[onert] Introduce BackPropAccumulator (Samsung#12878)

This commit introduces BackPropAccumulator that sums branched back-prop tensors accumulatively.

ONE-DCO-1.0-Signed-off-by: ragmani <[email protected]>

runtime/onert/backend/train/ops/BackPropAccumulator.cc

@@ -0,0 +1,63 @@
+/*
+ * Copyright (c) 2024 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 "BackPropAccumulator.h"
+
+#include "OperationUtils.h"
+
+#include <cker/operation/BinaryArithmeticOps.h>
+#include <util/CalculateActivationRange.h>
+
+namespace onert
+{
+namespace backend
+{
+namespace train
+{
+namespace ops
+{
+
+BackPropAccumulator::BackPropAccumulator(const IPortableTensor *disposable_tensor,
+                                         IPortableTensor *back_prop_tensor)
+  : _disposable_tensor{disposable_tensor}, _back_prop_tensor{back_prop_tensor}
+{
+  if (disposable_tensor->getShape() != back_prop_tensor->getShape())
+    throw std::runtime_error("train BackPropAccumulator: Unsupported shapes");
+
+  float output_activation_min = 0, output_activation_max = 0;
+  util::CalculateActivationRange(ir::Activation::NONE, &output_activation_min,
+                                 &output_activation_max);
+  _op_params.float_activation_max = output_activation_max;
+  _op_params.float_activation_min = output_activation_min;
+}
+
+void BackPropAccumulator::forward(bool)
+{
+  // DO NOTHING
+}
+
+void BackPropAccumulator::backward()
+{
+  nnfw::cker::BinaryArithmeticOp<nnfw::cker::BinaryArithmeticOpType::ADD>(
+    _op_params, getShape(_disposable_tensor), getBuffer<float>(_disposable_tensor),
+    getShape(_back_prop_tensor), getBuffer<float>(_back_prop_tensor), getShape(_back_prop_tensor),
+    getBuffer<float>(_back_prop_tensor));
+}
+
+} // namespace ops
+} // namespace train
+} // namespace backend
+} // namespace onert

runtime/onert/backend/train/ops/BackPropAccumulator.h

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+/*
+ * Copyright (c) 2024 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.
+ */
+
+#ifndef __ONERT_BACKEND_TRAIN_OPS_BACKPROP_ACCUMULATOR_H__
+#define __ONERT_BACKEND_TRAIN_OPS_BACKPROP_ACCUMULATOR_H__
+
+#include <backend/IPortableTensor.h>
+#include <cker/Types.h>
+#include <exec/train/ITrainableFunction.h>
+
+namespace onert
+{
+namespace backend
+{
+namespace train
+{
+namespace ops
+{
+
+// TODO Introduce IFunction for only backwarding
+class BackPropAccumulator : public exec::train::ITrainableFunction
+{
+public:
+  BackPropAccumulator(const IPortableTensor *disposable_tensor, IPortableTensor *back_prop_tensor);
+
+public:
+  void forward(bool training) override;
+  void backward() override;
+
+private:
+  const IPortableTensor *_disposable_tensor;
+  IPortableTensor *_back_prop_tensor;
+
+  nnfw::cker::BinaryArithmeticOpParam _op_params;
+};
+
+} // namespace ops
+} // namespace train
+} // namespace backend
+} // namespace onert
+
+#endif // __ONERT_BACKEND_TRAIN_OPS_BACKPROP_ACCUMULATOR_H__