Update namespace in libs/tflite/ext (#4015)

Update namespace in libs/tflite/ext to nnfw::tflite
Reduce namespace depth for custom op

Signed-off-by: Hyeongseok Oh <hseok82.oh@samsung.com>

diff --git a/libs/tflite/include/tflite/NNAPISession.h b/libs/tflite/include/tflite/NNAPISession.h
index ec9fbd8..b2a999d 100644 (file)
--- a/libs/tflite/include/tflite/NNAPISession.h
+++ b/libs/tflite/include/tflite/NNAPISession.h
@@ -92,7 +92,7 @@ public:
 
 private:
   ::tflite::Interpreter *const _interp;
-  nnfw::NNAPIDelegate _delegate;
+  nnfw::tflite::NNAPIDelegate _delegate;
 };
 
 } // namespace tflite

diff --git a/libs/tflite/include/tflite/ext/kernels/Abs.h b/libs/tflite/include/tflite/ext/kernels/Abs.h
index 4ea8569..74e4aa6 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/Abs.h
+++ b/libs/tflite/include/tflite/ext/kernels/Abs.h
@@ -19,14 +19,12 @@
 
 #include "tensorflow/contrib/lite/context.h"
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace Abs
 {
 
@@ -36,9 +34,8 @@ TfLiteStatus PrepareAbs(TfLiteContext *context, TfLiteNode *node);
 TfLiteStatus EvalAbs(TfLiteContext *context, TfLiteNode *node);
 
 } // namespace Abs
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_ABS_H__

diff --git a/libs/tflite/include/tflite/ext/kernels/CustomOps.h b/libs/tflite/include/tflite/ext/kernels/CustomOps.h
index 2642445..3f9459b 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/CustomOps.h
+++ b/libs/tflite/include/tflite/ext/kernels/CustomOps.h
@@ -29,14 +29,12 @@
 #include "tflite/ext/kernels/TensorFlowSum.h"
 #include "tflite/ext/kernels/Abs.h"
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 
 #define REGISTER_FUNCTION(Name)                                                    \
   TfLiteRegistration *Register_##Name(void)                                        \
@@ -55,9 +53,8 @@ REGISTER_FUNCTION(Abs)
 
 #undef REGISTER_FUNCTION
 
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_CUSTOM_OP_H__

diff --git a/libs/tflite/include/tflite/ext/kernels/SquaredDifference.h b/libs/tflite/include/tflite/ext/kernels/SquaredDifference.h
index 9bf2936..492523c 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/SquaredDifference.h
+++ b/libs/tflite/include/tflite/ext/kernels/SquaredDifference.h
@@ -26,14 +26,12 @@
 
 #include "tensorflow/contrib/lite/context.h"
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace SquaredDifference
 {
 
@@ -71,9 +69,8 @@ TfLiteStatus PrepareSquaredDifference(TfLiteContext *context, TfLiteNode *node);
 TfLiteStatus EvalSquaredDifference(TfLiteContext *context, TfLiteNode *node);
 
 } // namespace SquaredDifference
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_SQUARED_DIFFERENCE_H__

diff --git a/libs/tflite/include/tflite/ext/kernels/TensorFlowMax.h b/libs/tflite/include/tflite/ext/kernels/TensorFlowMax.h
index 9fb8b73..d31d764 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/TensorFlowMax.h
+++ b/libs/tflite/include/tflite/ext/kernels/TensorFlowMax.h
@@ -25,14 +25,12 @@
 
 #include "tensorflow/contrib/lite/context.h"
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace TensorFlowMax
 {
 
@@ -70,9 +68,8 @@ TfLiteStatus PrepareTensorFlowMax(TfLiteContext *context, TfLiteNode *node);
 TfLiteStatus EvalTensorFlowMax(TfLiteContext *context, TfLiteNode *node);
 
 } // namespace TensorFlowMax
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_TENSORFLOW_MAX_H__

diff --git a/libs/tflite/include/tflite/ext/kernels/TensorFlowSum.h b/libs/tflite/include/tflite/ext/kernels/TensorFlowSum.h
index 6479c92..66783cf 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/TensorFlowSum.h
+++ b/libs/tflite/include/tflite/ext/kernels/TensorFlowSum.h
@@ -19,14 +19,12 @@
 
 #include "tensorflow/contrib/lite/context.h"
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace TensorFlowSum
 {
 
@@ -36,9 +34,8 @@ TfLiteStatus PrepareTensorFlowSum(TfLiteContext *context, TfLiteNode *node);
 TfLiteStatus EvalTensorFlowSum(TfLiteContext *context, TfLiteNode *node);
 
 } // namespace TensorFlowSum
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_TENSORFLOW_SUM_H__

diff --git a/libs/tflite/include/tflite/ext/kernels/register.h b/libs/tflite/include/tflite/ext/kernels/register.h
index b1884fe..124af7a 100644 (file)
--- a/libs/tflite/include/tflite/ext/kernels/register.h
+++ b/libs/tflite/include/tflite/ext/kernels/register.h
@@ -26,19 +26,16 @@ limitations under the License.
 #include "tensorflow/contrib/lite/context.h"
 #include "tensorflow/contrib/lite/model.h"
 
-// TODO Use namespace nnfw
+namespace nnfw {
 namespace tflite {
-namespace ops {
-namespace builtin {
 
-class BuiltinOpResolver : public MutableOpResolver {
+class BuiltinOpResolver : public ::tflite::MutableOpResolver {
  public:
   BuiltinOpResolver();
 };
 
-}  // namespace builtin
-}  // namespace ops
 }  // namespace tflite
+}  // namespace nnfw
 
 #endif // __NNFW_TFLITE_EXT_KERNELS_REGISTER_H__
 

diff --git a/libs/tflite/include/tflite/ext/nnapi_delegate.h b/libs/tflite/include/tflite/ext/nnapi_delegate.h
index 076975c..3aac01a 100644 (file)
--- a/libs/tflite/include/tflite/ext/nnapi_delegate.h
+++ b/libs/tflite/include/tflite/ext/nnapi_delegate.h
@@ -38,6 +38,7 @@ class ANeuralNetworksMemory;
 class ANeuralNetworksCompilation;
 
 namespace nnfw {
+namespace tflite {
 
 class NNAPIAllocation : public ::tflite::MMAPAllocation {
  public:
@@ -88,6 +89,7 @@ class NNAPIDelegate {
   std::vector<int> model_states_outputs_;  // holds TFLite tensor ids
 };
 
+} // namespace tflite
 } // namespace nnfw
 
 #endif  // __NNFW_TFLITE_EXT_NNAPI_DELEGATE_H__

diff --git a/libs/tflite/src/Diff.cpp b/libs/tflite/src/Diff.cpp
index 3759c66..f652eab 100644 (file)
--- a/libs/tflite/src/Diff.cpp
+++ b/libs/tflite/src/Diff.cpp
@@ -535,7 +535,7 @@ int RandomTestRunner::run(const nnfw::tflite::Builder &builder)
   }
   else
   {
-    nnfw::NNAPIDelegate d;
+    nnfw::tflite::NNAPIDelegate d;
 
     if (d.BuildGraph(nnapi.get()))
     {

diff --git a/libs/tflite/src/ext/kernels/Abs.cpp b/libs/tflite/src/ext/kernels/Abs.cpp
index 047fead..7e9c233 100644 (file)
--- a/libs/tflite/src/ext/kernels/Abs.cpp
+++ b/libs/tflite/src/ext/kernels/Abs.cpp
@@ -20,14 +20,12 @@
 #include <iostream>
 #include <cmath>
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace Abs
 {
 
@@ -37,11 +35,11 @@ void FreeAbs(TfLiteContext *context, void *buffer) {}
 
 TfLiteStatus PrepareAbs(TfLiteContext *context, TfLiteNode *node)
 {
-  TF_LITE_ENSURE_EQ(context, NumInputs(node), 1);
-  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumInputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumOutputs(node), 1);
 
-  const TfLiteTensor *input = GetInput(context, node, 0);
-  TfLiteTensor *output = GetOutput(context, node, 0);
+  const TfLiteTensor *input = ::tflite::GetInput(context, node, 0);
+  TfLiteTensor *output = ::tflite::GetOutput(context, node, 0);
 
   TF_LITE_ENSURE_EQ(context, input->type, output->type);
 
@@ -50,9 +48,9 @@ TfLiteStatus PrepareAbs(TfLiteContext *context, TfLiteNode *node)
 
 TfLiteStatus EvalAbs(TfLiteContext *context, TfLiteNode *node)
 {
-  const TfLiteTensor *input = GetInput(context, node, 0);
-  TfLiteTensor *output = GetOutput(context, node, 0);
-  size_t elements = NumElements(input);
+  const TfLiteTensor *input = ::tflite::GetInput(context, node, 0);
+  TfLiteTensor *output = ::tflite::GetOutput(context, node, 0);
+  size_t elements = ::tflite::NumElements(input);
   switch (input->type)
   {
     case kTfLiteFloat32:
@@ -100,7 +98,6 @@ TfLiteStatus EvalAbs(TfLiteContext *context, TfLiteNode *node)
 }
 
 } // namespace Abs
-} // nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw

diff --git a/libs/tflite/src/ext/kernels/SquaredDifference.cpp b/libs/tflite/src/ext/kernels/SquaredDifference.cpp
index 9cecdeb..8ac2b1d 100644 (file)
--- a/libs/tflite/src/ext/kernels/SquaredDifference.cpp
+++ b/libs/tflite/src/ext/kernels/SquaredDifference.cpp
@@ -19,14 +19,12 @@
 
 #include <iostream>
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace SquaredDifference
 {
 
@@ -39,12 +37,12 @@ void FreeSquaredDifference(TfLiteContext *context, void *buffer) {}
 
 TfLiteStatus PrepareSquaredDifference(TfLiteContext *context, TfLiteNode *node)
 {
-  TF_LITE_ENSURE_EQ(context, NumInputs(node), 2);
-  TF_LITE_ENSURE_EQ(context, NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumInputs(node), 2);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumOutputs(node), 1);
 
-  const TfLiteTensor *input1 = GetInput(context, node, 0);
-  const TfLiteTensor *input2 = GetInput(context, node, 1);
-  TfLiteTensor *output = GetOutput(context, node, 0);
+  const TfLiteTensor *input1 = ::tflite::GetInput(context, node, 0);
+  const TfLiteTensor *input2 = ::tflite::GetInput(context, node, 1);
+  TfLiteTensor *output = ::tflite::GetOutput(context, node, 0);
 
   TF_LITE_ENSURE_EQ(context, input1->type, input2->type);
   TF_LITE_ENSURE_EQ(context, input1->type, output->type);
@@ -55,12 +53,12 @@ TfLiteStatus PrepareSquaredDifference(TfLiteContext *context, TfLiteNode *node)
 TfLiteStatus EvalSquaredDifference(TfLiteContext *context, TfLiteNode *node)
 {
 
-  const TfLiteTensor *input1 = GetInput(context, node, 0);
-  const TfLiteTensor *input2 = GetInput(context, node, 1);
+  const TfLiteTensor *input1 = ::tflite::GetInput(context, node, 0);
+  const TfLiteTensor *input2 = ::tflite::GetInput(context, node, 1);
 
-  TfLiteTensor *output = GetOutput(context, node, 0);
+  TfLiteTensor *output = ::tflite::GetOutput(context, node, 0);
 
-  size_t elements = NumElements(input1);
+  size_t elements = ::tflite::NumElements(input1);
 
   switch (input1->type)
   {
@@ -109,7 +107,6 @@ TfLiteStatus EvalSquaredDifference(TfLiteContext *context, TfLiteNode *node)
 }
 
 } // namespace SquaredDifference
-} // nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw

diff --git a/libs/tflite/src/ext/kernels/TensorFlowMax.cpp b/libs/tflite/src/ext/kernels/TensorFlowMax.cpp
index 2817175..d72ad24 100644 (file)
--- a/libs/tflite/src/ext/kernels/TensorFlowMax.cpp
+++ b/libs/tflite/src/ext/kernels/TensorFlowMax.cpp
@@ -19,14 +19,12 @@
 
 #include <iostream>
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace TensorFlowMax
 {
 
@@ -34,9 +32,9 @@ struct TensorFlowMaxOp
 {
   TensorFlowMaxOp(TfLiteContext *context, TfLiteNode *node)
   {
-    input = tflite::GetInput(context, node, 0);
-    axis = tflite::GetInput(context, node, 1);
-    output = tflite::GetOutput(context, node, 0);
+    input = ::tflite::GetInput(context, node, 0);
+    axis = ::tflite::GetInput(context, node, 1);
+    output = ::tflite::GetOutput(context, node, 0);
   }
   const TfLiteTensor *input;
   const TfLiteTensor *axis;
@@ -62,16 +60,16 @@ TfLiteStatus ResizeTempAxis(TfLiteContext *context, TensorFlowMaxOp *op_context,
                             TfLiteTensor *resolved_axis)
 {
   TfLiteIntArray *axis_size = TfLiteIntArrayCreate(1);
-  axis_size->data[0] = static_cast<int>(tflite::NumElements(op_context->axis));
+  axis_size->data[0] = static_cast<int>(::tflite::NumElements(op_context->axis));
   return context->ResizeTensor(context, resolved_axis, axis_size);
 }
 
 // Resizes output array based on the input size and resolved axis.
 TfLiteStatus ResizeOutputTensor(TfLiteContext *context, TensorFlowMaxOp *op_context)
 {
-  size_t num_axis = tflite::NumElements(op_context->axis);
+  size_t num_axis = ::tflite::NumElements(op_context->axis);
   TfLiteIntArray *input_dims = op_context->input->dims;
-  int input_num_dims = tflite::NumDimensions(op_context->input);
+  int input_num_dims = ::tflite::NumDimensions(op_context->input);
   const int *axis = op_context->axis->data.i32;
 
   {
@@ -100,7 +98,7 @@ TfLiteStatus ResizeOutputTensor(TfLiteContext *context, TensorFlowMaxOp *op_cont
       }
     }
     // Determines output dimensions.
-    int output_num_dims = tflite::NumDimensions(op_context->output);
+    int output_num_dims = ::tflite::NumDimensions(op_context->output);
     TF_LITE_ENSURE(context, (input_num_dims == output_num_dims) ||
                                 (input_num_dims - num_reduce_axis == output_num_dims));
 
@@ -153,7 +151,7 @@ TfLiteStatus InitializeTemporaries(TfLiteContext *context, TfLiteNode *node,
   scratch_tensor->type = kTfLiteInt32;
   scratch_tensor->allocation_type = kTfLiteArenaRw;
   TfLiteIntArray *index_size = TfLiteIntArrayCreate(1);
-  index_size->data[0] = tflite::NumDimensions(op_context->input);
+  index_size->data[0] = ::tflite::NumDimensions(op_context->input);
   TF_LITE_ENSURE_OK(context, context->ResizeTensor(context, scratch_tensor, index_size));
 
   // Creates a temp tensor to store resolved axis given input data.
@@ -165,18 +163,18 @@ TfLiteStatus InitializeTemporaries(TfLiteContext *context, TfLiteNode *node,
 
 TfLiteStatus PrepareTensorFlowMax(TfLiteContext *context, TfLiteNode *node)
 {
-  TF_LITE_ENSURE_EQ(context, tflite::NumInputs(node), 2);
-  TF_LITE_ENSURE_EQ(context, tflite::NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumInputs(node), 2);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumOutputs(node), 1);
 
   TensorFlowMaxOp op_context(context, node);
   TF_LITE_ENSURE_OK(context, InitializeTemporaries(context, node, &op_context));
 
   TfLiteTensor *resolved_axis = &context->tensors[node->temporaries->data[1]];
   // Leaves work to Eval if axis is not constant; else resizes output.
-  if (!tflite::IsConstantTensor(op_context.axis))
+  if (!::tflite::IsConstantTensor(op_context.axis))
   {
-    tflite::SetTensorToDynamic(op_context.output);
-    tflite::SetTensorToDynamic(resolved_axis);
+    ::tflite::SetTensorToDynamic(op_context.output);
+    ::tflite::SetTensorToDynamic(resolved_axis);
     return kTfLiteOk;
   }
   resolved_axis->allocation_type = kTfLiteArenaRw;
@@ -353,11 +351,11 @@ TfLiteStatus EvalTensorFlowMax(TfLiteContext *context, TfLiteNode *node)
 {
 
   TensorFlowMaxOp op_context(context, node);
-  int num_axis = static_cast<int>(tflite::NumElements(op_context.axis));
+  int num_axis = static_cast<int>(::tflite::NumElements(op_context.axis));
   TfLiteTensor *temp_index = &context->tensors[node->temporaries->data[0]];
   TfLiteTensor *resolved_axis = &context->tensors[node->temporaries->data[1]];
   // Resize the output tensor if the output tensor is dynamic.
-  if (tflite::IsDynamicTensor(op_context.output))
+  if (::tflite::IsDynamicTensor(op_context.output))
   {
     TF_LITE_ENSURE_OK(context, ResizeTempAxis(context, &op_context, resolved_axis));
     TF_LITE_ENSURE_OK(context, ResizeOutputTensor(context, &op_context));
@@ -400,8 +398,8 @@ TfLiteStatus EvalTensorFlowMax(TfLiteContext *context, TfLiteNode *node)
 
   return returnStatus;
 }
+
 } // namespace TensorFlowMax
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw

diff --git a/libs/tflite/src/ext/kernels/TensorFlowSum.cpp b/libs/tflite/src/ext/kernels/TensorFlowSum.cpp
index da614ab..cbf9797 100644 (file)
--- a/libs/tflite/src/ext/kernels/TensorFlowSum.cpp
+++ b/libs/tflite/src/ext/kernels/TensorFlowSum.cpp
@@ -19,14 +19,12 @@
 
 #include <iostream>
 
-namespace tflite
+namespace nnfw
 {
-namespace ops
+namespace tflite
 {
 namespace custom
 {
-namespace nnfw
-{
 namespace TensorFlowSum
 {
 
@@ -34,9 +32,9 @@ struct TensorFlowSumOp
 {
   TensorFlowSumOp(TfLiteContext *context, TfLiteNode *node)
   {
-    input = tflite::GetInput(context, node, 0);
-    axis = tflite::GetInput(context, node, 1);
-    output = tflite::GetOutput(context, node, 0);
+    input = ::tflite::GetInput(context, node, 0);
+    axis = ::tflite::GetInput(context, node, 1);
+    output = ::tflite::GetOutput(context, node, 0);
   }
   const TfLiteTensor *input;
   const TfLiteTensor *axis;
@@ -62,16 +60,16 @@ TfLiteStatus ResizeTempAxis(TfLiteContext *context, TensorFlowSumOp *op_context,
                             TfLiteTensor *resolved_axis)
 {
   TfLiteIntArray *axis_size = TfLiteIntArrayCreate(1);
-  axis_size->data[0] = static_cast<int>(tflite::NumElements(op_context->axis));
+  axis_size->data[0] = static_cast<int>(::tflite::NumElements(op_context->axis));
   return context->ResizeTensor(context, resolved_axis, axis_size);
 }
 
 // Resizes output array based on the input size and resolved axis.
 TfLiteStatus ResizeOutputTensor(TfLiteContext *context, TensorFlowSumOp *op_context)
 {
-  size_t num_axis = tflite::NumElements(op_context->axis);
+  size_t num_axis = ::tflite::NumElements(op_context->axis);
   TfLiteIntArray *input_dims = op_context->input->dims;
-  int input_num_dims = tflite::NumDimensions(op_context->input);
+  int input_num_dims = ::tflite::NumDimensions(op_context->input);
   const int *axis = op_context->axis->data.i32;
 
   {
@@ -100,7 +98,7 @@ TfLiteStatus ResizeOutputTensor(TfLiteContext *context, TensorFlowSumOp *op_cont
       }
     }
     // Determines output dimensions.
-    int output_num_dims = tflite::NumDimensions(op_context->output);
+    int output_num_dims = ::tflite::NumDimensions(op_context->output);
     TF_LITE_ENSURE(context, (input_num_dims == output_num_dims) ||
                                 (input_num_dims - num_reduce_axis == output_num_dims));
 
@@ -153,7 +151,7 @@ TfLiteStatus InitializeTemporaries(TfLiteContext *context, TfLiteNode *node,
   scratch_tensor->type = kTfLiteInt32;
   scratch_tensor->allocation_type = kTfLiteArenaRw;
   TfLiteIntArray *index_size = TfLiteIntArrayCreate(1);
-  index_size->data[0] = tflite::NumDimensions(op_context->input);
+  index_size->data[0] = ::tflite::NumDimensions(op_context->input);
   TF_LITE_ENSURE_OK(context, context->ResizeTensor(context, scratch_tensor, index_size));
 
   // Creates a temp tensor to store resolved axis given input data.
@@ -165,18 +163,18 @@ TfLiteStatus InitializeTemporaries(TfLiteContext *context, TfLiteNode *node,
 
 TfLiteStatus PrepareTensorFlowSum(TfLiteContext *context, TfLiteNode *node)
 {
-  TF_LITE_ENSURE_EQ(context, tflite::NumInputs(node), 2);
-  TF_LITE_ENSURE_EQ(context, tflite::NumOutputs(node), 1);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumInputs(node), 2);
+  TF_LITE_ENSURE_EQ(context, ::tflite::NumOutputs(node), 1);
 
   TensorFlowSumOp op_context(context, node);
   TF_LITE_ENSURE_OK(context, InitializeTemporaries(context, node, &op_context));
 
   TfLiteTensor *resolved_axis = &context->tensors[node->temporaries->data[1]];
   // Leaves work to Eval if axis is not constant; else resizes output.
-  if (!tflite::IsConstantTensor(op_context.axis))
+  if (!::tflite::IsConstantTensor(op_context.axis))
   {
-    tflite::SetTensorToDynamic(op_context.output);
-    tflite::SetTensorToDynamic(resolved_axis);
+    ::tflite::SetTensorToDynamic(op_context.output);
+    ::tflite::SetTensorToDynamic(resolved_axis);
     return kTfLiteOk;
   }
   resolved_axis->allocation_type = kTfLiteArenaRw;
@@ -348,11 +346,11 @@ TfLiteStatus EvalTensorFlowSum(TfLiteContext *context, TfLiteNode *node)
 {
 
   TensorFlowSumOp op_context(context, node);
-  int num_axis = static_cast<int>(tflite::NumElements(op_context.axis));
+  int num_axis = static_cast<int>(::tflite::NumElements(op_context.axis));
   TfLiteTensor *temp_index = &context->tensors[node->temporaries->data[0]];
   TfLiteTensor *resolved_axis = &context->tensors[node->temporaries->data[1]];
   // Resize the output tensor if the output tensor is dynamic.
-  if (tflite::IsDynamicTensor(op_context.output))
+  if (::tflite::IsDynamicTensor(op_context.output))
   {
     TF_LITE_ENSURE_OK(context, ResizeTempAxis(context, &op_context, resolved_axis));
     TF_LITE_ENSURE_OK(context, ResizeOutputTensor(context, &op_context));
@@ -395,8 +393,8 @@ TfLiteStatus EvalTensorFlowSum(TfLiteContext *context, TfLiteNode *node)
 
   return returnStatus;
 }
+
 } // namespace TensorFlowSum
-} // namespace nnfw
 } // namespace custom
-} // namespace ops
 } // namespace tflite
+} // namespace nnfw

diff --git a/libs/tflite/src/ext/kernels/register.cpp b/libs/tflite/src/ext/kernels/register.cpp
index ed4cd2c..b822bd6 100644 (file)
--- a/libs/tflite/src/ext/kernels/register.cpp
+++ b/libs/tflite/src/ext/kernels/register.cpp
@@ -14,18 +14,17 @@ See the License for the specific language governing permissions and
 limitations under the License.
 ==============================================================================*/
 
+// NOTE To minimize diff with upstream tensorflow, disable clang-format
+// clang-format off
+
 // NOTE This code is derived from the following file (in TensorFlow)
 //        'externals/tensorflow/tensorflow/contrib/lite/kernels/register.cc'
 #include "tflite/ext/kernels/register.h"
 #include "tflite/ext/kernels/CustomOps.h"
 
-// TODO Use namespace nnfw
-namespace tflite
-{
-namespace ops
-{
-namespace builtin
-{
+namespace tflite {
+namespace ops {
+namespace builtin {
 
 TfLiteRegistration *Register_RELU();
 TfLiteRegistration *Register_RELU_N1_TO_1();
@@ -113,8 +112,19 @@ TfLiteRegistration *Register_SQUARE();
 TfLiteRegistration *Register_ZEROS_LIKE();
 #endif // OBS_BUILD
 
+}  // namespace builtin
+}  // namespace ops
+}  // namespace tflite
+
+namespace nnfw {
+namespace tflite {
+
 BuiltinOpResolver::BuiltinOpResolver()
 {
+  // Using namespace directive to minimize diff with upstream tensorflow
+  using namespace ::tflite::ops::builtin;
+  using namespace ::tflite;
+
   AddBuiltin(BuiltinOperator_RELU, Register_RELU());
   AddBuiltin(BuiltinOperator_RELU_N1_TO_1, Register_RELU_N1_TO_1());
   AddBuiltin(BuiltinOperator_RELU6, Register_RELU6());
@@ -201,12 +211,11 @@ BuiltinOpResolver::BuiltinOpResolver()
   AddBuiltin(BuiltinOperator_ZEROS_LIKE, Register_ZEROS_LIKE());
 #endif // OBS_BUILD
 
-  AddCustom("TensorFlowMax", tflite::ops::custom::nnfw::Register_TensorFlowMax());
-  AddCustom("SquaredDifference", tflite::ops::custom::nnfw::Register_SquaredDifference());
-  AddCustom("TensorFlowSum", tflite::ops::custom::nnfw::Register_TensorFlowSum());
-  AddCustom("Abs", tflite::ops::custom::nnfw::Register_Abs());
+  AddCustom("TensorFlowMax", nnfw::tflite::custom::Register_TensorFlowMax());
+  AddCustom("SquaredDifference", nnfw::tflite::custom::Register_SquaredDifference());
+  AddCustom("TensorFlowSum", nnfw::tflite::custom::Register_TensorFlowSum());
+  AddCustom("Abs", nnfw::tflite::custom::Register_Abs());
 }
 
-} // namespace builtin
-} // namespace ops
-} // namespace tflite
+}  // namespace tflite
+}  // namespace nnfw

diff --git a/libs/tflite/src/ext/nnapi_delegate.cpp b/libs/tflite/src/ext/nnapi_delegate.cpp
index 0cc5a74..25858a7 100644 (file)
--- a/libs/tflite/src/ext/nnapi_delegate.cpp
+++ b/libs/tflite/src/ext/nnapi_delegate.cpp
@@ -41,6 +41,7 @@ limitations under the License.
 #endif
 
 namespace nnfw {
+namespace tflite {
 
 void logError(const char* format, ...) {
   // stderr is convenient for native tests, but is not captured for apps
@@ -155,7 +156,7 @@ NNAPIDelegate::~NNAPIDelegate() {
 }
 
 // Adds the tensors of the interpreter to the NN API model.
-TfLiteStatus addTensorOperands(tflite::Interpreter* interpreter,
+TfLiteStatus addTensorOperands(::tflite::Interpreter* interpreter,
                                ANeuralNetworksModel* nn_model,
                                uint32_t* no_of_operands_added,
                                std::vector<int64_t>* nnapi_ids) {
@@ -248,7 +249,7 @@ TfLiteStatus addTensorOperands(tflite::Interpreter* interpreter,
     // only memory
     if (tensor->allocation_type == kTfLiteMmapRo) {
       if (const NNAPIAllocation* alloc = dynamic_cast<const NNAPIAllocation*>(
-              static_cast<const tflite::Allocation*>(tensor->allocation))) {
+              static_cast<const ::tflite::Allocation*>(tensor->allocation))) {
         RETURN_ERROR_IF_NN_FAILED(
             ANeuralNetworksModel_setOperandValueFromMemory(
                 nn_model, next_id, alloc->memory(),
@@ -285,7 +286,7 @@ void MapAndAddTensorIds(const int* from_ids_buf, size_t from_ids_count,
 // Adds the operations and their parameters to the NN API model.
 // 'next-id' is the operand ID of the next operand of the model.
 TfLiteStatus AddOpsAndParams(
-    tflite::Interpreter* interpreter, ANeuralNetworksModel* nn_model,
+    ::tflite::Interpreter* interpreter, ANeuralNetworksModel* nn_model,
     uint32_t next_id, std::vector<int>* model_state_inputs,
     std::vector<int>* model_state_outputs,
     const std::vector<int64_t>& tensor_id_to_nnapi_id) {
@@ -293,8 +294,8 @@ TfLiteStatus AddOpsAndParams(
     const auto* node_and_registration = interpreter->node_and_registration(i);
     const TfLiteNode& node = node_and_registration->first;
     const TfLiteRegistration& registration = node_and_registration->second;
-    tflite::BuiltinOperator builtin =
-        static_cast<tflite::BuiltinOperator>(registration.builtin_code);
+    ::tflite::BuiltinOperator builtin =
+        static_cast<::tflite::BuiltinOperator>(registration.builtin_code);
 
     // Add the parameters.
     std::vector<uint32_t> augmented_inputs, augmented_outputs;
@@ -495,6 +496,9 @@ TfLiteStatus AddOpsAndParams(
 
     ANeuralNetworksOperationType nn_op_type;
 
+    // Using namespace directive to minimize diff with upstream tensorflow
+    namespace tflite = ::tflite;
+
     switch (builtin) {
       case tflite::BuiltinOperator_ADD:
         nn_op_type = ANEURALNETWORKS_ADD;
@@ -1199,6 +1203,7 @@ TfLiteStatus NNAPIDelegate::Invoke(::tflite::Interpreter* interpreter) {
 
 bool NNAPIDelegate::IsSupported() { return nnfw::NNAPIExists(); }
 
+} // namespace tflite
 } // namespace nnfw
 
 // clang-format on

diff --git a/libs/tflite/src/interp/FlatBufferBuilder.cpp b/libs/tflite/src/interp/FlatBufferBuilder.cpp
index 84246d3..4b9cde7 100644 (file)
--- a/libs/tflite/src/interp/FlatBufferBuilder.cpp
+++ b/libs/tflite/src/interp/FlatBufferBuilder.cpp
@@ -27,7 +27,7 @@ std::unique_ptr<::tflite::Interpreter> FlatBufferBuilder::build(void) const
 {
   std::unique_ptr<::tflite::Interpreter> interpreter;
 
-  ::tflite::ops::builtin::BuiltinOpResolver resolver;
+  nnfw::tflite::BuiltinOpResolver resolver;
 
   ::tflite::InterpreterBuilder builder(_model, resolver);
 

diff --git a/tools/nnapi_test/src/nnapi_test.cc b/tools/nnapi_test/src/nnapi_test.cc
index 31452b2..73e80f0 100644 (file)
--- a/tools/nnapi_test/src/nnapi_test.cc
+++ b/tools/nnapi_test/src/nnapi_test.cc
@@ -24,7 +24,7 @@
 #include <stdexcept>
 
 using namespace tflite;
-using namespace tflite::ops::builtin;
+using namespace nnfw::tflite;
 
 int main(const int argc, char **argv)
 {

diff --git a/tools/tflite_benchmark/src/tflite_benchmark.cc b/tools/tflite_benchmark/src/tflite_benchmark.cc
index 30400a3..ba447e2 100644 (file)
--- a/tools/tflite_benchmark/src/tflite_benchmark.cc
+++ b/tools/tflite_benchmark/src/tflite_benchmark.cc
@@ -36,7 +36,7 @@
 #include "util/benchmark.h"
 
 using namespace tflite;
-using namespace tflite::ops::builtin;
+using namespace nnfw::tflite;
 
 void help(std::ostream &out, const int argc, char **argv)
 {

diff --git a/tools/tflite_benchmark_model/benchmark_tflite_model.cc b/tools/tflite_benchmark_model/benchmark_tflite_model.cc
index 5524eab..e37fa49 100644 (file)
--- a/tools/tflite_benchmark_model/benchmark_tflite_model.cc
+++ b/tools/tflite_benchmark_model/benchmark_tflite_model.cc
@@ -53,7 +53,7 @@ limitations under the License.
 #include "tflite/ext/nnapi_delegate.h"
 
 namespace {
-  nnfw::NNAPIDelegate nnfw_delegate_;
+  nnfw::tflite::NNAPIDelegate nnfw_delegate_;
 }
 
 #ifdef TFLITE_CUSTOM_OPS_HEADER
@@ -310,7 +310,7 @@ void BenchmarkTfLiteModel::Init() {
   tflite::MutableOpResolver resolver;
   RegisterSelectedOps(&resolver);
 #else
-  tflite::ops::builtin::BuiltinOpResolver resolver;
+  nnfw::tflite::BuiltinOpResolver resolver;
 #endif
 
   tflite::InterpreterBuilder(*model, resolver)(&interpreter);

diff --git a/tools/tflite_examples/src/conv.cpp b/tools/tflite_examples/src/conv.cpp
index 43693b9..e517da9 100644 (file)
--- a/tools/tflite_examples/src/conv.cpp
+++ b/tools/tflite_examples/src/conv.cpp
@@ -21,7 +21,7 @@
 #include <iostream>
 
 using namespace tflite;
-using namespace tflite::ops::builtin;
+using namespace nnfw::tflite;
 
 namespace vector
 {

diff --git a/tools/tflite_run/src/tflite_run.cc b/tools/tflite_run/src/tflite_run.cc
index 26e5219..0e70018 100644 (file)
--- a/tools/tflite_run/src/tflite_run.cc
+++ b/tools/tflite_run/src/tflite_run.cc
@@ -37,7 +37,7 @@
 #include <algorithm>
 
 using namespace tflite;
-using namespace tflite::ops::builtin;
+using namespace nnfw::tflite;
 using namespace std::placeholders; // for _1, _2 ...
 
 void print_max_idx(float *f, int size)