IntelGPU backend: helper function improvement (#1541)

* IntelGPU backend: helper function improvement

* PR1541. Change string to stringsteam

src/ngraph/runtime/intelgpu/intelgpu_op_broadcast.cpp

@@ -52,7 +52,7 @@ void runtime::intelgpu::do_bcast_sum_operation(cldnn::topology& topology,
             gws = runtime::intelgpu::generate_loops(writer, output_shape, true);
 
             writer << "output" << access_dims(output_shape) << " = input0"
-                   << access_dims(output_shape, axis) << ";\n";
+                   << access_dims(output_shape, "i", axis) << ";\n";
 
             // Closing brackets for Broadcast loop
             runtime::intelgpu::generate_loops(writer, output_shape, false);
@@ -88,7 +88,7 @@ void runtime::intelgpu::do_bcast_sum_operation(cldnn::topology& topology,
                 ++var_idx;
             }
 
-            writer << "output" << access_dims(input_shape, axis) << " += input0"
+            writer << "output" << access_dims(input_shape, "i", axis) << " += input0"
                    << access_dims(input_shape) << ";\n";
 
             // Closing brackets for Sum loop
@@ -164,10 +164,10 @@ void runtime::intelgpu::do_max_min_operation(cldnn::topology& topology,
             }
 
             writer << "if (input" << access_dims(input_shape) << operation << "output"
-                   << access_dims(input_shape, axis) << ")\n";
+                   << access_dims(input_shape, "i", axis) << ")\n";
             writer.block_begin();
             {
-                writer << "output" << access_dims(input_shape, axis) << " = input"
+                writer << "output" << access_dims(input_shape, "i", axis) << " = input"
                        << access_dims(input_shape) << ";\n";
             }
             writer.block_end();
@@ -241,7 +241,7 @@ void runtime::intelgpu::do_product_operation(cldnn::topology& topology,
                 ++var_idx;
             }
 
-            writer << "output" << access_dims(input_shape, axis) << " *= input"
+            writer << "output" << access_dims(input_shape, "i", axis) << " *= input"
                    << access_dims(input_shape) << ";\n";
 
             // Closing brackets for loop

src/ngraph/runtime/intelgpu/intelgpu_op_custom_kernels.cpp

@@ -65,31 +65,33 @@ string runtime::intelgpu::array_dims(const Shape& dimentions, const AxisSet& axi
     return buffer;
 }
 
-string
-    runtime::intelgpu::access_dims(const Shape& dimentions, const AxisSet& axis, bool is_reversed)
+string runtime::intelgpu::access_dims(const Shape& dimentions,
+                                      const string& var,
+                                      const AxisSet& axis,
+                                      bool is_reversed)
 {
     size_t var_idx = 0;
-    string buffer;
+    stringstream buffer;
 
     for (auto const& i : dimentions)
     {
         if (axis.find(var_idx) == axis.end())
         {
-            buffer += "[i" + to_string(var_idx) + "]";
+            buffer << "[" << var << var_idx << "]";
         }
         else if (is_reversed)
         {
-            buffer += "[" + to_string(i) + " - i" + to_string(var_idx) + " - 1]";
+            buffer << "[" << i << " - " << var << var_idx << " - 1]";
         }
         ++var_idx;
     }
 
-    if (buffer.empty())
+    if (!buffer.rdbuf()->in_avail())
     { // it means scalar
-        buffer = "[0]";
+        buffer.str("[0]");
     }
 
-    return buffer;
+    return buffer.str();
 }
 
 void runtime::intelgpu::gen_func_def(codegen::CodeWriter& writer,
@@ -1028,7 +1030,7 @@ void runtime::intelgpu::do_reverse_operation(cldnn::topology& topology,
         gws = generate_loops(writer, output_shape, true);
 
         writer << "output" << access_dims(output_shape) << " = input0"
-               << access_dims(output_shape, reversed_axes, true) << ";\n";
+               << access_dims(output_shape, "i", reversed_axes, true) << ";\n";
 
         generate_loops(writer, output_shape, false);
     }

src/ngraph/runtime/intelgpu/intelgpu_op_custom_kernels.hpp

@@ -152,6 +152,7 @@ namespace ngraph
             std::vector<cldnn_arg> get_kernel_args(size_t input, size_t output);
             std::string array_dims(const Shape& dimentions, const AxisSet& axis = {});
             std::string access_dims(const Shape& dimentions,
+                                    const std::string& var = "i",
                                     const AxisSet& axis = {},
                                     bool is_reversed = false);
             std::vector<size_t>

src/ngraph/runtime/intelgpu/intelgpu_op_softmax.cpp

@@ -132,7 +132,7 @@ void runtime::intelgpu::do_softmax_operation(cldnn::topology& topology,
     const string entry_point_name = "softmax_" + output_name;
     const string middle_name = entry_point_name + "_middle";
     const string entry_point_middle_name = "softmax_middle_" + output_name;
-    const string expression = "output" + access_dims(input_shape, axes) + " = 0.0f;\n";
+    const string expression = "output" + access_dims(input_shape, "i", axes) + " = 0.0f;\n";
     const Shape new_shape = shape_dims(output_shape, axes);
     const cldnn::layout layout_middle = IntelGPULayout::create_cldnn_layout(output_type, new_shape);
     codegen::CodeWriter writer0;
@@ -147,7 +147,7 @@ void runtime::intelgpu::do_softmax_operation(cldnn::topology& topology,
     {
         gws = generate_loops_w_axes(writer0, output_shape, true, axes, expression);
 
-        writer0 << "output" << access_dims(input_shape, axes) << " += exp(input"
+        writer0 << "output" << access_dims(input_shape, "i", axes) << " += exp(input"
                 << access_dims(input_shape) << ");\n";
 
         generate_loops_w_axes(writer0, output_shape, false, axes, "");
@@ -173,7 +173,7 @@ void runtime::intelgpu::do_softmax_operation(cldnn::topology& topology,
     {
         gws = generate_loops(writer1, output_shape, true);
         writer1 << "output" << access_dims(input_shape) << " = exp(input0"
-                << access_dims(input_shape) << ")/input1" << access_dims(input_shape, axes)
+                << access_dims(input_shape) << ")/input1" << access_dims(input_shape, "i", axes)
                 << ";\n";
         generate_loops(writer1, output_shape, false);
     }