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-rw-r--r--runtime/neurun/test/graph/operation/SetIO.cc99
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diff --git a/runtime/neurun/test/graph/operation/SetIO.cc b/runtime/neurun/test/graph/operation/SetIO.cc
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+/*
+ * Copyright (c) 2018 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 <gtest/gtest.h>
+
+#include "ir/Graph.h"
+#include "ir/Index.h"
+#include "ir/OperandIndexSequence.h"
+#include "ir/operation/Conv2D.h"
+#include "ir/operation/Concat.h"
+
+#include <cpp14/memory.h>
+
+#include <stdexcept>
+
+using Index = neurun::ir::IOIndex;
+using IndexSet = neurun::ir::OperandIndexSequence;
+
+TEST(graph_operation_setIO, operation_setIO_conv)
+{
+ neurun::ir::Graph graph;
+
+ neurun::ir::Shape shape{3};
+ neurun::ir::TypeInfo type{neurun::ir::DataType::INT32};
+
+ // Add Conv
+ using Graph = neurun::ir::operation::Conv2D;
+
+ auto input_operand = graph.addOperand(shape, type);
+ auto kernel_operand = graph.addOperand(shape, type);
+ auto bias_operand = graph.addOperand(shape, type);
+ IndexSet inputs{input_operand, kernel_operand, bias_operand};
+
+ Graph::Param conv_params;
+ conv_params.padding.type = neurun::ir::PaddingType::SAME;
+ conv_params.stride.horizontal = 1;
+ conv_params.stride.vertical = 1;
+ conv_params.activation = neurun::ir::Activation::NONE;
+
+ auto output_operand = graph.addOperand(shape, type).value();
+ IndexSet outputs{output_operand};
+
+ auto conv = nnfw::cpp14::make_unique<Graph>(inputs, outputs, conv_params);
+
+ ASSERT_NE(conv, nullptr);
+ ASSERT_EQ(conv->getInputs().at(Index{0}).value(), inputs.at(0).value());
+ conv->setInputs({8, 9, 10});
+ ASSERT_NE(conv->getInputs().at(Index{0}).value(), inputs.at(0).value());
+ ASSERT_EQ(conv->getInputs().at(Index{0}).value(), 8);
+}
+
+TEST(graph_operation_setIO, operation_setIO_concat)
+{
+ neurun::ir::Graph graph;
+
+ neurun::ir::Shape shape{3};
+
+ neurun::ir::TypeInfo type{neurun::ir::DataType::INT32};
+
+ using Graph = neurun::ir::operation::Concat;
+
+ // Add Concat
+ IndexSet inputs;
+ for (int i = 0; i < 6; ++i)
+ {
+ inputs.append(graph.addOperand(shape, type));
+ }
+
+ Graph::Param concat_params{0};
+
+ auto output_operand = graph.addOperand(shape, type).value();
+ IndexSet outputs{output_operand};
+
+ auto concat = nnfw::cpp14::make_unique<Graph>(inputs, outputs, concat_params);
+
+ ASSERT_NE(concat, nullptr);
+ ASSERT_EQ(concat->getInputs().size(), 6);
+ ASSERT_EQ(concat->getInputs().at(Index{0}).value(), inputs.at(0).value());
+
+ concat->setInputs({80, 6, 9, 11});
+ ASSERT_EQ(concat->getInputs().size(), 4);
+ ASSERT_NE(concat->getInputs().at(Index{0}).value(), inputs.at(0).value());
+ ASSERT_EQ(concat->getInputs().at(Index{0}).value(), 80);
+ ASSERT_EQ(concat->getInputs().at(Index{2}).value(), 9);
+ ASSERT_THROW(concat->getInputs().at(Index{5}), std::out_of_range);
+}