TFLu: Remove support for unknown output dims for detecion_pp

tensorflow/lite/micro/kernels/detection_postprocess.cc

@@ -15,16 +15,7 @@ limitations under the License.
 #include <numeric>
 
 #define FLATBUFFERS_LOCALE_INDEPENDENT 0
-#if !defined(__GNUC__) || defined(__CC_ARM) || defined(__clang__)
-// TODO: remove this once this PR is merged and part of tensorflow downloads:
-// https://github.com/google/flatbuffers/pull/6132
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdouble-promotion"
 #include "flatbuffers/flexbuffers.h"
-#pragma clang diagnostic pop
-#else
-#include "flatbuffers/flexbuffers.h"
-#endif
 #include "tensorflow/lite/c/builtin_op_data.h"
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/kernels/internal/common.h"
@@ -129,49 +120,8 @@ struct OpData {
   TfLiteQuantizationParams input_box_encodings;
   TfLiteQuantizationParams input_class_predictions;
   TfLiteQuantizationParams input_anchors;
-
-  // In case out dimensions need to be allocated.
-  TfLiteIntArray* detection_boxes_dims;
-  TfLiteIntArray* detection_classes_dims;
-  TfLiteIntArray* detection_scores_dims;
-  TfLiteIntArray* num_detections_dims;
 };
 
-TfLiteStatus AllocateOutDimensions(TfLiteContext* context,
-                                    TfLiteTensor* tensor,
-                                    TfLiteIntArray** dims, int x, int y = 0,
-                                    int z = 0) {
-  int size = 1;
-  int size_dim = 1;
-  size = size * x;
-
-  if (y > 0) {
-    size = size * y;
-    size_dim++;
-    if (z > 0) {
-      size = size * z;
-      size_dim++;
-    }
-  }
-
-  *dims = reinterpret_cast<TfLiteIntArray*>(context->AllocatePersistentBuffer(
-      context, TfLiteIntArrayGetSizeInBytes(size)));
-
-  (*dims)->size = size_dim;
-  (*dims)->data[0] = x;
-  if (y > 0) {
-    (*dims)->data[1] = y;
-  }
-  if (z > 0) {
-    (*dims)->data[2] = z;
-  }
-
-  TFLITE_DCHECK(tensor->type == kTfLiteFloat32);
-  tensor->bytes = size * sizeof(float);
-
-  return kTfLiteOk;
-}
-
 void* Init(TfLiteContext* context, const char* buffer, size_t length) {
   OpData* op_data = nullptr;
 
@@ -271,54 +221,10 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   context->RequestScratchBufferInArena(
       context, buffer_size * num_boxes * sizeof(int), &op_data->selected_idx);
 
-  // number of detected boxes
-  const int num_detected_boxes =
-      op_data->max_detections * op_data->max_classes_per_detection;
-
   // Outputs: detection_boxes, detection_scores, detection_classes,
   // num_detections
   TF_LITE_ENSURE_EQ(context, NumOutputs(node), 4);
 
-  // Output Tensor detection_boxes: size is set to (1, num_detected_boxes, 4)
-  TfLiteTensor* detection_boxes =
-      GetOutput(context, node, kOutputTensorDetectionBoxes);
-  if (detection_boxes->dims->size == 0) {
-    TF_LITE_ENSURE_STATUS(AllocateOutDimensions(context, detection_boxes,
-                                                &detection_boxes->dims,
-                                                1, num_detected_boxes, 4));
-    op_data->detection_boxes_dims = detection_boxes->dims;
-  }
-
-  // Output Tensor detection_classes: size is set to (1, num_detected_boxes)
-  TfLiteTensor* detection_classes =
-      GetOutput(context, node, kOutputTensorDetectionClasses);
-  if (detection_classes->dims->size == 0) {
-    TF_LITE_ENSURE_STATUS(AllocateOutDimensions(
-        context, detection_classes,
-        &detection_classes->dims, 1, num_detected_boxes));
-    op_data->detection_classes_dims = detection_classes->dims;
-  }
-
-  // Output Tensor detection_scores: size is set to (1, num_detected_boxes)
-  TfLiteTensor* detection_scores =
-      GetOutput(context, node, kOutputTensorDetectionScores);
-  if (detection_scores->dims->size == 0) {
-    TF_LITE_ENSURE_STATUS(AllocateOutDimensions(
-        context, detection_scores,
-        &detection_scores->dims, 1, num_detected_boxes));
-    op_data->detection_scores_dims = detection_scores->dims;
-   }
-
-  // Output Tensor num_detections: size is set to 1
-  TfLiteTensor* num_detections =
-      GetOutput(context, node, kOutputTensorNumDetections);
-  if (num_detections->dims->size == 0) {
-    TF_LITE_ENSURE_STATUS(
-        AllocateOutDimensions(context, num_detections,
-                              &num_detections->dims, 1));
-    op_data->num_detections_dims = num_detections->dims;
-  }
-
   return kTfLiteOk;
 }
 
@@ -870,28 +776,6 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
   TF_LITE_ENSURE(context, (kBatchSize == 1));
   auto* op_data = static_cast<OpData*>(node->user_data);
 
-  TfLiteEvalTensor* detection_boxes =
-      tflite::micro::GetEvalOutput(context, node, kOutputTensorDetectionBoxes);
-  if (detection_boxes->dims->size == 0) {
-    detection_boxes->dims = op_data->detection_boxes_dims;
-  }
-  TfLiteEvalTensor* detection_classes =
-      tflite::micro::GetEvalOutput(context, node,
-                                   kOutputTensorDetectionClasses);
-  if (detection_classes->dims->size == 0) {
-    detection_classes->dims = op_data->detection_classes_dims;
-  }
-  TfLiteEvalTensor* detection_scores =
-      tflite::micro::GetEvalOutput(context, node, kOutputTensorDetectionScores);
-  if (detection_scores->dims->size == 0) {
-    detection_scores->dims = op_data->detection_scores_dims;
-   }
-  TfLiteEvalTensor* num_detections =
-      tflite::micro::GetEvalOutput(context, node, kOutputTensorNumDetections);
-  if (num_detections->dims->size == 0) {
-    num_detections->dims = op_data->num_detections_dims;
-  }
-
   // These two functions correspond to two blocks in the Object Detection model.
   // In future, we would like to break the custom op in two blocks, which is
   // currently not feasible because we would like to input quantized inputs

tensorflow/lite/micro/kernels/detection_postprocess_test.cc

@@ -13,22 +13,12 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
-#if !defined(__GNUC__) || defined(__CC_ARM) || defined(__clang__)
-// TODO: remove this once this PR is merged and part of tensorflow downloads:
-// https://github.com/google/flatbuffers/pull/6132
-#pragma clang diagnostic push
-#pragma clang diagnostic ignored "-Wdouble-promotion"
 #include "flatbuffers/flexbuffers.h"
-#pragma clang diagnostic pop
-#else
-#include "flatbuffers/flexbuffers.h"
-#endif
 #include "tensorflow/lite/c/builtin_op_data.h"
 #include "tensorflow/lite/c/common.h"
 #include "tensorflow/lite/micro/kernels/kernel_runner.h"
-
 #include "tensorflow/lite/micro/testing/micro_test.h"
-#include "tensorflow/lite/micro/testing/test_utils.h"
+#include "tensorflow/lite/micro/test_helpers.h"
 
 // See: tensorflow/lite/micro/kernels/detection_postprocess_test/readme
 #include "tensorflow/lite/micro/kernels/detection_postprocess_test/flexbuffers_generated_data.h"
@@ -484,20 +474,4 @@ TF_LITE_MICRO_TEST(
       /* input3 min/max */ 0.0, 100.5);
 }
 
-TF_LITE_MICRO_TEST(DetectionPostprocessFloatFastNMSUndefinedOutputDimensions) {
-  float output_data1[12];
-  float output_data2[3];
-  float output_data3[3];
-  float output_data4[1];
-
-  tflite::testing::TestDetectionPostprocess(
-      tflite::testing::kInputShape1, tflite::testing::kInputData1,
-      tflite::testing::kInputShape2, tflite::testing::kInputData2,
-      tflite::testing::kInputShape3, tflite::testing::kInputData3, nullptr,
-      output_data1, nullptr, output_data2, nullptr, output_data3, nullptr,
-      output_data4, tflite::testing::kGolden1, tflite::testing::kGolden2,
-      tflite::testing::kGolden3, tflite::testing::kGolden4,
-      /* tolerance */ 0, /* Use regular NMS: */ false);
-}
-
 TF_LITE_MICRO_TESTS_END