !isa<DeallocOp>(op);
+ if (auto storeOp = dyn_cast<StoreOp>(op))
+ return storeOp.value() == alloc;
+ return !isa<DeallocOp>(op);
}))
return failure();
if (auto sizeInterface =
dyn_cast_or_null<OffsetSizeAndStrideOpInterface>(definingOp)) {
- int64_t nthDynamicIndex =
- memrefType.getRelativeIndexOfDynamicDim(unsignedIndex);
- return sizeInterface.sizes()[nthDynamicIndex];
+ assert(sizeInterface.isDynamicSize(unsignedIndex) &&
+ "Expected dynamic subview size");
+ return sizeInterface.getDynamicSize(unsignedIndex);
}
// dim(memrefcast) -> dim
return Value{*dynExtents};
}
- // dim(insert_slice.result()) -> dim(insert_slice.dest())
- if (auto insertSliceOp =
- dyn_cast_or_null<tensor::InsertSliceOp>(definingOp)) {
- this->sourceMutable().assign(insertSliceOp.dest());
- return getResult();
- }
-
// The size at the given index is now known to be a dynamic size.
unsigned unsignedIndex = index.getValue().getZExtValue();
- if (auto sizeInterface =
- dyn_cast_or_null<OffsetSizeAndStrideOpInterface>(definingOp)) {
- int64_t nthDynamicIndex =
- tensorType.getRelativeIndexOfDynamicDim(unsignedIndex);
- return sizeInterface.sizes()[nthDynamicIndex];
+ if (auto sliceOp = dyn_cast_or_null<tensor::ExtractSliceOp>(definingOp)) {
+ assert(sliceOp.isDynamicSize(unsignedIndex) &&
+ "Expected dynamic slice size");
+ return sliceOp.getDynamicSize(unsignedIndex);
}
// dim(cast) -> dim
return llvm::count_if(getShape(), isDynamic);
}
-int64_t ShapedType::getRelativeIndexOfDynamicDim(unsigned dim) const {
- assert(isDynamicDim(dim) && "expected a dynamic dim");
- int nthDynamicIndex = -1;
- for (unsigned idx = 0; idx <= dim; ++idx)
- if (isDynamicDim(idx))
- ++nthDynamicIndex;
- return nthDynamicIndex;
-}
-
bool ShapedType::hasStaticShape() const {
return hasRank() && llvm::none_of(getShape(), isDynamic);
}
}
// -----
-
// CHECK-LABEL: func @allocator
// CHECK: %[[alloc:.+]] = memref.alloc
// CHECK: memref.store %[[alloc:.+]], %arg0
func @allocator(%arg0 : memref<memref<?xi32>>, %arg1 : index) {
%0 = memref.alloc(%arg1) : memref<?xi32>
memref.store %0, %arg0[] : memref<memref<?xi32>>
- return
-}
-
-// -----
-
-#map0 = affine_map<(d0, d1)[s0, s1, s2] -> (d0 * s1 + s0 + d1 * s2)>
-
-// CHECK-LABEL: func @rank_reducing_subview_dim
-// CHECK-SAME: %[[IDX_0:[0-9a-zA-Z]*]]: index
-// CHECK-SAME: %[[IDX_1:[0-9a-zA-Z]*]]: index
-func @rank_reducing_subview_dim(%arg0 : memref<?x?x?xf32>, %arg1 : index,
- %arg2 : index) -> index
-{
- %c0 = constant 0 : index
- %c1 = constant 1 : index
- %c4 = constant 4 : index
- %0 = memref.subview %arg0[%c0, %arg1, %c1] [%c4, 1, %arg2] [%c1, %c1, %c1] : memref<?x?x?xf32> to memref<?x?xf32, #map0>
- %1 = memref.dim %0, %c1 : memref<?x?xf32, #map0>
-
- // CHECK-NEXT: return %[[IDX_1]] : index
- return %1 : index
+ return
}
%2 = tensor.dim %0, %c1 : tensor<?x?xf32>
return %1, %2: index, index
}
-
-// -----
-
-// CHECK-LABEL: func @rank_reducing_extract_slice_dim
-// CHECK-SAME: %[[IDX_0:[0-9a-zA-Z]*]]: index
-// CHECK-SAME: %[[IDX_1:[0-9a-zA-Z]*]]: index
-func @rank_reducing_extract_slice_dim(%arg0 : tensor<?x?x?xf32>, %arg1 : index,
- %arg2 : index) -> index
-{
- %c0 = constant 0 : index
- %c1 = constant 1 : index
- %c4 = constant 4 : index
- %0 = tensor.extract_slice %arg0[%c0, %arg1, %c1] [%c4, 1, %arg2] [%c1, %c1, %c1] : tensor<?x?x?xf32> to tensor<?x?xf32>
- %1 = tensor.dim %0, %c1 : tensor<?x?xf32>
-
- // CHECK-NEXT: return %[[IDX_1]] : index
- return %1 : index
-}
-
-// -----
-
-// CHECK-LABEL: func @rank_reducing_insert_slice_dim
-// CHECK-SAME: %[[OUT:[0-9a-zA-Z]*]]: tensor<?x?x?xf32>
-func @rank_reducing_insert_slice_dim(%out : tensor<?x?x?xf32>, %in : tensor<?x?xf32>, %arg1 : index,
- %arg2 : index) -> index
-{
- // CHECK-NEXT: %[[C1:.*]] = constant 1 : index
-
- %c0 = constant 0 : index
- %c1 = constant 1 : index
- %c4 = constant 4 : index
- %0 = tensor.insert_slice %in into %out[%c0, %arg1, %c1] [1, 1, 1] [%c1, %c1, %c1] : tensor<?x?xf32> into tensor<?x?x?xf32>
-
- // CHECK-NEXT: %[[D1:.*]] = tensor.dim %[[OUT]], %[[C1]] : tensor<?x?x?xf32>
- %1 = tensor.dim %0, %c1 : tensor<?x?x?xf32>
-
- // CHECK-NEXT: return %[[D1]] : index
- return %1 : index
-}