From d43453baa525c04d401fc88a57602030fa16a7b8 Mon Sep 17 00:00:00 2001
From: "A. Unique TensorFlower" <gardener@tensorflow.org>
Date: Tue, 19 Mar 2019 14:07:23 -0700
Subject: [PATCH] Add negative axis support to Pack.

PiperOrigin-RevId: 239265388
---
 tensorflow/lite/kernels/pack.cc      | 36 ++++++++++++--------
 tensorflow/lite/kernels/pack_test.cc | 51 ++++++++++++++++++++++++++++
 2 files changed, 72 insertions(+), 15 deletions(-)

diff --git a/tensorflow/lite/kernels/pack.cc b/tensorflow/lite/kernels/pack.cc
index e26abaaff1e..3515c3e873f 100644
--- a/tensorflow/lite/kernels/pack.cc
+++ b/tensorflow/lite/kernels/pack.cc
@@ -28,16 +28,20 @@ namespace {
 constexpr int kOutputTensor = 0;
 
 TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
-  const TfLitePackParams* data =
+  TfLitePackParams* data =
       reinterpret_cast<TfLitePackParams*>(node->builtin_data);
 
   TF_LITE_ENSURE_EQ(context, NumInputs(node), data->values_count);
   TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
 
   const TfLiteTensor* input0 = GetInput(context, node, 0);
+  const int dimension_size = NumDimensions(input0) + 1;
+  if (data->axis < 0) {
+    data->axis += dimension_size;
+  }
   TF_LITE_ENSURE(context, NumDimensions(input0) >= data->axis);
-  // TODO(renjieliu): Support negative axis.
   TF_LITE_ENSURE(context, data->axis >= 0);
+
   if (input0->type != kTfLiteInt32 && input0->type != kTfLiteFloat32 &&
       input0->type != kTfLiteUInt8 && input0->type != kTfLiteInt8 &&
       input0->type != kTfLiteInt16 && input0->type != kTfLiteInt64) {
@@ -53,7 +57,6 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   }
 
   // Resize output. rank R will become rank R + 1
-  const int dimension_size = NumDimensions(input0) + 1;
   const TfLiteIntArray* input_shape = input0->dims;
   TfLiteIntArray* output_shape = TfLiteIntArrayCreate(dimension_size);
   int i = 0;
@@ -81,8 +84,10 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
 }
 
 template <typename T>
-void PackImpl(TfLiteContext* context, TfLiteNode* node, TfLiteTensor* output,
-              int values_count, int axis) {
+TfLiteStatus PackImpl(TfLiteContext* context, TfLiteNode* node,
+                      TfLiteTensor* output, int values_count, int axis) {
+  TF_LITE_ENSURE(context, axis >= 0);
+
   VectorOfTensors<T> all_inputs(*context, *node->inputs);
   tflite::PackParams op_params;
   op_params.axis = axis;
@@ -90,6 +95,7 @@ void PackImpl(TfLiteContext* context, TfLiteNode* node, TfLiteTensor* output,
 
   reference_ops::Pack<T>(op_params, all_inputs.shapes(), all_inputs.data(),
                          GetTensorShape(output), GetTensorData<T>(output));
+  return kTfLiteOk;
 }
 
 TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
@@ -99,24 +105,24 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
   TfLiteTensor* output = GetOutput(context, node, kOutputTensor);
   switch (output->type) {
     case kTfLiteFloat32: {
-      PackImpl<float>(context, node, output, data->values_count, data->axis);
-      break;
+      return PackImpl<float>(context, node, output, data->values_count,
+                             data->axis);
     }
     case kTfLiteUInt8: {
-      PackImpl<uint8_t>(context, node, output, data->values_count, data->axis);
-      break;
+      return PackImpl<uint8_t>(context, node, output, data->values_count,
+                               data->axis);
     }
     case kTfLiteInt8: {
-      PackImpl<int8_t>(context, node, output, data->values_count, data->axis);
-      break;
+      return PackImpl<int8_t>(context, node, output, data->values_count,
+                              data->axis);
     }
     case kTfLiteInt32: {
-      PackImpl<int32_t>(context, node, output, data->values_count, data->axis);
-      break;
+      return PackImpl<int32_t>(context, node, output, data->values_count,
+                               data->axis);
     }
     case kTfLiteInt64: {
-      PackImpl<int64_t>(context, node, output, data->values_count, data->axis);
-      break;
+      return PackImpl<int64_t>(context, node, output, data->values_count,
+                               data->axis);
     }
     default: {
       context->ReportError(context, "Type '%s' is not supported by pack.",
diff --git a/tensorflow/lite/kernels/pack_test.cc b/tensorflow/lite/kernels/pack_test.cc
index f44111567fc..b40bb45b76a 100644
--- a/tensorflow/lite/kernels/pack_test.cc
+++ b/tensorflow/lite/kernels/pack_test.cc
@@ -72,6 +72,16 @@ TEST(PackOpTest, FloatThreeInputsDifferentAxis) {
   EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
 }
 
+TEST(PackOpTest, FloatThreeInputsNegativeAxis) {
+  PackOpModel<float> model({TensorType_FLOAT32, {2}}, -1, 3);
+  model.SetInput(0, {1, 4});
+  model.SetInput(1, {2, 5});
+  model.SetInput(2, {3, 6});
+  model.Invoke();
+  EXPECT_THAT(model.GetOutputShape(), ElementsAre(2, 3));
+  EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
+}
+
 TEST(PackOpTest, FloatMultilDimensions) {
   PackOpModel<float> model({TensorType_FLOAT32, {2, 3}}, 1, 2);
   model.SetInput(0, {1, 2, 3, 4, 5, 6});
@@ -116,6 +126,16 @@ TEST(PackOpTest, Int32ThreeInputsDifferentAxis) {
   EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
 }
 
+TEST(PackOpTest, Int32ThreeInputsNegativeAxis) {
+  PackOpModel<int32_t> model({TensorType_INT32, {2}}, -1, 3);
+  model.SetInput(0, {1, 4});
+  model.SetInput(1, {2, 5});
+  model.SetInput(2, {3, 6});
+  model.Invoke();
+  EXPECT_THAT(model.GetOutputShape(), ElementsAre(2, 3));
+  EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
+}
+
 TEST(PackOpTest, Int32MultilDimensions) {
   PackOpModel<int32_t> model({TensorType_INT32, {2, 3}}, 1, 2);
   model.SetInput(0, {1, 2, 3, 4, 5, 6});
@@ -149,6 +169,17 @@ TEST(PackOpTest, Int64ThreeInputsDifferentAxis) {
               ElementsAreArray({1LL << 33, 2LL, 3LL, 4LL, 5LL, -(1LL << 34)}));
 }
 
+TEST(PackOpTest, Int64ThreeInputsNegativeAxis) {
+  PackOpModel<int64_t> model({TensorType_INT64, {2}}, -1, 3);
+  model.SetInput(0, {1LL << 33, 4});
+  model.SetInput(1, {2, 5});
+  model.SetInput(2, {3, -(1LL << 34)});
+  model.Invoke();
+  EXPECT_THAT(model.GetOutputShape(), ElementsAre(2, 3));
+  EXPECT_THAT(model.GetOutput(),
+              ElementsAreArray({1LL << 33, 2LL, 3LL, 4LL, 5LL, -(1LL << 34)}));
+}
+
 TEST(PackOpTest, Int64MultilDimensions) {
   PackOpModel<int64_t> model({TensorType_INT64, {2, 3}}, 1, 2);
   model.SetInput(0, {1LL << 33, 2, 3, 4, 5, 6});
@@ -181,6 +212,16 @@ TEST(PackOpTest, Uint8ThreeInputsDifferentAxis) {
   EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
 }
 
+TEST(PackOpTest, Uint8ThreeInputsNegativeAxis) {
+  PackOpModel<uint8_t> model({TensorType_UINT8, {2}}, -1, 3);
+  model.SetInput(0, {1, 4});
+  model.SetInput(1, {2, 5});
+  model.SetInput(2, {3, 6});
+  model.Invoke();
+  EXPECT_THAT(model.GetOutputShape(), ElementsAre(2, 3));
+  EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
+}
+
 TEST(PackOpTest, Uint8MultilDimensions) {
   PackOpModel<uint8_t> model({TensorType_UINT8, {2, 3}}, 1, 2);
   model.SetInput(0, {1, 2, 3, 4, 5, 6});
@@ -212,6 +253,16 @@ TEST(PackOpTest, Int8ThreeInputsDifferentAxis) {
   EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
 }
 
+TEST(PackOpTest, Int8ThreeInputsNegativeAxis) {
+  PackOpModel<int8_t> model({TensorType_INT8, {2}}, -1, 3);
+  model.SetInput(0, {1, 4});
+  model.SetInput(1, {2, 5});
+  model.SetInput(2, {3, 6});
+  model.Invoke();
+  EXPECT_THAT(model.GetOutputShape(), ElementsAre(2, 3));
+  EXPECT_THAT(model.GetOutput(), ElementsAreArray({1, 2, 3, 4, 5, 6}));
+}
+
 TEST(PackOpTest, Int8MultilDimensions) {
   PackOpModel<int8_t> model({TensorType_INT8, {2, 3}}, 1, 2);
   model.SetInput(0, {1, 2, 3, 4, 5, 6});