The DeepSeek-1.3B model fine-tuned with CVEFix for vulnerability fixing

Training Details

batch size: 2
learning rate: 3e-5
epochs: 2
training steps: 5516

Prompt

{at most 20 lines before the buggy lines} {buggy lines} {at most 20 lines after the buggy lines}

TfLiteStatus HardSwishEval(TfLiteContext* context, TfLiteNode* node) {\n  HardSwishData* data = static_cast<HardSwishData*>(node->user_data);
// buggy lines start:
  const TfLiteTensor* input = GetInput(context, node, 0);
  TfLiteTensor* output = GetOutput(context, node, 0);
// buggy lines end
  switch (input->type) {
    case kTfLiteFloat32: {
      if (kernel_type == kReference) {
        reference_ops::HardSwish(
            GetTensorShape(input), GetTensorData<float>(input),
            GetTensorShape(output), GetTensorData<float>(output));
      } else {
        optimized_ops::HardSwish(
            GetTensorShape(input), GetTensorData<float>(input),
            GetTensorShape(output), GetTensorData<float>(output));
      }
      return kTfLiteOk;
    } break;
    case kTfLiteUInt8: {
      HardSwishParams& params = data->params;
      if (kernel_type == kReference) {
        reference_ops::HardSwish(
            params, GetTensorShape(input), GetTensorData<uint8_t>(input),
            GetTensorShape(output), GetTensorData<uint8_t>(output));
      } else {
// fixed lines:

The model is trained to take the prompt and generate the fixed lines replacing the buggy lines

  const TfLiteTensor* input;
  TF_LITE_ENSURE_OK(context, GetInputSafe(context, node, 0, &input));
  TfLiteTensor* output;
  TF_LITE_ENSURE_OK(context, GetOutputSafe(context, node, 0, &output));