kernel test for GRU

Samsung · Oct 25, 2024 · a354856 · a354856
1 parent 3370ae6
commit a354856
Showing 1 changed file with 129 additions and 1 deletion.
diff --git a/compiler/luci-interpreter/src/kernels/GRU.test.cpp b/compiler/luci-interpreter/src/kernels/GRU.test.cpp
@@ -35,7 +35,135 @@ class GRUTest : public ::testing::Test
   std::unique_ptr<IMemoryManager> _memory_manager;
 };
 
-TEST_F(GRUTest, floatTest) { SUCCEED(); }
+TEST_F(GRUTest, floatTest)
+{
+  Shape input_shape{2, 1, 2};
+  std::vector<float> input_data{0.98045033, 0.39546537, 0.5209594, 0.72873044};
+
+  Shape ref_output_shape{1, 1, 2};
+  std::vector<float> ref_output_data{0.22777566, -0.1976251};
+
+  Shape hidden_hidden_shape{6, 2};
+  std::vector<float> hidden_hidden_data{
+    0.8073279857635498,   -0.5218740105628967, 0.1166749969124794,  0.33110499382019043,
+    0.2770330011844635,   0.23767800629138947, 0.1293960064649582,  0.17175200581550598,
+    -0.15584999322891235, 0.8137810230255127,  -0.2667199969291687, -0.23028500378131866};
+  Shape hidden_input_shape{6, 2};
+  std::vector<float> hidden_input_data{
+    -0.1928129941225052, -0.4582270085811615, -0.17884500324726105, -0.27543601393699646,
+    0.704787015914917,   0.1874309927225113,  -0.28071099519729614, -0.40605801343917847,
+    -0.4156219959259033, 0.6752780079841614,  0.4272859990596771,   -0.24114100635051727};
+
+  Shape state_shape{1, 2};
+  std::vector<float> state_data{0.0, 0.0};
+
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Tensor hidden_hidden_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_hidden_shape, hidden_hidden_data, _memory_manager.get());
+
+  Tensor hidden_input_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_input_shape, hidden_input_data, _memory_manager.get());
+
+  Tensor state_tensor =
+    makeInputTensor<DataType::FLOAT32>(state_shape, state_data, _memory_manager.get());
+
+  GRUParams params{};
+
+  GRU kernel(&input_tensor, &hidden_hidden_tensor, nullptr, &hidden_input_tensor, nullptr,
+             &state_tensor, &output_tensor, params);
+  kernel.configure();
+  _memory_manager->allocate_memory(output_tensor);
+  kernel.execute();
+
+  EXPECT_THAT(extractTensorData<float>(output_tensor),
+              ::testing::ElementsAreArray(ref_output_data));
+}
+
+TEST_F(GRUTest, Unmatched_io_type_NEG)
+{
+  Shape input_shape{2, 1, 2};
+  std::vector<float> input_data{0.98045033, 0.39546537, 0.5209594, 0.72873044};
+
+  Shape ref_output_shape{1, 1, 2};
+  std::vector<float> ref_output_data{0.22777566, -0.1976251};
+
+  Shape hidden_hidden_shape{6, 2};
+  std::vector<float> hidden_hidden_data{
+    0.8073279857635498,   -0.5218740105628967, 0.1166749969124794,  0.33110499382019043,
+    0.2770330011844635,   0.23767800629138947, 0.1293960064649582,  0.17175200581550598,
+    -0.15584999322891235, 0.8137810230255127,  -0.2667199969291687, -0.23028500378131866};
+  Shape hidden_input_shape{6, 2};
+  std::vector<float> hidden_input_data{
+    -0.1928129941225052, -0.4582270085811615, -0.17884500324726105, -0.27543601393699646,
+    0.704787015914917,   0.1874309927225113,  -0.28071099519729614, -0.40605801343917847,
+    -0.4156219959259033, 0.6752780079841614,  0.4272859990596771,   -0.24114100635051727};
+
+  Shape state_shape{1, 2};
+  std::vector<float> state_data{0.0, 0.0};
+
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::U32);
+
+  Tensor hidden_hidden_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_hidden_shape, hidden_hidden_data, _memory_manager.get());
+
+  Tensor hidden_input_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_input_shape, hidden_input_data, _memory_manager.get());
+
+  Tensor state_tensor =
+    makeInputTensor<DataType::FLOAT32>(state_shape, state_data, _memory_manager.get());
+
+  GRUParams params{};
+
+  GRU kernel(&input_tensor, &hidden_hidden_tensor, nullptr, &hidden_input_tensor, nullptr,
+             &state_tensor, &output_tensor, params);
+
+  EXPECT_ANY_THROW(kernel.configure());
+}
+
+TEST_F(GRUTest, Unmatched_weight_size_NEG)
+{
+  Shape input_shape{2, 1, 2};
+  std::vector<float> input_data{0.98045033, 0.39546537, 0.5209594, 0.72873044};
+
+  Shape ref_output_shape{1, 1, 2};
+  std::vector<float> ref_output_data{0.22777566, -0.1976251};
+
+  Shape hidden_hidden_shape{1, 2};
+  std::vector<float> hidden_hidden_data{-0.2667199969291687, -0.23028500378131866};
+  Shape hidden_input_shape{6, 2};
+  std::vector<float> hidden_input_data{
+    -0.1928129941225052, -0.4582270085811615, -0.17884500324726105, -0.27543601393699646,
+    0.704787015914917,   0.1874309927225113,  -0.28071099519729614, -0.40605801343917847,
+    -0.4156219959259033, 0.6752780079841614,  0.4272859990596771,   -0.24114100635051727};
+
+  Shape state_shape{1, 2};
+  std::vector<float> state_data{0.0, 0.0};
+
+  Tensor input_tensor =
+    makeInputTensor<DataType::FLOAT32>(input_shape, input_data, _memory_manager.get());
+  Tensor output_tensor = makeOutputTensor(DataType::FLOAT32);
+
+  Tensor hidden_hidden_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_hidden_shape, hidden_hidden_data, _memory_manager.get());
+
+  Tensor hidden_input_tensor = makeInputTensor<DataType::FLOAT32>(
+    hidden_input_shape, hidden_input_data, _memory_manager.get());
+
+  Tensor state_tensor =
+    makeInputTensor<DataType::FLOAT32>(state_shape, state_data, _memory_manager.get());
+
+  GRUParams params{};
+
+  GRU kernel(&input_tensor, &hidden_hidden_tensor, nullptr, &hidden_input_tensor, nullptr,
+             &state_tensor, &output_tensor, params);
+
+  EXPECT_ANY_THROW(kernel.configure());
+}
 
 } // namespace
 } // namespace kernels