MLECO-3611: Formatting fixes for generated files.
Template files updated for generated files to adhere to
coding guidelines and clang format configuration. There
will still be unavoidable violations, but most of the
others have been fixed.
Change-Id: Ia03db40f8c62a369f2b07fe02eea65e41993a523
Signed-off-by: Kshitij Sisodia <kshitij.sisodia@arm.com>
diff --git a/tests/use_case/noise_reduction/InferenceTestRNNoise.cc b/tests/use_case/noise_reduction/InferenceTestRNNoise.cc
index 3cdaee1..17ce9ac 100644
--- a/tests/use_case/noise_reduction/InferenceTestRNNoise.cc
+++ b/tests/use_case/noise_reduction/InferenceTestRNNoise.cc
@@ -1,6 +1,6 @@
/*
- * SPDX-FileCopyrightText: Copyright 2021 Arm Limited and/or its affiliates <open-source-office@arm.com>
- * SPDX-License-Identifier: Apache-2.0
+ * SPDX-FileCopyrightText: Copyright 2021 Arm Limited and/or its affiliates
+ * <open-source-office@arm.com> SPDX-License-Identifier: Apache-2.0
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
@@ -14,10 +14,10 @@
* See the License for the specific language governing permissions and
* limitations under the License.
*/
-#include "TensorFlowLiteMicro.hpp"
-#include "RNNoiseModel.hpp"
-#include "TestData_noise_reduction.hpp"
#include "BufAttributes.hpp"
+#include "RNNoiseModel.hpp"
+#include "TensorFlowLiteMicro.hpp"
+#include "TestData_noise_reduction.hpp"
#include <catch.hpp>
#include <random>
@@ -50,15 +50,13 @@
{
std::random_device rndDevice;
std::mt19937 mersenneGen{rndDevice()};
- std::uniform_int_distribution<short> dist {-128, 127};
+ std::uniform_int_distribution<short> dist{-128, 127};
- auto gen = [&dist, &mersenneGen](){
- return dist(mersenneGen);
- };
+ auto gen = [&dist, &mersenneGen]() { return dist(mersenneGen); };
std::vector<std::vector<int8_t>> randomInput{NUMBER_OF_IFM_FILES};
for (size_t i = 0; i < model.GetNumInputs(); ++i) {
- TfLiteTensor *inputTensor = model.GetInputTensor(i);
+ TfLiteTensor* inputTensor = model.GetInputTensor(i);
REQUIRE(inputTensor);
randomInput[i].resize(inputTensor->bytes);
std::generate(std::begin(randomInput[i]), std::end(randomInput[i]), gen);
@@ -82,8 +80,10 @@
REQUIRE(RunInferenceRandom(model));
}
- template<typename T>
- void TestInference(const std::vector<std::vector<T>> input_goldenFV, const std::vector<std::vector<T>> output_goldenFV, arm::app::Model& model)
+ template <typename T>
+ void TestInference(const std::vector<std::vector<T>> input_goldenFV,
+ const std::vector<std::vector<T>> output_goldenFV,
+ arm::app::Model& model)
{
for (size_t i = 0; i < model.GetNumInputs(); ++i) {
TfLiteTensor* inputTensor = model.GetInputTensor(i);
@@ -93,41 +93,37 @@
REQUIRE(RunInference(model, input_goldenFV));
for (size_t i = 0; i < model.GetNumOutputs(); ++i) {
- TfLiteTensor *outputTensor = model.GetOutputTensor(i);
+ TfLiteTensor* outputTensor = model.GetOutputTensor(i);
REQUIRE(outputTensor);
auto tensorData = tflite::GetTensorData<T>(outputTensor);
REQUIRE(tensorData);
for (size_t j = 0; j < outputTensor->bytes; j++) {
- REQUIRE(static_cast<int>(tensorData[j]) == static_cast<int>((output_goldenFV[i][j])));
+ REQUIRE(static_cast<int>(tensorData[j]) ==
+ static_cast<int>((output_goldenFV[i][j])));
}
}
}
TEST_CASE("Running inference with Tflu and RNNoise Int8", "[RNNoise]")
{
- std::vector<std::vector<int8_t>> goldenInputFV {NUMBER_OF_IFM_FILES};
- std::vector<std::vector<int8_t>> goldenOutputFV {NUMBER_OF_OFM_FILES};
+ std::vector<std::vector<int8_t>> goldenInputFV{NUMBER_OF_IFM_FILES};
+ std::vector<std::vector<int8_t>> goldenOutputFV{NUMBER_OF_OFM_FILES};
- std::array<size_t, NUMBER_OF_IFM_FILES> inputSizes = {IFM_0_DATA_SIZE,
- IFM_1_DATA_SIZE,
- IFM_2_DATA_SIZE,
- IFM_3_DATA_SIZE};
+ std::array<size_t, NUMBER_OF_IFM_FILES> inputSizes = {
+ IFM_0_DATA_SIZE, IFM_1_DATA_SIZE, IFM_2_DATA_SIZE, IFM_3_DATA_SIZE};
- std::array<size_t, NUMBER_OF_OFM_FILES> outputSizes = {OFM_0_DATA_SIZE,
- OFM_1_DATA_SIZE,
- OFM_2_DATA_SIZE,
- OFM_3_DATA_SIZE,
- OFM_4_DATA_SIZE};
+ std::array<size_t, NUMBER_OF_OFM_FILES> outputSizes = {
+ OFM_0_DATA_SIZE, OFM_1_DATA_SIZE, OFM_2_DATA_SIZE, OFM_3_DATA_SIZE, OFM_4_DATA_SIZE};
- for (uint32_t i = 0 ; i < NUMBER_OF_IFM_FILES; ++i) {
+ for (uint32_t i = 0; i < NUMBER_OF_IFM_FILES; ++i) {
goldenInputFV[i].resize(inputSizes[i]);
- std::memcpy(goldenInputFV[i].data(), get_ifm_data_array(i), inputSizes[i]);
+ std::memcpy(goldenInputFV[i].data(), GetIfmDataArray(i), inputSizes[i]);
}
- for (uint32_t i = 0 ; i < NUMBER_OF_OFM_FILES; ++i) {
+ for (uint32_t i = 0; i < NUMBER_OF_OFM_FILES; ++i) {
goldenOutputFV[i].resize(outputSizes[i]);
- std::memcpy(goldenOutputFV[i].data(), get_ofm_data_array(i), outputSizes[i]);
+ std::memcpy(goldenOutputFV[i].data(), GetOfmDataArray(i), outputSizes[i]);
}
DYNAMIC_SECTION("Executing inference with re-init")
@@ -146,4 +142,4 @@
}
} /* namespace noise_reduction */
-} /* namespace test */
+} /* namespace test */