fix Tensor(range, elemop) ctor to use placement-new instead of (move) assignment

src/TiledArray/tensor/tensor.h

@@ -144,9 +144,12 @@ class Tensor {
     size_t size = range_.volume() * nbatch;
     allocator_type allocator;
     auto* ptr = allocator.allocate(size);
-    if (default_construct) {
-      std::uninitialized_default_construct_n(ptr, size);
-      // std::uninitialized_value_construct_n(ptr, size);
+    // default construct elements of data only if can have any effect ...
+    if constexpr (!std::is_trivially_default_constructible_v<T>) {
+      // .. and requested
+      if (default_construct) {
+        std::uninitialized_default_construct_n(ptr, size);
+      }
     }
     auto deleter = [
 #ifdef TA_TENSOR_MEM_TRACE
@@ -182,9 +185,12 @@ class Tensor {
     size_t size = range_.volume() * nbatch;
     allocator_type allocator;
     auto* ptr = allocator.allocate(size);
-    if (default_construct) {
-      std::uninitialized_default_construct_n(ptr, size);
-      // std::uninitialized_value_construct_n(ptr, size);
+    // default construct elements of data only if can have any effect ...
+    if constexpr (!std::is_trivially_default_constructible_v<T>) {
+      // .. and requested
+      if (default_construct) {
+        std::uninitialized_default_construct_n(ptr, size);
+      }
     }
     auto deleter = [
 #ifdef TA_TENSOR_MEM_TRACE
@@ -288,7 +294,8 @@ class Tensor {
   }
 
   /// Construct a tensor with a range equal to \c range. The data is
-  /// uninitialized.
+  /// default-initialized (which, for `T` with trivial default constructor,
+  /// means data is uninitialized).
   /// \param range The range of the tensor
   /// \param nbatch The number of batches (default is 1)
   explicit Tensor(const range_type& range, size_type nbatch = 1)
@@ -336,9 +343,10 @@ class Tensor {
                 value_type, ElementIndexOp, const Range::index_type&>>>
   Tensor(const range_type& range, const ElementIndexOp& element_idx_op)
       : Tensor(range, 1, default_construct{false}) {
-    auto* data_ptr = data_.get();
+    pointer MADNESS_RESTRICT const data = this->data();
     for (auto&& element_idx : range) {
-      data_ptr[range.ordinal(element_idx)] = element_idx_op(element_idx);
+      const auto ord = range.ordinal(element_idx);
+      new (data + ord) value_type(element_idx_op(element_idx));
     }
   }
 
@@ -350,8 +358,9 @@ class Tensor {
   Tensor(const range_type& range, InIter it)
       : Tensor(range, 1, default_construct{false}) {
     auto n = range.volume();
-    pointer MADNESS_RESTRICT const data = this->data();
-    for (size_type i = 0ul; i < n; ++i, ++it) data[i] = *it;
+    pointer MADNESS_RESTRICT data = this->data();
+    for (size_type i = 0ul; i < n; ++i, ++it, ++data)
+      new (data) value_type(*it);
   }
 
   template <typename U>

tests/tensor_of_tensor.cpp

@@ -200,6 +200,15 @@ BOOST_AUTO_TEST_CASE_TEMPLATE(default_constructor, ITensor, itensor_types) {
 
 BOOST_AUTO_TEST_CASE_TEMPLATE(unary_constructor, ITensor, itensor_types) {
   const auto& a = ToT<ITensor>(0);
+
+  // apply element-wise op with default initializer
+  // this is a reproducer for
+  // https://github.com/ValeevGroup/tiledarray/issues/445
+  {
+    BOOST_CHECK_NO_THROW(
+        Tensor<ITensor> t(a.range(), [](auto&& l) { return ITensor(); }));
+  }
+
   // apply element-wise op
   BOOST_CHECK_NO_THROW(Tensor<ITensor> t(a, [](const int l) { return l * 2; }));
   Tensor<ITensor> t(a, [](const int l) { return l * 2; });