address klocwork issue (#1748)

src/ngraph/runtime/cpu/op/rnn.cpp

@@ -47,14 +47,14 @@ op::Rnn::Rnn(std::shared_ptr<Node> src_layer,
              std::shared_ptr<Node> weights_layer,
              std::shared_ptr<Node> weights_iter,
              std::shared_ptr<Node> bias,
-             const int num_timesteps,
-             const int num_gates_per_cell,
-             const int src_sequence_length,
-             const int src_layer_feature_size,
-             const int src_iter_feature_size,
-             const int num_cell_states,
-             const int direction,
-             const int num_fused_layers)
+             size_t num_timesteps,
+             size_t num_gates_per_cell,
+             size_t src_sequence_length,
+             size_t src_layer_feature_size,
+             size_t src_iter_feature_size,
+             size_t num_cell_states,
+             size_t direction,
+             size_t num_fused_layers)
     : Op("Rnn", check_single_output_args({src_layer, src_iter, weights_layer, weights_iter, bias}))
     , m_num_timesteps(num_timesteps)
     , m_num_gates_per_cell(num_gates_per_cell)
@@ -79,7 +79,7 @@ op::Rnn::Rnn(std::shared_ptr<Node> src_layer,
 
     if (src_layer->get_shape().size() == 2)
     {
-        m_batch_size = static_cast<int>(src_layer->get_shape()[0] / num_timesteps);
+        m_batch_size = src_layer->get_shape()[0] / m_num_timesteps;
     }
     else
     {
@@ -110,11 +110,9 @@ op::Rnn::Rnn(std::shared_ptr<Node> src_layer,
     set_output_size(2);
     set_output_type(0,
                     src_layer->get_element_type(),
-                    Shape{static_cast<unsigned long>(m_direction * m_num_timesteps * m_batch_size),
-                          static_cast<unsigned long>(m_src_iter_feature_size)});
+                    Shape{(m_direction * m_num_timesteps * m_batch_size), m_src_iter_feature_size});
     set_output_type(1,
                     src_layer->get_element_type(),
-                    Shape{static_cast<unsigned long>(m_num_cell_states * m_direction *
-                                                     m_num_fused_layers * m_batch_size),
-                          static_cast<unsigned long>(m_src_iter_feature_size)});
+                    Shape{(m_num_cell_states * m_direction * m_num_fused_layers * m_batch_size),
+                          m_src_iter_feature_size});
 }

src/ngraph/runtime/cpu/op/rnn.hpp

@@ -51,35 +51,35 @@ namespace ngraph
                 std::shared_ptr<Node> weights_layer,
                 std::shared_ptr<Node> weights_iter,
                 std::shared_ptr<Node> bias,
-                const int num_timesteps,
-                const int num_gates_per_cell,
-                const int src_sequence_length,
-                const int src_layer_feature_size,
-                const int src_iter_feature_size,
-                const int num_cell_states,
-                const int direction,
-                const int num_fused_layers);
+                size_t num_timesteps,
+                size_t num_gates_per_cell,
+                size_t src_sequence_length,
+                size_t src_layer_feature_size,
+                size_t src_iter_feature_size,
+                size_t num_cell_states,
+                size_t direction,
+                size_t num_fused_layers);
             virtual std::shared_ptr<Node>
                 copy_with_new_args(const NodeVector& new_args) const override;
-            int get_num_timesteps() const { return m_num_timesteps; }
-            int get_src_sequence_length() const { return m_src_sequence_length; }
-            int get_gates_per_cell() const { return m_num_gates_per_cell; }
-            int get_batch_size() const { return m_batch_size; }
-            int get_src_layer_feature_size() const { return m_src_layer_feature_size; }
-            int get_src_iter_feature_size() const { return m_src_iter_feature_size; }
-            int get_num_cell_states() const { return m_num_cell_states; }
-            int get_direction() const { return m_direction; }
-            int get_num_fused_layers() const { return m_num_fused_layers; }
+            size_t get_num_timesteps() const { return m_num_timesteps; }
+            size_t get_src_sequence_length() const { return m_src_sequence_length; }
+            size_t get_gates_per_cell() const { return m_num_gates_per_cell; }
+            size_t get_batch_size() const { return m_batch_size; }
+            size_t get_src_layer_feature_size() const { return m_src_layer_feature_size; }
+            size_t get_src_iter_feature_size() const { return m_src_iter_feature_size; }
+            size_t get_num_cell_states() const { return m_num_cell_states; }
+            size_t get_direction() const { return m_direction; }
+            size_t get_num_fused_layers() const { return m_num_fused_layers; }
         private:
-            int m_num_timesteps;
-            int m_num_gates_per_cell;
-            int m_src_sequence_length;
-            int m_batch_size;
-            int m_src_layer_feature_size;
-            int m_src_iter_feature_size;
-            int m_num_cell_states;
-            int m_direction;
-            int m_num_fused_layers;
+            size_t m_num_timesteps;
+            size_t m_num_gates_per_cell;
+            size_t m_src_sequence_length;
+            size_t m_batch_size;
+            size_t m_src_layer_feature_size;
+            size_t m_src_iter_feature_size;
+            size_t m_num_cell_states;
+            size_t m_direction;
+            size_t m_num_fused_layers;
         };
     }
 }