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diff --git a/compiler/locomotiv/src/Node/Softmax.cpp b/compiler/locomotiv/src/Node/Softmax.cpp
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+/*
+ * 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 "Validation.h"
+
+#include <nncc/core/ADT/tensor/Shape.h>
+#include <nncc/core/ADT/tensor/Buffer.h>
+#include <nncc/core/ADT/tensor/Index.h>
+#include <nncc/core/ADT/tensor/IndexEnumerator.h>
+#include <nncc/core/ADT/tensor/LexicalLayout.h>
+
+using nncc::core::ADT::tensor::Index;
+using nncc::core::ADT::tensor::IndexEnumerator;
+using nncc::core::ADT::tensor::LexicalLayout;
+using nncc::core::ADT::tensor::make_buffer;
+using nncc::core::ADT::tensor::Shape;
+
+#include <cassert>
+#include <stdexcept>
+#include <cmath>
+
+namespace
+{
+
+Index reduce_index(const Index &index, uint32_t axis)
+{
+ Index r_index;
+
+ r_index.resize(index.rank());
+ for (uint32_t i = 0; i < index.rank(); ++i)
+ r_index.at(i) = index.at(i);
+ r_index.at(axis) = 0;
+
+ return r_index;
+}
+
+Shape reduce_shape(const Shape &shape, uint32_t axis)
+{
+ Shape r_shape;
+
+ r_shape.resize(shape.rank());
+ for (uint32_t i = 0; i < shape.rank(); ++i)
+ r_shape.dim(i) = shape.dim(i);
+ r_shape.dim(axis) = 1;
+
+ return r_shape;
+}
+
+} // namespace
+
+namespace locomotiv
+{
+
+void NodeExecution::execute(loco::TensorSoftmax *softmax)
+{
+ auto input_data = annot_data(softmax->input());
+
+ validate(input_data, "Input not ready");
+ validate(annot_domain(softmax->input()) == loco::Domain::Tensor,
+ "Input domain of TensorSoftmax is not Tensor");
+
+ std::unique_ptr<NodeData> softmax_data = nullptr;
+
+ switch (input_data->dtype())
+ {
+ case loco::DataType::FLOAT32:
+ {
+ auto axis = softmax->axis();
+
+ auto *input_shape = input_data->shape();
+ auto input_bufptr = input_data->as_f32_bufptr();
+ auto softmax_buf = make_buffer<float, LexicalLayout>(*input_data->shape());
+
+ auto reduce_sum_shape = reduce_shape(*input_shape, axis);
+ auto reduce_sum_bufptr = make_buffer<float, LexicalLayout>(reduce_sum_shape);
+
+ for (IndexEnumerator e{*input_shape}; e.valid(); e.advance())
+ {
+ const auto &index = e.current();
+ const auto r_index = reduce_index(index, axis);
+
+ reduce_sum_bufptr.at(r_index) += exp(input_bufptr->at(index));
+ }
+
+ for (IndexEnumerator e{*input_shape}; e.valid(); e.advance())
+ {
+ const auto &index = e.current();
+ const auto r_index = reduce_index(index, axis);
+
+ softmax_buf.at(index) = exp(input_bufptr->at(index)) / reduce_sum_bufptr.at(r_index);
+ }
+
+ softmax_data = make_data(softmax_buf);
+ break;
+ }
+ default:
+ throw std::runtime_error("NYI for this DataType");
+ }
+
+ assert(softmax_data != nullptr);
+ annot_data(softmax, std::move(softmax_data));
+ annot_domain(softmax, annot_domain(softmax->input()));
+}
+
+} // namespace locomotiv