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[Clean-up] Clang-format some existing files #3179

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[Clean-up] Clang-format some existing files #3179

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18 changes: 9 additions & 9 deletions signal/micro/kernels/stacker_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -32,15 +32,15 @@ class StackerKernelRunner {
StackerKernelRunner(int* input_dims_data, const int16_t* input_data,
int* output_dims_data, int16_t* output_data,
int* output_ready_dims_data, bool* ouput_ready_data)
: tensors_{testing::CreateTensor(
input_data,
tflite::testing::IntArrayFromInts(input_dims_data)),
testing::CreateTensor(
output_data,
tflite::testing::IntArrayFromInts(output_dims_data)),
testing::CreateTensor(
ouput_ready_data,
testing::IntArrayFromInts(output_ready_dims_data))},
: tensors_{
testing::CreateTensor(
input_data, tflite::testing::IntArrayFromInts(input_dims_data)),
testing::CreateTensor(
output_data,
tflite::testing::IntArrayFromInts(output_dims_data)),
testing::CreateTensor(
ouput_ready_data,
testing::IntArrayFromInts(output_ready_dims_data))},
inputs_array_{testing::IntArrayFromInts(inputs_array_data_)},
outputs_array_{testing::IntArrayFromInts(outputs_array_data_)},
kernel_runner_{*registration_, tensors_, kTensorsSize,
Expand Down
4 changes: 2 additions & 2 deletions tensorflow/compiler/mlir/lite/schema/schema_utils.h
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Expand Up @@ -24,9 +24,9 @@ namespace tflite {
// problem. The new builtin operator will be assigned to the extended builtin
// code field in the flatbuffer schema. Those methods helps to hide builtin code
// details.
BuiltinOperator GetBuiltinCode(const OperatorCode *op_code);
BuiltinOperator GetBuiltinCode(const OperatorCode* op_code);

BuiltinOperator GetBuiltinCode(const OperatorCodeT *op_code);
BuiltinOperator GetBuiltinCode(const OperatorCodeT* op_code);

} // namespace tflite

Expand Down
34 changes: 20 additions & 14 deletions tensorflow/lite/experimental/microfrontend/lib/filterbank_test.cc
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Expand Up @@ -76,8 +76,9 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckChannelFrequencyStarts) {
kSampleRate, kSpectrumSize));

const int16_t expected[] = {0, 4, 8};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i <= state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.channel_frequency_starts[i], expected[i]);
Expand All @@ -93,8 +94,9 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckChannelWeightStarts) {
kSampleRate, kSpectrumSize));

const int16_t expected[] = {0, 8, 16};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i <= state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.channel_weight_starts[i], expected[i]);
Expand All @@ -110,8 +112,9 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckChannelWidths) {
kSampleRate, kSpectrumSize));

const int16_t expected[] = {8, 8, 8};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels + 1,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i <= state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.channel_widths[i], expected[i]);
Expand All @@ -129,9 +132,10 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckWeights) {
const int16_t expected[] = {0, 3277, 2217, 1200, 222, 0, 0, 0,
0, 3376, 2468, 1591, 744, 0, 0, 0,
0, 4020, 3226, 2456, 1708, 983, 277, 0};
TF_LITE_MICRO_EXPECT_EQ(state.channel_weight_starts[state.num_channels] +
state.channel_widths[state.num_channels],
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.channel_weight_starts[state.num_channels] +
state.channel_widths[state.num_channels],
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
for (size_t i = 0; i < sizeof(expected) / sizeof(expected[0]); ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.weights[i], expected[i]);
}
Expand All @@ -148,9 +152,10 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckUnweights) {
const int16_t expected[] = {0, 819, 1879, 2896, 3874, 0, 0, 0,
0, 720, 1628, 2505, 3352, 0, 0, 0,
0, 76, 870, 1640, 2388, 3113, 3819, 0};
TF_LITE_MICRO_EXPECT_EQ(state.channel_weight_starts[state.num_channels] +
state.channel_widths[state.num_channels],
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.channel_weight_starts[state.num_channels] +
state.channel_widths[state.num_channels],
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
for (size_t i = 0; i < sizeof(expected) / sizeof(expected[0]); ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.unweights[i], expected[i]);
}
Expand Down Expand Up @@ -204,8 +209,9 @@ TF_LITE_MICRO_TEST(FilterbankTest_CheckSqrt) {
uint32_t* scaled_filterbank = FilterbankSqrt(&state, kScaleShift);

const uint32_t expected[] = {247311, 508620};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i < state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(scaled_filterbank[i], expected[i]);
Expand Down
10 changes: 6 additions & 4 deletions tensorflow/lite/experimental/microfrontend/lib/noise_reduction_test.cc
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Expand Up @@ -48,8 +48,9 @@ TF_LITE_MICRO_TEST(NoiseReductionTest_TestNoiseReductionEstimate) {
NoiseReductionApply(&state, signal);

const uint32_t expected[] = {6321887, 31248341};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i < state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(state.estimate[i], expected[i]);
Expand All @@ -68,8 +69,9 @@ TF_LITE_MICRO_TEST(NoiseReductionTest_TestNoiseReduction) {
NoiseReductionApply(&state, signal);

const uint32_t expected[] = {241137, 478104};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i < state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(signal[i], expected[i]);
Expand Down
5 changes: 3 additions & 2 deletions tensorflow/lite/experimental/microfrontend/lib/pcan_gain_control_test.cc
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Expand Up @@ -52,8 +52,9 @@ TF_LITE_MICRO_TEST(PcanGainControlTest_TestPcanGainControl) {
PcanGainControlApply(&state, signal);

const uint32_t expected[] = {3578, 1533};
TF_LITE_MICRO_EXPECT_EQ(state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
TF_LITE_MICRO_EXPECT_EQ(
state.num_channels,
static_cast<int>(sizeof(expected) / sizeof(expected[0])));
int i;
for (i = 0; i < state.num_channels; ++i) {
TF_LITE_MICRO_EXPECT_EQ(signal[i], expected[i]);
Expand Down
1 change: 0 additions & 1 deletion tensorflow/lite/kernels/internal/reference/integer_ops/conv.h
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Expand Up @@ -135,7 +135,6 @@ inline void ConvPerChannel(
}
}


// Fixed-point per-channel-quantization convolution reference kernel.
// 16-bit data and 8-bit filter
template <typename AccumScalar>
Expand Down
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