Unique Init, Prepare, Eval functions Kernels N-Z (#2351)

efactor init, prepare , and eval functions to be unique names for kernels who's name starts with the Letters N-Z BUG=[b/313963581](https://b.corp.google.com/issues/313963581)
tensorflow · Dec 12, 2023 · 93d4b1c · 93d4b1c
1 parent ec57f3b
commit 93d4b1c
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Showing 23 changed files with 81 additions and 69 deletions.
diff --git a/tensorflow/lite/micro/kernels/neg.cc b/tensorflow/lite/micro/kernels/neg.cc
@@ -27,7 +27,7 @@ namespace {
 constexpr int kInputTensor = 0;
 constexpr int kOutputTensor = 0;
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus NegEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input =
       tflite::micro::GetEvalInput(context, node, kInputTensor);
   TfLiteEvalTensor* output =
@@ -51,7 +51,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_NEG() {
-  return tflite::micro::RegisterOp(nullptr, nullptr, Eval);
+  return tflite::micro::RegisterOp(nullptr, nullptr, NegEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/pack.cc b/tensorflow/lite/micro/kernels/pack.cc
@@ -69,7 +69,7 @@ TfLiteStatus PackImpl(TfLiteContext* context, TfLiteNode* node,
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus PackEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLitePackParams* data =
       reinterpret_cast<TfLitePackParams*>(node->builtin_data);
 
@@ -106,7 +106,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_PACK() {
-  return tflite::micro::RegisterOp(nullptr, nullptr, Eval);
+  return tflite::micro::RegisterOp(nullptr, nullptr, PackEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/pad.cc b/tensorflow/lite/micro/kernels/pad.cc
@@ -32,12 +32,12 @@ struct OpData {
   int32_t output_zero_point;
 };
 
-void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+void* PadInit(TfLiteContext* context, const char* buffer, size_t length) {
   TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
   return context->AllocatePersistentBuffer(context, sizeof(OpData));
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus PadEval(TfLiteContext* context, TfLiteNode* node) {
   TFLITE_DCHECK(node->user_data != nullptr);
   const OpData* data = static_cast<const OpData*>(node->user_data);
 
@@ -218,12 +218,12 @@ TfLiteStatus PadPrepare(TfLiteContext* context, TfLiteNode* node) {
 }
 
 TFLMRegistration Register_PAD() {
-  return tflite::micro::RegisterOp(Init, PadPrepare, Eval);
+  return tflite::micro::RegisterOp(PadInit, PadPrepare, PadEval);
 }
 
 // Also register Pad as PadV2.
 TFLMRegistration Register_PADV2() {
-  return tflite::micro::RegisterOp(Init, PadPrepare, Eval);
+  return tflite::micro::RegisterOp(PadInit, PadPrepare, PadEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/pooling.cc b/tensorflow/lite/micro/kernels/pooling.cc
@@ -91,19 +91,19 @@ TfLiteStatus MaxEval(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+void* PoolInit(TfLiteContext* context, const char* buffer, size_t length) {
   TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
   return context->AllocatePersistentBuffer(context, sizeof(OpDataPooling));
 }
 
 }  // namespace
 
 TFLMRegistration Register_AVERAGE_POOL_2D() {
-  return tflite::micro::RegisterOp(Init, PoolingPrepare, AverageEval);
+  return tflite::micro::RegisterOp(PoolInit, PoolingPrepare, AverageEval);
 }
 
 TFLMRegistration Register_MAX_POOL_2D() {
-  return tflite::micro::RegisterOp(Init, PoolingPrepare, MaxEval);
+  return tflite::micro::RegisterOp(PoolInit, PoolingPrepare, MaxEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/quantize.cc b/tensorflow/lite/micro/kernels/quantize.cc
@@ -25,7 +25,8 @@ limitations under the License.
 namespace tflite {
 namespace {
 
-void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+void* InitQuantizeReference(TfLiteContext* context, const char* buffer,
+                            size_t length) {
   TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
   return context->AllocatePersistentBuffer(context,
                                            sizeof(OpDataQuantizeReference));
@@ -34,8 +35,8 @@ void* Init(TfLiteContext* context, const char* buffer, size_t length) {
 }  // namespace
 
 TFLMRegistration Register_QUANTIZE() {
-  return tflite::micro::RegisterOp(Init, PrepareQuantizeReference,
-                                   EvalQuantizeReference);
+  return tflite::micro::RegisterOp(
+      InitQuantizeReference, PrepareQuantizeReference, EvalQuantizeReference);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/reshape.cc b/tensorflow/lite/micro/kernels/reshape.cc
@@ -29,7 +29,7 @@ limitations under the License.
 namespace tflite {
 namespace {
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus EvalReshapeReference(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input =
       tflite::micro::GetEvalInput(context, node, kReshapeInputTensor);
   TfLiteEvalTensor* output =
@@ -52,7 +52,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_RESHAPE() {
-  return tflite::micro::RegisterOp(nullptr, PrepareReshapeReference, Eval);
+  return tflite::micro::RegisterOp(nullptr, PrepareReshapeReference,
+                                   EvalReshapeReference);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/resize_bilinear.cc b/tensorflow/lite/micro/kernels/resize_bilinear.cc
@@ -30,7 +30,7 @@ constexpr int kInputTensor = 0;
 constexpr int kSizeTensor = 1;
 constexpr int kOutputTensor = 0;
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ResizeBilinearPrepare(TfLiteContext* context, TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
 
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
@@ -66,7 +66,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ResizeBilinearEval(TfLiteContext* context, TfLiteNode* node) {
   auto* params =
       reinterpret_cast<TfLiteResizeBilinearParams*>(node->builtin_data);
 
@@ -110,7 +110,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_RESIZE_BILINEAR() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, ResizeBilinearPrepare,
+                                   ResizeBilinearEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/resize_nearest_neighbor.cc b/tensorflow/lite/micro/kernels/resize_nearest_neighbor.cc
@@ -31,7 +31,8 @@ constexpr int kInputTensor = 0;
 constexpr int kSizeTensor = 1;
 constexpr int kOutputTensor = 0;
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ResizeNearestNeighborPrepare(TfLiteContext* context,
+                                          TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
 
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
@@ -65,7 +66,8 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ResizeNearestNeighborEval(TfLiteContext* context,
+                                       TfLiteNode* node) {
   auto* params =
       reinterpret_cast<TfLiteResizeNearestNeighborParams*>(node->builtin_data);
 
@@ -117,7 +119,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_RESIZE_NEAREST_NEIGHBOR() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, ResizeNearestNeighborPrepare,
+                                   ResizeNearestNeighborEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/round.cc b/tensorflow/lite/micro/kernels/round.cc
@@ -26,7 +26,7 @@ namespace {
 constexpr int kInputTensor = 0;
 constexpr int kOutputTensor = 0;
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus RoundPrepare(TfLiteContext* context, TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
 
   TfLiteTensor* input =
@@ -50,7 +50,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus RoundEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input =
       tflite::micro::GetEvalInput(context, node, kInputTensor);
   TfLiteEvalTensor* output =
@@ -66,7 +66,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_ROUND() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, RoundPrepare, RoundEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/shape.cc b/tensorflow/lite/micro/kernels/shape.cc
@@ -35,14 +35,14 @@ void ExtractShape(const TfLiteEvalTensor* input, int32_t* output_data) {
   }
 }
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ShapePrepare(TfLiteContext* context, TfLiteNode* node) {
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
   TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
 
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus ShapeEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input =
       tflite::micro::GetEvalInput(context, node, kInputTensor);
   TfLiteEvalTensor* output =
@@ -61,7 +61,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_SHAPE() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, ShapePrepare, ShapeEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/slice.cc b/tensorflow/lite/micro/kernels/slice.cc
@@ -44,7 +44,7 @@ void GetBeginAndSizeVectors(int dimensions, const TfLiteEvalTensor* begin,
   }
 }
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SlicePrepare(TfLiteContext* context, TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
 
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 3);
@@ -81,7 +81,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SliceEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input =
       tflite::micro::GetEvalInput(context, node, kInputTensor);
   const TfLiteEvalTensor* begin =
@@ -158,7 +158,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_SLICE() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, SlicePrepare, SliceEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/space_to_batch_nd.cc b/tensorflow/lite/micro/kernels/space_to_batch_nd.cc
@@ -39,12 +39,13 @@ constexpr int kOutputTensor = 0;
 const int kInputOutputMinDimensionNum = 3;
 const int kInputOutputMaxDimensionNum = 4;
 
-void* Init(TfLiteContext* context, const char* buffer, size_t length) {
+void* SpaceToBatchNDInit(TfLiteContext* context, const char* buffer,
+                         size_t length) {
   TFLITE_DCHECK(context->AllocatePersistentBuffer != nullptr);
   return context->AllocatePersistentBuffer(context, sizeof(SpaceToBatchParams));
 }
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SpaceToBatchNDPrepare(TfLiteContext* context, TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
 
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 3);
@@ -67,7 +68,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SpaceToBatchNDEval(TfLiteContext* context, TfLiteNode* node) {
   TFLITE_DCHECK(node->user_data != nullptr);
   const SpaceToBatchParams& params =
       *(static_cast<const SpaceToBatchParams*>(node->user_data));
@@ -115,7 +116,8 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace.
 
 TFLMRegistration Register_SPACE_TO_BATCH_ND() {
-  return tflite::micro::RegisterOp(Init, Prepare, Eval);
+  return tflite::micro::RegisterOp(SpaceToBatchNDInit, SpaceToBatchNDPrepare,
+                                   SpaceToBatchNDEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/split.cc b/tensorflow/lite/micro/kernels/split.cc
@@ -67,7 +67,7 @@ TfLiteStatus SplitImpl(TfLiteContext* context, TfLiteNode* node,
   return kTfLiteOk;
 }
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SplitPrepare(TfLiteContext* context, TfLiteNode* node) {
   MicroContext* micro_context = GetMicroContext(context);
   TfLiteTensor* axis = micro_context->AllocateTempInputTensor(node, 0);
   TF_LITE_ENSURE(context, axis != nullptr);
@@ -82,7 +82,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SplitEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* axis = tflite::micro::GetEvalInput(context, node, 0);
   const TfLiteEvalTensor* input = tflite::micro::GetEvalInput(context, node, 1);
 
@@ -119,7 +119,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_SPLIT() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, SplitPrepare, SplitEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/split_v.cc b/tensorflow/lite/micro/kernels/split_v.cc
@@ -71,7 +71,7 @@ TfLiteStatus SplitImpl(TfLiteContext* context, TfLiteNode* node,
   return kTfLiteOk;
 }
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SplitVPrepare(TfLiteContext* context, TfLiteNode* node) {
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 3);
 
   MicroContext* micro_context = GetMicroContext(context);
@@ -85,7 +85,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SplitVEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input = tflite::micro::GetEvalInput(context, node, 0);
   const TfLiteEvalTensor* axis = tflite::micro::GetEvalInput(context, node, 2);
 
@@ -121,7 +121,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_SPLIT_V() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, SplitVPrepare, SplitVEval);
 }
 
 }  // namespace tflite
diff --git a/tensorflow/lite/micro/kernels/squeeze.cc b/tensorflow/lite/micro/kernels/squeeze.cc
@@ -44,7 +44,7 @@ struct SqueezeContext {
   TfLiteTensor* output;
 };
 
-TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SqueezePrepare(TfLiteContext* context, TfLiteNode* node) {
   TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
   TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
 
@@ -87,7 +87,7 @@ TfLiteStatus Prepare(TfLiteContext* context, TfLiteNode* node) {
   return kTfLiteOk;
 }
 
-TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
+TfLiteStatus SqueezeEval(TfLiteContext* context, TfLiteNode* node) {
   const TfLiteEvalTensor* input = tflite::micro::GetEvalInput(context, node, 0);
 
   if (input->type == kTfLiteString) {
@@ -112,7 +112,7 @@ TfLiteStatus Eval(TfLiteContext* context, TfLiteNode* node) {
 }  // namespace
 
 TFLMRegistration Register_SQUEEZE() {
-  return tflite::micro::RegisterOp(nullptr, Prepare, Eval);
+  return tflite::micro::RegisterOp(nullptr, SqueezePrepare, SqueezeEval);
 }
 
 }  // namespace tflite