Fix VGF runtime aborts on 0-dim tensor inputs and Python scalar coercion (#19446)

extension/aten_util/aten_bridge.cpp

@@ -18,11 +18,22 @@ namespace extension {
 
 namespace {
 void check_tensor_meta(const at::Tensor& a, const executorch::aten::Tensor& b) {
-  // Check sizes/strides pointers
-  ET_CHECK_MSG(
-      b.sizes().data() != nullptr, "ETensor must have valid sizes array");
-  ET_CHECK_MSG(
-      b.strides().data() != nullptr, "ETensor must have valid strides array");
+  // 0-dim (scalar) tensors legitimately have empty sizes/strides arrays;
+  // their `.data()` may return nullptr depending on the underlying container.
+  // Only require non-null sizes/strides/dim_order storage when the tensor
+  // actually has at least one dimension. The nullptr check is meant to catch
+  // malformed metadata for ranked tensors (where these arrays MUST be
+  // addressable because dim_order_to_stride_nocheck below indexes into them);
+  // it must not abort on valid 0-dim inputs.
+  if (b.dim() > 0) {
+    ET_CHECK_MSG(
+        b.sizes().data() != nullptr, "ETensor must have valid sizes array");
+    ET_CHECK_MSG(
+        b.strides().data() != nullptr, "ETensor must have valid strides array");
+    ET_CHECK_MSG(
+        b.dim_order().data() != nullptr,
+        "ETensor must have valid dim_order array");
+  }
   // Check disabled because in ASR model we get 1 element tensor with different
   // rank.
   /*

extension/aten_util/test/aten_bridge_test.cpp

@@ -155,6 +155,47 @@ TEST(ATenBridgeTest, AliasTensorPtrToATenTensor) {
   EXPECT_EQ(at_tensor.const_data_ptr(), et_tensor_ptr->const_data_ptr());
 }
 
+// 0-dim (scalar) tensors legitimately have empty sizes/strides arrays whose
+// `.data()` may return nullptr. Regression test for T270603238: ensure
+// check_tensor_meta does not abort on valid 0-dim tensors. We pass nullptr
+// explicitly for sizes/dim_order/strides because std::vector::data() on an
+// empty vector is implementation-defined (libstdc++/libc++ may return a
+// non-null sentinel) — using nullptr makes the regression deterministic
+// across STL implementations.
+TEST(ATenBridgeTest, AliasETensorToATenTensorZeroDim) {
+  auto at_tensor = at::scalar_tensor(42.0f);
+  ASSERT_EQ(at_tensor.dim(), 0);
+  auto dtype = torchToExecuTorchScalarType(at_tensor.options().dtype());
+  torch::executor::TensorImpl tensor_impl(
+      dtype,
+      /*dim=*/0,
+      /*sizes=*/nullptr,
+      /*data=*/nullptr,
+      /*dim_order=*/nullptr,
+      /*strides=*/nullptr);
+  torch::executor::Tensor etensor(&tensor_impl);
+  alias_etensor_to_attensor(at_tensor, etensor);
+  EXPECT_EQ(at_tensor.const_data_ptr(), etensor.const_data_ptr());
+}
+
+TEST(ATenBridgeTest, AliasATTensorToETensorZeroDim) {
+  auto at_tensor = at::scalar_tensor(7);
+  ASSERT_EQ(at_tensor.dim(), 0);
+  auto dtype = torchToExecuTorchScalarType(at_tensor.options().dtype());
+  std::vector<uint8_t> etensor_data(at_tensor.nbytes());
+  torch::executor::TensorImpl tensor_impl(
+      dtype,
+      /*dim=*/0,
+      /*sizes=*/nullptr,
+      etensor_data.data(),
+      /*dim_order=*/nullptr,
+      /*strides=*/nullptr);
+  torch::executor::Tensor etensor(&tensor_impl);
+  auto aliased_at_tensor = alias_attensor_to_etensor(etensor);
+  EXPECT_EQ(aliased_at_tensor.dim(), 0);
+  EXPECT_EQ(aliased_at_tensor.const_data_ptr(), etensor_data.data());
+}
+
 TEST(ATenBridgeTest, AliasATTensorToETensorChannelsLast) {
   auto at_tensor = at::randn({2, 3, 4, 5}).to(at::MemoryFormat::ChannelsLast);
   std::vector<Tensor::SizesType> sizes(