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Co-authored-by: Alexandra <[email protected]>

doc/main/tbb_userguide/Advanced_Topic_Other_Kinds_of_Iteration_Spaces.rst

@@ -76,7 +76,7 @@ equivalent, even on a single processor.
 
 Also, ``blocked_range2d`` allows to use different value types across
 its first dimension (called "rows") and the second one ("columns").
-That allows combining indexes, pointers, and iterators into a joint
+That means you can combine indexes, pointers, and iterators into a joint
 iteration space. The method functions ``rows()`` and ``cols()`` return
 corresponding dimensions in the form of a ``blocked_range``.
 
@@ -90,7 +90,7 @@ constructor takes N instances of ``blocked_range<T>``, not individual boundary
 values. To indicate the distinctions, the different naming pattern was chosen.
 
 
-An Example of a Multidimensional Iteration Space
+Example of a Multidimensional Iteration Space
 ------------------------------------------------
 
 The example demonstrates calculation of a 3-dimensional filter over the pack

doc/main/tbb_userguide/snippets/blocked_nd_range_example.cpp

@@ -19,12 +19,12 @@ int main() {
     std::vector<std::vector<std::vector<float>>> feature_maps(feature_maps_length, std::vector<std::vector<float>>(feature_maps_width, std::vector<float>(feature_maps_heigth, 1.0f)));
     std::vector<std::vector<std::vector<float>>> out(out_length, std::vector<std::vector<float>>(out_width, std::vector<float>(out_heigth, 0.f)));
 
-    // 3D convolution calculates sum of all elements in kernel
+    // 3D convolution calculates the sum of all elements in the kernel
     convolution3d(feature_maps, out,
                   out_length, out_width, out_heigth,
                   kernel_length, kernel_width, kernel_height);
 
-    // Checks correctness of convolution by equality to expected sum of elements
+    // Checks correctness of convolution by equality to the expected sum of elements
     float expected = float(kernel_length * kernel_height * kernel_width);
     for (auto i : out) {
         for (auto j : i) {