[TE] Support negative indices

include/tvm/te/tensor.h

@@ -100,6 +100,15 @@ class TensorNode : public DataProducerNode {
  *  or intermediate computation result.
  */
 class Tensor : public DataProducer {
+ private:
+  /*!
+   * \brief Helper for indexing operations into tensors
+   * \param indices The indices
+   * \param support_negative_indices Whether to normalize indices in the case of negative indices.
+   * \return the result expression representing tensor read.
+   */
+  inline PrimExpr IndexTensor(Array<PrimExpr> indices, bool support_negative_indices) const;
+
  public:
   TVM_DLL Tensor(Array<PrimExpr> shape, DataType dtype, Operation op, int value_index);
   /*!
@@ -138,6 +147,29 @@ class Tensor : public DataProducer {
    * \return the result expression representing tensor read.
    */
   TVM_DLL PrimExpr operator()(Array<Var> indices) const;
+  /*!
+   * \brief Take elements from the tensor with support for negative indices.
+   * \param args The indices
+   * \return the result expression representing tensor read.
+   */
+  template <typename... Args>
+  TVM_DLL PrimExpr IndexWithNegativeIndices(Args&&... args) const {
+    Array<PrimExpr> indices{std::forward<Args>(args)...};
+    return IndexWithNegativeIndices(indices);
+  }
+  /*!
+   * \brief Take elements from the tensor with support for negative indices.
+   * \param indices the indices.
+   * \return the result expression representing tensor read.
+   */
+  TVM_DLL PrimExpr IndexWithNegativeIndices(Array<PrimExpr> indices) const;
+  /*!
+   * \brief Take elements from the tensor with support for negative indices.
+   * \param indices the indices.
+   * \return the result expression representing tensor read.
+   */
+  TVM_DLL PrimExpr IndexWithNegativeIndices(Array<Var> indices) const;
+
   /*!
    * \brief data structure to represent a slice that fixes first k coordinates.
    *  This is used to enable syntax sugar of Tensor[x][y][z] to get the element.

src/te/tensor.cc

@@ -39,18 +39,39 @@ IterVar reduce_axis(Range dom, std::string name) { return IterVar(dom, Var(name)
 Var var(std::string name_hint, DataType t) { return Var(name_hint, t); }
 
 // Tensor
+inline PrimExpr Tensor::IndexTensor(Array<PrimExpr> indices, bool support_negative_indices) const {
+  Array<PrimExpr> shape = (*this)->shape;
+
+  if (shape.size() != 0) {
+    ICHECK_EQ(shape.size(), indices.size())
+        << "Tensor dimension mismatch in read "
+        << "ndim = " << ndim() << ", indices.size=" << indices.size();
+  }
+
+  if (support_negative_indices) {
+    for (size_t i = 0; i < shape.size(); i++) {
+      PrimExpr new_index =
+          Select(indices[i] < make_const(indices[i]->dtype, 0), indices[i] + shape[i], indices[i]);
+      indices.Set(i, new_index);
+    }
+  }
+  return ProducerLoad((*this), indices);
+}
+
 PrimExpr Tensor::operator()(Array<Var> indices) const {
   Array<PrimExpr> arr(indices.begin(), indices.end());
   return operator()(arr);
 }
 
-PrimExpr Tensor::operator()(Array<PrimExpr> indices) const {
-  if (ndim() != 0) {
-    ICHECK_EQ(ndim(), indices.size()) << "Tensor dimension mismatch in read "
-                                      << "ndim = " << ndim() << ", indices.size=" << indices.size();
-  }
+PrimExpr Tensor::operator()(Array<PrimExpr> indices) const { return IndexTensor(indices, false); }
 
-  return ProducerLoad((*this), indices);
+PrimExpr Tensor::IndexWithNegativeIndices(Array<Var> indices) const {
+  Array<PrimExpr> arr(indices.begin(), indices.end());
+  return IndexWithNegativeIndices(arr);
+}
+
+PrimExpr Tensor::IndexWithNegativeIndices(Array<PrimExpr> indices) const {
+  return IndexTensor(indices, true);
 }
 
 String TensorNode::GetNameHint() const {

tests/cpp/tensor_test.cc

@@ -49,3 +49,14 @@ TEST(Tensor, Reduce) {
       {m, n}, [&](Var i, Var j) { return sum(max(1 + A[i][rv] + 1, B[j][rv]), {rv}); }, "C");
   LOG(INFO) << C->op.as<te::ComputeOpNode>()->body;
 }
+
+TEST(Tensor, Indexing) {
+  using namespace tvm;
+  using namespace tvm::te;
+
+  Var x("x"), y("y");
+  te::Tensor A = te::placeholder({x, y}, DataType::Float(32), "A");
+  LOG(INFO) << A(0, 0);
+  LOG(INFO) << A.IndexWithNegativeIndices(-1, -1);
+  LOG(INFO) << A.IndexWithNegativeIndices(0, -1);
+}