| 30 | |
| 31 | namespace { |
| 32 | TfLiteStatus ResizeOutput(TfLiteContext* context, TfLiteNode* node) { |
| 33 | const TfLiteTensor* top_k = GetInput(context, node, kInputTopK); |
| 34 | // INT32 number of top results is supported. |
| 35 | TF_LITE_ENSURE_EQ(context, top_k->type, kTfLiteInt32); |
| 36 | // Check that the tensor contains only one value. |
| 37 | TF_LITE_ENSURE_EQ(context, NumElements(top_k), 1); |
| 38 | const int32 k = *GetTensorData<int32_t>(top_k); |
| 39 | |
| 40 | const TfLiteTensor* input = GetInput(context, node, kInputTensor); |
| 41 | const int num_dimensions = NumDimensions(input); |
| 42 | // Check that input has one or more dimensions. |
| 43 | TF_LITE_ENSURE_MSG(context, input->dims->size >= 1, |
| 44 | "TopK k input must have 1 or more dimensions."); |
| 45 | // Check that k is less or equal the internal dimension. |
| 46 | TF_LITE_ENSURE_MSG(context, k <= input->dims->data[num_dimensions - 1], |
| 47 | "TopK k is higher than the internal dimension."); |
| 48 | |
| 49 | TfLiteIntArray* output_indexes_shape = TfLiteIntArrayCreate(num_dimensions); |
| 50 | TfLiteIntArray* output_values_shape = TfLiteIntArrayCreate(num_dimensions); |
| 51 | for (int i = 0; i < num_dimensions - 1; ++i) { |
| 52 | output_indexes_shape->data[i] = input->dims->data[i]; |
| 53 | output_values_shape->data[i] = input->dims->data[i]; |
| 54 | } |
| 55 | output_indexes_shape->data[num_dimensions - 1] = k; |
| 56 | output_values_shape->data[num_dimensions - 1] = k; |
| 57 | TfLiteTensor* output_indexes = GetOutput(context, node, kOutputIndexes); |
| 58 | TfLiteTensor* output_values = GetOutput(context, node, kOutputValues); |
| 59 | // Force output types. |
| 60 | output_indexes->type = kTfLiteInt32; |
| 61 | output_values->type = input->type; |
| 62 | auto resize_tensor = [context](TfLiteTensor* tensor, TfLiteIntArray* new_size, |
| 63 | TfLiteIntArray* delete_on_error) { |
| 64 | TfLiteStatus status = context->ResizeTensor(context, tensor, new_size); |
| 65 | if (status != kTfLiteOk) { |
| 66 | if (delete_on_error != nullptr) { |
| 67 | TfLiteIntArrayFree(delete_on_error); |
| 68 | } |
| 69 | } |
| 70 | return status; |
| 71 | }; |
| 72 | TF_LITE_ENSURE_OK(context, resize_tensor(output_indexes, output_indexes_shape, |
| 73 | output_values_shape)); |
| 74 | TF_LITE_ENSURE_OK(context, |
| 75 | resize_tensor(output_values, output_values_shape, nullptr)); |
| 76 | return kTfLiteOk; |
| 77 | } |
| 78 | |
| 79 | // Class that collects indices of top k values. Based on template |
| 80 | // tensorflow::gtl::TopN<> but, for optimization, it re-uses the same container. |
no test coverage detected