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Add int16 support to PACK/UNPACK #2737

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Add int16 support to PACK/UNPACK #2737

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49e4a08
Add int16 support to PACK
andresovela Oct 29, 2024
8052aa2
Add int16 support to UNPACK
andresovela Oct 29, 2024
877e0f0
Fix formatting
andresovela Oct 29, 2024
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4 changes: 4 additions & 0 deletions tensorflow/lite/micro/kernels/pack.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -85,6 +85,10 @@ TfLiteStatus PackEval(TfLiteContext* context, TfLiteNode* node) {
return PackImpl<int8_t>(context, node, output, data->values_count,
data->axis);
}
case kTfLiteInt16: {
return PackImpl<int16_t>(context, node, output, data->values_count,
data->axis);
}
case kTfLiteInt32: {
return PackImpl<int32_t>(context, node, output, data->values_count,
data->axis);
Expand Down
68 changes: 25 additions & 43 deletions tensorflow/lite/micro/kernels/pack_test.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -110,44 +110,11 @@ void TestPackThreeInputsFloat(int* input1_dims_data, const float* input1_data,
1e-5f, output_data);
}

void TestPackTwoInputsQuantized(
int* input1_dims_data, const int8_t* input1_data, int* input2_dims_data,
const int8_t* input2_data, int axis, int* output_dims_data,
const int8_t* expected_output_data, int8_t* output_data) {
TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data);
TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data);
TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);
const int output_dims_count = ElementCount(*output_dims);

constexpr int input_size = 2;
constexpr int output_size = 1;
constexpr int tensors_size = input_size + output_size;
TfLiteTensor tensors[tensors_size] = {
// CreateQuantizedTensor needs scale/zero_point values as input, but these
// values don't matter as to the functionality of PACK, so just set as 1.0
// and 128.
CreateQuantizedTensor(input1_data, input1_dims, 1.0, 128),
CreateQuantizedTensor(input2_data, input2_dims, 1.0, 128),
CreateQuantizedTensor(output_data, output_dims, 1.0, 128)};

TfLitePackParams builtin_data = {
.values_count = 2,
.axis = axis,
};
int inputs_array_data[] = {2, 0, 1};
TfLiteIntArray* inputs_array = IntArrayFromInts(inputs_array_data);
int outputs_array_data[] = {1, 2};
TfLiteIntArray* outputs_array = IntArrayFromInts(outputs_array_data);

ValidatePackGoldens(tensors, tensors_size, builtin_data, inputs_array,
outputs_array, expected_output_data, output_dims_count,
1e-5f, output_data);
}

void TestPackTwoInputsQuantized32(
int* input1_dims_data, const int32_t* input1_data, int* input2_dims_data,
const int32_t* input2_data, int axis, int* output_dims_data,
const int32_t* expected_output_data, int32_t* output_data) {
template <typename T>
void TestPackTwoInputsQuantized(int* input1_dims_data, const T* input1_data,
int* input2_dims_data, const T* input2_data,
int axis, int* output_dims_data,
const T* expected_output_data, T* output_data) {
TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data);
TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data);
TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);
Expand Down Expand Up @@ -227,7 +194,7 @@ TF_LITE_MICRO_TEST(PackFloatThreeInputsNegativeAxis) {
input3_values, axis, output_shape, golden, output_data);
}

TF_LITE_MICRO_TEST(PackFloatMultilDimensions) {
TF_LITE_MICRO_TEST(PackFloatMultiDimensions) {
int input_shape[] = {2, 2, 3};
int output_shape[] = {3, 2, 2, 3};
const float input1_values[] = {1, 2, 3, 4, 5, 6};
Expand All @@ -242,7 +209,7 @@ TF_LITE_MICRO_TEST(PackFloatMultilDimensions) {
output_shape, golden, output_data);
}

TF_LITE_MICRO_TEST(PackQuantizedMultilDimensions) {
TF_LITE_MICRO_TEST(PackQuantizedInt8MultiDimensions) {
int input_shape[] = {2, 2, 3};
int output_shape[] = {3, 2, 2, 3};
const int8_t input1_values[] = {1, 2, 3, 4, 5, 6};
Expand All @@ -252,12 +219,27 @@ TF_LITE_MICRO_TEST(PackQuantizedMultilDimensions) {
constexpr int output_dims_count = 12;
int8_t output_data[output_dims_count];

tflite::testing::TestPackTwoInputsQuantized(
tflite::testing::TestPackTwoInputsQuantized<int8_t>(
input_shape, input1_values, input_shape, input2_values, axis,
output_shape, golden, output_data);
}

TF_LITE_MICRO_TEST(PackQuantizedInt16MultiDimensions) {
int input_shape[] = {2, 2, 3};
int output_shape[] = {3, 2, 2, 3};
const int16_t input1_values[] = {1, 2, 3, 4, 5, 6};
const int16_t input2_values[] = {7, 8, 9, 10, 11, 12};
const int16_t golden[] = {1, 2, 3, 7, 8, 9, 4, 5, 6, 10, 11, 12};
const int axis = 1;
constexpr int output_dims_count = 12;
int16_t output_data[output_dims_count];

tflite::testing::TestPackTwoInputsQuantized<int16_t>(
input_shape, input1_values, input_shape, input2_values, axis,
output_shape, golden, output_data);
}

TF_LITE_MICRO_TEST(PackQuantized32MultilDimensions) {
TF_LITE_MICRO_TEST(PackQuantizedInt32MultiDimensions) {
int input_shape[] = {2, 2, 3};
int output_shape[] = {3, 2, 2, 3};
const int32_t input1_values[] = {1, 2, 3, 4, 5, 6};
Expand All @@ -267,7 +249,7 @@ TF_LITE_MICRO_TEST(PackQuantized32MultilDimensions) {
constexpr int output_dims_count = 12;
int32_t output_data[output_dims_count];

tflite::testing::TestPackTwoInputsQuantized32(
tflite::testing::TestPackTwoInputsQuantized<int32_t>(
input_shape, input1_values, input_shape, input2_values, axis,
output_shape, golden, output_data);
}
Expand Down
3 changes: 3 additions & 0 deletions tensorflow/lite/micro/kernels/unpack.cc
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Expand Up @@ -86,6 +86,9 @@ TfLiteStatus UnpackEval(TfLiteContext* context, TfLiteNode* node) {
case kTfLiteInt32: {
return UnpackImpl<int32_t>(context, node, input, data->num, data->axis);
}
case kTfLiteInt16: {
return UnpackImpl<int16_t>(context, node, input, data->num, data->axis);
}
case kTfLiteInt8: {
return UnpackImpl<int8_t>(context, node, input, data->num, data->axis);
}
Expand Down
38 changes: 30 additions & 8 deletions tensorflow/lite/micro/kernels/unpack_test.cc
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Expand Up @@ -132,12 +132,13 @@ void TestUnpackOneOutputFloat(int* input_dims_data, const float* input_data,
}
}

void TestUnpackThreeOutputsQuantized32(
int* input_dims_data, const int32_t* input_data, int axis,
int* output1_dims_data, const int32_t* expected_output1_data,
int* output2_dims_data, const int32_t* expected_output2_data,
int* output3_dims_data, const int32_t* expected_output3_data,
int32_t* output1_data, int32_t* output2_data, int32_t* output3_data) {
template <typename T>
void TestUnpackThreeOutputsQuantized(
int* input_dims_data, const T* input_data, int axis, int* output1_dims_data,
const T* expected_output1_data, int* output2_dims_data,
const T* expected_output2_data, int* output3_dims_data,
const T* expected_output3_data, T* output1_data, T* output2_data,
T* output3_data) {
TfLiteIntArray* input_dims = IntArrayFromInts(input_dims_data);
TfLiteIntArray* output1_dims = IntArrayFromInts(output1_dims_data);
TfLiteIntArray* output2_dims = IntArrayFromInts(output2_dims_data);
Expand Down Expand Up @@ -257,7 +258,28 @@ TF_LITE_MICRO_TEST(UnpackFloatOneOutput) {
output_shape, golden, output_data);
}

TF_LITE_MICRO_TEST(UnpackQuantized32ThreeOutputs) {
TF_LITE_MICRO_TEST(UnpackQuantizedInt16ThreeOutputs) {
int input_shape[] = {2, 3, 2};
const int16_t input_values[] = {1, 2, 3, 4, 5, 6};
int output1_shape[] = {1, 2};
const int16_t output1_golden[] = {1, 2};
int output2_shape[] = {1, 2};
const int16_t output2_golden[] = {3, 4};
int output3_shape[] = {1, 2};
const int16_t output3_golden[] = {5, 6};
constexpr int output1_dims_count = 2;
constexpr int output2_dims_count = 2;
constexpr int output3_dims_count = 2;
int16_t output1_data[output1_dims_count];
int16_t output2_data[output2_dims_count];
int16_t output3_data[output3_dims_count];
tflite::testing::TestUnpackThreeOutputsQuantized<int16_t>(
input_shape, input_values, 0, output1_shape, output1_golden,
output2_shape, output2_golden, output3_shape, output3_golden,
output1_data, output2_data, output3_data);
}

TF_LITE_MICRO_TEST(UnpackQuantizedInt32ThreeOutputs) {
int input_shape[] = {2, 3, 2};
const int32_t input_values[] = {1, 2, 3, 4, 5, 6};
int output1_shape[] = {1, 2};
Expand All @@ -272,7 +294,7 @@ TF_LITE_MICRO_TEST(UnpackQuantized32ThreeOutputs) {
int32_t output1_data[output1_dims_count];
int32_t output2_data[output2_dims_count];
int32_t output3_data[output3_dims_count];
tflite::testing::TestUnpackThreeOutputsQuantized32(
tflite::testing::TestUnpackThreeOutputsQuantized<int32_t>(
input_shape, input_values, 0, output1_shape, output1_golden,
output2_shape, output2_golden, output3_shape, output3_golden,
output1_data, output2_data, output3_data);
Expand Down
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