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Add kernels optimized for size flag to FC and SVDF #2734

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merged 2 commits into from
Nov 1, 2024
Merged

Add kernels optimized for size flag to FC and SVDF #2734

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658347e
Add kernels optimized for size flag to FC and SVDF
mansnils Sep 20, 2024
a5dc2c8
Merge branch 'main' into misc
mergify[bot] Nov 1, 2024
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11 changes: 8 additions & 3 deletions tensorflow/lite/micro/kernels/cmsis_nn/fully_connected.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -148,22 +148,27 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
} else if (input->type == kTfLiteInt8) {
buf_size = arm_fully_connected_s8_get_buffer_size(&filter_dims);

int8_t* filter_data = GetTensorData<int8_t>(filter);
data->kernel_sums = nullptr;

#if defined(KERNELS_OPTIMIZED_FOR_SPEED)
const int8_t* filter_data = GetTensorData<const int8_t>(filter);

if (buf_size > 0 && filter_data != nullptr) {
const int32_t input_offset = -data->reference_op_data.input_zero_point;
const int32_t filter_offset =
-data->reference_op_data.filter_zero_point;

data->kernel_sums = static_cast<int32_t*>(
context->AllocatePersistentBuffer(context, buf_size));

int32_t input_offset = -data->reference_op_data.input_zero_point;
int32_t filter_offset = -data->reference_op_data.filter_zero_point;
arm_vector_sum_s8(data->kernel_sums, filter_dims.n, data->output_depth,
filter_data, input_offset, filter_offset,
tflite::GetTensorData<int32_t>(bias));

// Do not request a scratch buffer since using persistent memory
buf_size = 0;
}
#endif
}
}

Expand Down
29 changes: 29 additions & 0 deletions tensorflow/lite/micro/kernels/cmsis_nn/svdf.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -39,6 +39,9 @@ struct CmsisNnOpDataSvdf {
int effective_scale_1_b;
int effective_scale_2_b;
int scratch_tensor_index;
#if defined(KERNELS_OPTIMIZED_FOR_SIZE)
int scratch_weight_tensor_index;
#endif
int scratch_output_tensor_index;

// Cached tensor zero point values for quantized operations.
Expand Down Expand Up @@ -189,13 +192,25 @@ TfLiteStatus CmsisNnPrepareSvdf(TfLiteContext* context, TfLiteNode* node) {
const int32_t buf_size = arm_svdf_s8_get_buffer_size(&weights_feature_dims);

if (buf_size > 0) {
#if defined(KERNELS_OPTIMIZED_FOR_SPEED)
data->kernel_sums = static_cast<int32_t*>(
context->AllocatePersistentBuffer(context, buf_size));

arm_vector_sum_s8(data->kernel_sums, input_size, num_filters,
GetTensorData<int8_t>(weights_feature),
-data->input_zero_point,
-data->activation_state_zero_point, nullptr);
#elif defined(KERNELS_OPTIMIZED_FOR_SIZE)
const TfLiteStatus scratch_kernel_status =
context->RequestScratchBufferInArena(
context, buf_size, &(data->scratch_weight_tensor_index));
TF_LITE_ENSURE_OK(context, scratch_kernel_status);
#else
MicroPrintf(
"Either KERNELS_OPTIMIZED_FOR_SIZE or KERNELS_OPTIMIZED_FOR_SPEED "
"must be defined");
return kTfLiteError;
#endif
}

} else {
Expand Down Expand Up @@ -291,7 +306,21 @@ TfLiteStatus EvalIntegerSVDF(TfLiteContext* context, TfLiteNode* node,
switch (weights_time_tensor->type) {
case kTfLiteInt8: {
cmsis_nn_context ctx;

#if defined(KERNELS_OPTIMIZED_FOR_SPEED)
ctx.buf = data.kernel_sums;
#elif defined(KERNELS_OPTIMIZED_FOR_SIZE)
ctx.buf = static_cast<int32_t*>(
context->GetScratchBuffer(context, data.scratch_weight_tensor_index));

const int input_size = input_tensor->dims->data[1];
const int num_filters = weights_feature_tensor->dims->data[0];

arm_vector_sum_s8(
static_cast<int32_t*>(ctx.buf), input_size, num_filters,
tflite::micro::GetTensorData<int8_t>(weights_feature_tensor),
-data.input_zero_point, -data.activation_state_zero_point, nullptr);
#endif

arm_svdf_s8(
&ctx, &scratch_ctx, &scratch_output_ctx, &svdf_params,
Expand Down
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