1 files changed, 116 insertions, 0 deletions
diff --git a/compiler/locomotiv/src/Node/ConstGen.cpp b/compiler/locomotiv/src/Node/ConstGen.cpp
new file mode 100644
index 000000000..0360b9fef
--- /dev/null
+++ b/compiler/locomotiv/src/Node/ConstGen.cpp
@@ -0,0 +1,116 @@
+/*
+ * Copyright (c) 2019 Samsung Electronics Co., Ltd. All Rights Reserved
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "NodeExecution.h"
+
+#include "NodeDataImpl.h"
+#include "NodeDomain.h"
+
+#include <nncc/core/ADT/tensor/Shape.h>
+#include <nncc/core/ADT/tensor/Buffer.h>
+#include <nncc/core/ADT/tensor/IndexEnumerator.h>
+#include <nncc/core/ADT/tensor/LexicalLayout.h>
+
+#include <stdexcept>
+#include <cassert>
+
+using nncc::core::ADT::tensor::Index;
+using nncc::core::ADT::tensor::IndexEnumerator;
+using nncc::core::ADT::tensor::Shape;
+using nncc::core::ADT::tensor::LexicalLayout;
+using nncc::core::ADT::tensor::make_buffer;
+
+namespace
+{
+
+/**
+ * @brief Get offset based on given shape and index. Assume lexical layout.
+ *
+ * examples)
+ * For shape = {3, 4} and index = {1, 2},
+ *     offset would be 6 ( = 1 * (4) + 2 )
+ * For shape = {2, 3, 4} and index = {1, 0, 2},
+ *     offset would be 14 ( = 1 * (3*4) + 0 *(4) + 2 )
+ */
+inline uint32_t offset_by_index(const Shape &shape, const Index &index)
+{
+  static const nncc::core::ADT::tensor::LexicalLayout l;
+  return l.offset(shape, index);
+}
+
+} // namespace
+
+namespace locomotiv
+{
+
+void NodeExecution::execute(loco::ConstGen *constgen)
+{
+  uint32_t volume = 1;
+
+  Shape shape;
+  shape.resize(constgen->rank());
+  for (uint32_t i = 0; i < shape.rank(); ++i)
+  {
+    shape.dim(i) = constgen->dim(i).value();
+    volume *= shape.dim(i);
+  }
+
+  std::unique_ptr<NodeData> data = nullptr;
+
+  switch (constgen->dtype())
+  {
+    case loco::DataType::S32:
+    {
+      assert(volume == constgen->size<loco::DataType::S32>());
+
+      auto buf = make_buffer<int32_t, LexicalLayout>(shape);
+
+      for (IndexEnumerator e{shape}; e.valid(); e.advance())
+      {
+        const auto &index = e.current();
+        uint32_t offset = ::offset_by_index(shape, index);
+        buf.at(index) = constgen->at<loco::DataType::S32>(offset);
+      }
+
+      data = locomotiv::make_data(buf);
+      break;
+    }
+    case loco::DataType::FLOAT32:
+    {
+      assert(volume == constgen->size<loco::DataType::FLOAT32>());
+
+      auto buf = make_buffer<float, LexicalLayout>(shape);
+
+      for (IndexEnumerator e{shape}; e.valid(); e.advance())
+      {
+        const auto &index = e.current();
+        uint32_t offset = ::offset_by_index(shape, index);
+        buf.at(index) = constgen->at<loco::DataType::FLOAT32>(offset);
+      }
+
+      data = locomotiv::make_data(buf);
+      break;
+    }
+    default:
+      throw std::runtime_error("NYI for this DataType");
+  }
+
+  assert(data != nullptr);
+  annot_data(constgen, std::move(data));
+  annot_domain(constgen, loco::Domain::Tensor);
+}
+
+} // namespace locomotiv