| 56 | } |
| 57 | |
| 58 | TfLiteStatus ResizeOutputTensors(TfLiteContext* context, TfLiteNode* node, |
| 59 | const TfLiteTensor* input, |
| 60 | const TfLiteTensor* size_splits, |
| 61 | const TfLiteTensor* axis) { |
| 62 | int axis_value = GetTensorData<int>(axis)[0]; |
| 63 | if (axis_value < 0) { |
| 64 | axis_value += NumDimensions(input); |
| 65 | } |
| 66 | |
| 67 | std::vector<int64_t> size_splits_vector; |
| 68 | if (size_splits->type == kTfLiteInt32) { |
| 69 | GetSizeSplitsVector<int32_t>(size_splits, &size_splits_vector); |
| 70 | } else if (size_splits->type == kTfLiteInt64) { |
| 71 | GetSizeSplitsVector<int64_t>(size_splits, &size_splits_vector); |
| 72 | } else { |
| 73 | context->ReportError(context, "size_splits only support type int32|int64."); |
| 74 | return kTfLiteError; |
| 75 | } |
| 76 | |
| 77 | int minus_one_index = -1; |
| 78 | int64_t size_splits_sum = 0; |
| 79 | |
| 80 | for (int i = 0; i < size_splits_vector.size(); ++i) { |
| 81 | if (size_splits_vector.at(i) == -1) { |
| 82 | if (minus_one_index == -1) { |
| 83 | minus_one_index = i; |
| 84 | } else { |
| 85 | context->ReportError(context, |
| 86 | "The size_splits contains more than one -1."); |
| 87 | } |
| 88 | } else { |
| 89 | size_splits_sum += size_splits_vector.at(i); |
| 90 | } |
| 91 | } |
| 92 | |
| 93 | TF_LITE_ENSURE(context, axis_value >= 0); |
| 94 | TF_LITE_ENSURE(context, axis_value < NumDimensions(input)); |
| 95 | const int input_size = SizeOfDimension(input, axis_value); |
| 96 | |
| 97 | if (minus_one_index != -1) { |
| 98 | if (size_splits_sum > input_size) { |
| 99 | context->ReportError( |
| 100 | context, |
| 101 | "The sum of size_splits must be less than the dimension of value."); |
| 102 | } else { |
| 103 | size_splits_vector[minus_one_index] = input_size - size_splits_sum; |
| 104 | } |
| 105 | } else if (size_splits_sum != input_size) { |
| 106 | context->ReportError( |
| 107 | context, |
| 108 | "The size_splits must sum to the dimension of value along axis."); |
| 109 | } |
| 110 | |
| 111 | for (int i = 0; i < NumOutputs(node); ++i) { |
| 112 | TfLiteIntArray* output_dims = TfLiteIntArrayCopy(input->dims); |
| 113 | output_dims->data[axis_value] = size_splits_vector.at(i); |
| 114 | TfLiteTensor* output = GetOutput(context, node, i); |
| 115 | TF_LITE_ENSURE_STATUS(context->ResizeTensor(context, output, output_dims)); |
no test coverage detected