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Merged
merged 17 commits into from
Mar 17, 2025
Merged

Add 16bit support for unpack, transpose and comparisons operators #3028

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5e0b839
Add 16bit support for unpack, transpose and comparisons operators
rameshkunasi Dec 24, 2024
611d82b
Added support for FC16x8 per channel quantization
rameshkunasi Dec 24, 2024
6d6e3ee
indentation correction
rameshkunasi Jan 9, 2025
733e523
indentation correction
rameshkunasi Jan 9, 2025
2ce81e8
indentation correction
rameshkunasi Jan 27, 2025
b1f00e7
Merge branch 'main' into main
suleshahid Feb 10, 2025
fe90463
Added unit tests for transpose, greater and fully_connected per chann…
rameshkunasi Mar 13, 2025
31a2318
Indentations and function name changes
rameshkunasi Mar 13, 2025
33d617b
Merge branch 'main' of github.com:rameshkunasi/tflite-micro
rameshkunasi Mar 13, 2025
529d8fe
Merge branch 'main' into main
rameshkunasi Mar 13, 2025
d4db629
Revert "Indentations and function name changes"
rameshkunasi Mar 13, 2025
fae534c
clean up
rameshkunasi Mar 13, 2025
6c37801
modified as per the suggested changes
rameshkunasi Mar 14, 2025
615c34a
Resolved unused variable error for xtensa
rameshkunasi Mar 14, 2025
2393651
Removed CMSIS_NN not supported flag in FC INT8 per channel quantizati…
rameshkunasi Mar 14, 2025
ae015fa
Moved FC Per channel INT8 quantization unit test under not supported …
rameshkunasi Mar 15, 2025
e890dbe
Fixed formatting error and compilation error for HEXAGON platform
rameshkunasi Mar 16, 2025
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15 changes: 14 additions & 1 deletion tensorflow/lite/micro/kernels/comparisons.cc
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
/* Copyright 2025 The TensorFlow Authors. 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.
Expand Down Expand Up @@ -286,6 +286,19 @@ TfLiteStatus GreaterEval(TfLiteContext* context, TfLiteNode* node) {
tflite::micro::GetTensorData<int8_t>(input2), output_shape,
output_data);
break;
case kTfLiteInt16:
requires_broadcast
? reference_ops::Broadcast4DSlowGreaterWithScaling(
data->params, input1_shape,
tflite::micro::GetTensorData<int16_t>(input1), input2_shape,
tflite::micro::GetTensorData<int16_t>(input2), output_shape,
output_data)
: reference_ops::GreaterWithScaling(
data->params, input1_shape,
tflite::micro::GetTensorData<int16_t>(input1), input2_shape,
tflite::micro::GetTensorData<int16_t>(input2), output_shape,
output_data);
break;
default:
MicroPrintf("Type %s (%d) not supported.",
TfLiteTypeGetName(input1->type), input1->type);
Expand Down
54 changes: 53 additions & 1 deletion tensorflow/lite/micro/kernels/comparisons_test.cc
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
/* Copyright 2023 The TensorFlow Authors. All Rights Reserved.
/* Copyright 2025 The TensorFlow Authors. 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.
Expand Down Expand Up @@ -126,6 +126,29 @@ void TestComparisonQuantizedInt8(const TFLMRegistration& registration,
TestComparison(registration, tensors, expected_output_data, output_data);
}

void TestComparisonQuantizedInt16(const TFLMRegistration& registration,
int* input1_dims_data, float* input1_data,
int16_t* input1_quantized, float input1_scale,
int input1_zero_point, int* input2_dims_data,
float* input2_data, int16_t* input2_quantized,
float input2_scale, int input2_zero_point,
bool* expected_output_data,
int* output_dims_data, bool* output_data) {
TfLiteIntArray* input1_dims = IntArrayFromInts(input1_dims_data);
TfLiteIntArray* input2_dims = IntArrayFromInts(input2_dims_data);
TfLiteIntArray* output_dims = IntArrayFromInts(output_dims_data);

TfLiteTensor tensors[tensors_size] = {
CreateQuantizedTensor(input1_data, input1_quantized, input1_dims,
input1_scale, input1_zero_point),
CreateQuantizedTensor(input2_data, input2_quantized, input2_dims,
input2_scale, input2_zero_point),
CreateTensor(output_data, output_dims),
};

TestComparison(registration, tensors, expected_output_data, output_data);
}

} // namespace
} // namespace testing
} // namespace tflite
Expand Down Expand Up @@ -656,6 +679,35 @@ TF_LITE_MICRO_TEST(GreaterQuantizedInt8WithBroadcast) {
}
}

TF_LITE_MICRO_TEST(GreaterQuantizedInt16WithBroadcast) {
const int num_shapes = 4;
const int max_shape_size = 5;
int test_shapes[num_shapes][max_shape_size] = {
{1, 6}, {2, 2, 3}, {3, 2, 1, 3}, {4, 1, 3, 1, 2}};

for (int i = 0; i < num_shapes; ++i) {
int* input1_dim = test_shapes[i];
int input2_dim[] = {1, 1};
float input1_data[] = {20, -2, -71, 8, 11, 20};
float input2_data[] = {8};

bool expected_data[] = {true, false, false, false, true, true};
int* expected_dim = input1_dim;

const float input1_scale = 0.5;
const int input1_zero_point = -9;
int16_t input1_quantized[6];
int16_t input2_quantized[6];

bool output_data[6];
tflite::testing::TestComparisonQuantizedInt16(
tflite::Register_GREATER(), input1_dim, input1_data, input1_quantized,
input1_scale, input1_zero_point, input2_dim, input2_data,
input2_quantized, input1_scale, input1_zero_point, expected_data,
expected_dim, output_data);
}
}

TF_LITE_MICRO_TEST(GreaterEqualQuantizedInt8WithBroadcast) {
const int num_shapes = 4;
const int max_shape_size = 5;
Expand Down
106 changes: 89 additions & 17 deletions tensorflow/lite/micro/kernels/fully_connected.cc
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Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
/* Copyright 2025 The TensorFlow Authors. 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.
Expand Down Expand Up @@ -238,25 +238,97 @@ TfLiteStatus FullyConnectedEval(TfLiteContext* context, TfLiteNode* node) {
case kTfLiteInt16: {
switch (filter->type) {
case kTfLiteInt8: {
tflite::reference_integer_ops::FullyConnected(
FullyConnectedParamsQuantized(data),
tflite::micro::GetTensorShape(input),
tflite::micro::GetTensorData<int16_t>(input),
tflite::micro::GetTensorShape(filter),
if (bias == nullptr || bias->type == kTfLiteInt32) {
data.is_per_channel
? tflite::reference_integer_ops::FullyConnectedPerChannel(
FullyConnectedParamsQuantized(data),
data.per_channel_output_multiplier,
reinterpret_cast<const int*>(
data.per_channel_output_shift),
tflite::micro::GetTensorShape(input),
tflite::micro::GetTensorData<int16_t>(input),
tflite::micro::GetTensorShape(filter),
#ifdef USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(micro_context, filter,
weights_comp_td,
data.weights_scratch_index),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(
micro_context, bias, bias_comp_td, data.bias_scratch_index),
tflite::micro::GetTensorData<int8_t>(
micro_context, filter, weights_comp_td,
data.weights_scratch_index),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int32_t>(
micro_context, bias, bias_comp_td,
data.bias_scratch_index),
#else // USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(filter),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(bias),
tflite::micro::GetTensorData<int8_t>(filter),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int32_t>(bias),
#endif // USE_TFLM_COMPRESSION
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int16_t>(output));
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int16_t>(output))
: tflite::reference_integer_ops::FullyConnected(
FullyConnectedParamsQuantized(data),
tflite::micro::GetTensorShape(input),
tflite::micro::GetTensorData<int16_t>(input),
tflite::micro::GetTensorShape(filter),
#ifdef USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(
micro_context, filter, weights_comp_td,
data.weights_scratch_index),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int32_t>(
micro_context, bias, bias_comp_td,
data.bias_scratch_index),
#else // USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(filter),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int32_t>(bias),
#endif // USE_TFLM_COMPRESSION
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int16_t>(output));
} else if (bias->type == kTfLiteInt64) {
data.is_per_channel
? tflite::reference_integer_ops::FullyConnectedPerChannel(
FullyConnectedParamsQuantized(data),
data.per_channel_output_multiplier,
reinterpret_cast<const int*>(
data.per_channel_output_shift),
tflite::micro::GetTensorShape(input),
tflite::micro::GetTensorData<int16_t>(input),
tflite::micro::GetTensorShape(filter),
#ifdef USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(
micro_context, filter, weights_comp_td,
data.weights_scratch_index),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(
micro_context, bias, bias_comp_td,
data.bias_scratch_index),
#else // USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(filter),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(bias),
#endif // USE_TFLM_COMPRESSION
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int16_t>(output))
: tflite::reference_integer_ops::FullyConnected(
FullyConnectedParamsQuantized(data),
tflite::micro::GetTensorShape(input),
tflite::micro::GetTensorData<int16_t>(input),
tflite::micro::GetTensorShape(filter),
#ifdef USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(
micro_context, filter, weights_comp_td,
data.weights_scratch_index),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(
micro_context, bias, bias_comp_td,
data.bias_scratch_index),
#else // USE_TFLM_COMPRESSION
tflite::micro::GetTensorData<int8_t>(filter),
tflite::micro::GetTensorShape(bias),
tflite::micro::GetOptionalTensorData<int64_t>(bias),
#endif // USE_TFLM_COMPRESSION
tflite::micro::GetTensorShape(output),
tflite::micro::GetTensorData<int16_t>(output));
}
break;
}
default: {
Expand Down
13 changes: 9 additions & 4 deletions tensorflow/lite/micro/kernels/fully_connected_common.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
/* Copyright 2024 The TensorFlow Authors. All Rights Reserved.
/* Copyright 2025 The TensorFlow Authors. 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.
Expand Down Expand Up @@ -95,9 +95,14 @@ TfLiteStatus CalculateOpDataFullyConnected(
filter->quantization.params);
const int per_channel_quantization_size = affine_quantization->scale->size;

// Currently only Int8 is supported for per channel quantization.
TF_LITE_ENSURE(context,
input->type == kTfLiteInt8 && filter->type != kTfLiteInt4);
// Currently only Int8/Int16 are supported for per channel quantization.
TF_LITE_ENSURE(
context,
(input->type == kTfLiteInt8 && filter->type != kTfLiteInt4) ||
(input->type == kTfLiteInt16 && filter->type != kTfLiteInt4));

TF_LITE_ENSURE_EQ(context, affine_quantization->scale->size,
per_channel_quantization_size);

TF_LITE_ENSURE_EQ(
context, per_channel_quantization_size,
Expand Down
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