1 files changed, 135 insertions, 0 deletions
diff --git a/runtime/onert/backend/gpu_cl/TensorBuilder.cc b/runtime/onert/backend/gpu_cl/TensorBuilder.cc
new file mode 100644
index 000000000..318335471
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+++ b/runtime/onert/backend/gpu_cl/TensorBuilder.cc
@@ -0,0 +1,135 @@
+/*
+ * Copyright (c) 2021 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 <memory>
+#include <queue>
+
+#include "TensorBuilder.h"
+
+#include "TensorManager.h"
+
+#include "tensorflow/lite/delegates/gpu/cl/tensor_type_util.h"
+#include "tensorflow/lite/delegates/gpu/cl/cl_device.h"
+#include "tensorflow/lite/delegates/gpu/cl/inference_context.h"
+
+#include "ir/OperandIndexMap.h"
+#include "ir/OperandIndexSequence.h"
+#include <ir/Operands.h>
+#include <util/Utils.h>
+
+#include <cassert>
+#include <stack>
+
+#include "util/logging.h"
+
+namespace onert
+{
+namespace backend
+{
+namespace gpu_cl
+{
+
+using UsesType = cl_common::UsesType;
+
+TensorBuilder::TensorBuilder(const ir::Operands &operands, TensorManager *tensor_mgr)
+  : _operands{operands}, _tensor_mgr{tensor_mgr}
+{
+  assert(_tensor_mgr);
+}
+
+void TensorBuilder::registerTensorInfo(const ir::OperandIndex &ind, const ir::OperandInfo &info,
+                                       ir::Layout backend_layout, TensorType type)
+{
+  assert(_tensor_mgr->constTensors().size() == 0);
+  assert(_tensor_mgr->nonconstTensors().size() == 0);
+
+  _uses_count_map[ind] = _operands.at(ind).getUses().size();
+
+  _tensor_info_map.emplace(ind, info);
+  _tensor_type_map.emplace(ind, type);
+
+  _tensor_layout_map.insert({ind, backend_layout});
+}
+
+void TensorBuilder::notifyFirstUse(const ir::OperandIndex &ind)
+{
+  _lifetime_seq.emplace_back(UsesType::FIRST, ind);
+}
+
+void TensorBuilder::notifyLastUse(const ir::OperandIndex &ind)
+{
+  _lifetime_seq.emplace_back(UsesType::LAST, ind);
+}
+
+bool TensorBuilder::isRegistered(const ir::OperandIndex &ind) const
+{
+  return _tensor_info_map.find(ind) != _tensor_info_map.end();
+}
+
+void TensorBuilder::prepare(void) { buildTensors(); }
+
+void TensorBuilder::allocate(void)
+{
+  auto lifetime_map = cl_common::createLifetimeMap(_lifetime_seq, _parent_map);
+
+  for (const auto &entry : lifetime_map)
+  {
+    const auto &use = entry.second;
+    auto use_type = use.first;
+    auto use_index = use.second;
+    assert(use_index.valid());
+    if (use_type == UsesType::FIRST)
+      _tensor_mgr->startLifetime(use_index);
+    else
+      _tensor_mgr->finishLifetime(use_index);
+  }
+
+  _tensor_mgr->allocateConsts();
+
+  // TODO Since `_parent_map` is filled for all Concat nodes even if the node this backend uses
+  //      After refactoring BackendContext we can uncomment this
+  // assert(_tensor_info_map.size() ==
+  //       _tensor_mgr->nonconstTensors().size() + num of constants of _tensor_info_map +
+  //       _parent_map.size());
+  _tensor_mgr->allocateNonconsts();
+}
+
+void TensorBuilder::postFunctionPrepare(void) { _tensor_mgr->tryDeallocConstants(); }
+
+void TensorBuilder::buildTensors(void)
+{
+  assert(_tensor_mgr->constTensors().size() == 0);
+  assert(_tensor_mgr->nonconstTensors().size() == 0);
+  // Normal tensors
+  for (const auto &entry : _tensor_info_map)
+  {
+    const auto &ind = entry.first;
+    if (_parent_map.count(ind) > 0)
+      continue;
+    auto type = _tensor_type_map.at(ind);
+    const auto &info = entry.second;
+    _tensor_mgr->buildTensor(ind, info, type);
+  }
+}
+
+ir::OperandIndex TensorBuilder::addTensor(const ir::Shape &shape)
+{
+  return _tensor_mgr->addTensor(shape);
+}
+
+} // namespace gpu_cl
+} // namespace backend
+} // namespace onert