1 files changed, 123 insertions, 0 deletions
diff --git a/compiler/luci/pass/src/QuantizeWeightsPass.test.cpp b/compiler/luci/pass/src/QuantizeWeightsPass.test.cpp
new file mode 100644
index 000000000..058e029ab
--- /dev/null
+++ b/compiler/luci/pass/src/QuantizeWeightsPass.test.cpp
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+/*
+ * Copyright (c) 2023 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 "luci/Pass/QuantizeWeightsPass.h"
+#include <luci/IR/CircleNodes.h>
+
+#include <gtest/gtest.h>
+
+namespace
+{
+struct QuantizeWeightsPassTest : public ::testing::Test
+{
+  /**
+   *  nconv graph
+   *
+   *        [CircleInput]
+   *              |
+   *              |
+   *        [CircleConv2D]
+   *              |
+   *              |
+   *        [CircleOutput]
+   */
+  void MakeGraph()
+  {
+    const int N = 1;
+    const int H = 4;
+    const int W = 4;
+    const int C = 3; // IC = OC
+
+    // graph input and output
+    auto graph_input = _g.inputs()->create();
+    auto graph_output = _g.outputs()->create();
+
+    // CircleInput
+    auto input = _g.nodes()->create<luci::CircleInput>();
+    input->index(graph_input->index());
+    input->shape({N, H, W, C});
+    input->dtype(loco::DataType::FLOAT32);
+    input->name("input");
+
+    // CircleConv2D
+    auto conv = _g.nodes()->create<luci::CircleConv2D>();
+    conv->input(input);
+    auto bias = _g.nodes()->create<luci::CircleConst>();
+    bias->dtype(loco::DataType::FLOAT32);
+    bias->shape({C});
+    bias->name("conv_bias");
+    conv->bias(bias);
+    auto weight = _g.nodes()->create<luci::CircleConst>();
+    weight->dtype(loco::DataType::FLOAT32);
+    weight->shape({C, H, W, C});
+    weight->size<loco::DataType::FLOAT32>(C * H * W * C);
+    conv->filter(weight);
+    conv->padding(luci::Padding::SAME);
+    conv->fusedActivationFunction(luci::FusedActFunc::NONE);
+    conv->dtype(loco::DataType::FLOAT32);
+    conv->name("nconv");
+
+    // CircleOutput
+    auto output = _g.nodes()->create<luci::CircleOutput>();
+    output->index(graph_output->index());
+    output->from(conv);
+    output->shape({N, H, W, C});
+    output->dtype(loco::DataType::FLOAT32);
+    output->name("output");
+  }
+  virtual void SetUp() { MakeGraph(); }
+  loco::Graph _g;
+};
+
+} // namespace
+
+TEST_F(QuantizeWeightsPassTest, name)
+{
+  luci::QuantizeWeightsPass pass(loco::DataType::FLOAT32, loco::DataType::S8,
+                                 luci::QuantizationGranularity::ChannelWise);
+  auto const name = pass.name();
+  ASSERT_NE(nullptr, name);
+}
+
+TEST_F(QuantizeWeightsPassTest, name_ctx)
+{
+  auto ctx = std::make_unique<luci::QuantizeWeightsPass::Context>();
+  {
+    ctx->input_model_dtype = loco::DataType::FLOAT32;
+    ctx->output_model_dtype = loco::DataType::S8;
+    ctx->granularity = luci::QuantizationGranularity::ChannelWise;
+  }
+
+  luci::QuantizeWeightsPass pass(std::move(ctx));
+  auto const name = pass.name();
+  ASSERT_NE(nullptr, name);
+}
+
+TEST_F(QuantizeWeightsPassTest, run_input_U8_NEG)
+{
+  loco::Graph g;
+  luci::QuantizeWeightsPass pass(loco::DataType::U8, loco::DataType::S8,
+                                 luci::QuantizationGranularity::ChannelWise);
+  EXPECT_THROW(pass.run(&_g), std::runtime_error);
+}
+
+TEST_F(QuantizeWeightsPassTest, run_output_f32_NEG)
+{
+  loco::Graph g;
+  luci::QuantizeWeightsPass pass(loco::DataType::FLOAT32, loco::DataType::FLOAT32,
+                                 luci::QuantizationGranularity::ChannelWise);
+  EXPECT_THROW(pass.run(&_g), std::runtime_error);
+}