[neurun] Apply Graph IR (#2244)

This commit replaces `internal::tflite::Model` with
`neurun::graph::Graph`.

Resolve #2155

Signed-off-by: Hanjoung Lee <hanjoung.lee@samsung.com>

diff --git a/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.cc b/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.cc
index e27e4f9..ff49209 100644 (file)
--- a/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.cc
+++ b/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.cc
@@ -13,7 +13,7 @@ namespace backend
 namespace acl_cl
 {
 
-InitializerGenerator::InitializerGenerator(const ::internal::tflite::operand::Set &ctx) : _ctx(ctx)
+InitializerGenerator::InitializerGenerator(const neurun::graph::operand::Set &ctx) : _ctx(ctx)
 {
   // DO NOTHING
 }

diff --git a/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.h b/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.h
index 6884c90..a93fa29 100644 (file)
--- a/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.h
+++ b/runtimes/neurun/src/backend/acl_cl/InitializerGenerator.h
@@ -3,7 +3,7 @@
 
 #include "internal/IInitializerGenerator.h"
 
-#include "internal/Model.h"
+#include "graph/operand/Set.h"
 
 namespace neurun
 {
@@ -15,7 +15,7 @@ namespace acl_cl
 class InitializerGenerator : public ::internal::IInitializerGenerator
 {
 public:
-  InitializerGenerator(const ::internal::tflite::operand::Set &ctx);
+  InitializerGenerator(const neurun::graph::operand::Set &ctx);
 
   Initializer generateWeight(const ::internal::tflite::op::Conv2D::implicit::Node &node) override;
   Initializer generateWeight(const ::internal::tflite::op::FullyConnected::Node &node) override;
@@ -24,7 +24,7 @@ public:
   Initializer generateBias(const ::internal::tflite::op::FullyConnected::Node &node) override;
 
 private:
-  const ::internal::tflite::operand::Set &_ctx;
+  const neurun::graph::operand::Set &_ctx;
 };
 
 } // namespace acl_cl

diff --git a/runtimes/neurun/src/backend/acl_cl/StageGenerator.cc b/runtimes/neurun/src/backend/acl_cl/StageGenerator.cc
index 73d022a..4e229d4 100644 (file)
--- a/runtimes/neurun/src/backend/acl_cl/StageGenerator.cc
+++ b/runtimes/neurun/src/backend/acl_cl/StageGenerator.cc
@@ -99,8 +99,7 @@ void ActivationBuilder::append(FuseCode code, ::arm_compute::ICLTensor *ifm_allo
 // StageGenerator
 //
 StageGenerator::StageGenerator(
-    const ::internal::tflite::operand::Set &ctx,
-    const std::shared_ptr<TensorBuilder> &tensor_builder,
+    const neurun::graph::operand::Set &ctx, const std::shared_ptr<TensorBuilder> &tensor_builder,
     const std::shared_ptr<::internal::common::TensorBuilder> &common_tensor_builder)
     : _ctx(ctx), _tensor_builder(tensor_builder), _common_tensor_builder(common_tensor_builder)
 {

diff --git a/runtimes/neurun/src/backend/acl_cl/StageGenerator.h b/runtimes/neurun/src/backend/acl_cl/StageGenerator.h
index 6f1dadf..f1bfaaf 100644 (file)
--- a/runtimes/neurun/src/backend/acl_cl/StageGenerator.h
+++ b/runtimes/neurun/src/backend/acl_cl/StageGenerator.h
@@ -3,7 +3,7 @@
 
 #include "internal/IStageGenerator.h"
 
-#include "internal/Model.h"
+#include "graph/operand/Set.h"
 #include "backend/acl_cl/TensorBuilder.h"
 #include "internal/common/TensorBuilder.h"
 
@@ -17,7 +17,7 @@ namespace acl_cl
 class StageGenerator : public ::internal::IStageGenerator
 {
 public:
-  StageGenerator(const ::internal::tflite::operand::Set &ctx,
+  StageGenerator(const neurun::graph::operand::Set &ctx,
                  const std::shared_ptr<TensorBuilder> &tensor_builder,
                  const std::shared_ptr<::internal::common::TensorBuilder> &common_tensor_builder);
 
@@ -43,7 +43,7 @@ public:
   generate(const ::internal::tflite::op::TensorConvert::AclToCommon::Node &node) override;
 
 private:
-  const ::internal::tflite::operand::Set &_ctx;
+  const neurun::graph::operand::Set &_ctx;
   std::shared_ptr<TensorBuilder> _tensor_builder;
   std::shared_ptr<::internal::common::TensorBuilder> _common_tensor_builder;
 };

diff --git a/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc b/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc
index 2af84a2..970dd9f 100644 (file)
--- a/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc
+++ b/runtimes/neurun/src/backend/cpu/InitializerGenerator.cc
@@ -13,7 +13,7 @@ namespace backend
 namespace cpu
 {
 
-InitializerGenerator::InitializerGenerator(const ::internal::tflite::operand::Set &ctx) : _ctx(ctx)
+InitializerGenerator::InitializerGenerator(const neurun::graph::operand::Set &ctx) : _ctx(ctx)
 {
   // DO NOTHING
 }

diff --git a/runtimes/neurun/src/backend/cpu/InitializerGenerator.h b/runtimes/neurun/src/backend/cpu/InitializerGenerator.h
index 2ce8e4a..dd621ee 100644 (file)
--- a/runtimes/neurun/src/backend/cpu/InitializerGenerator.h
+++ b/runtimes/neurun/src/backend/cpu/InitializerGenerator.h
@@ -3,7 +3,7 @@
 
 #include "internal/IInitializerGenerator.h"
 
-#include "internal/Model.h"
+#include "graph/operand/Set.h"
 
 namespace neurun
 {
@@ -15,7 +15,7 @@ namespace cpu
 class InitializerGenerator : public ::internal::IInitializerGenerator
 {
 public:
-  InitializerGenerator(const ::internal::tflite::operand::Set &ctx);
+  InitializerGenerator(const neurun::graph::operand::Set &ctx);
 
   Initializer generateWeight(const ::internal::tflite::op::Conv2D::implicit::Node &node) override;
   Initializer generateWeight(const ::internal::tflite::op::FullyConnected::Node &node) override;
@@ -24,7 +24,7 @@ public:
   Initializer generateBias(const ::internal::tflite::op::FullyConnected::Node &node) override;
 
 private:
-  const ::internal::tflite::operand::Set &_ctx;
+  const neurun::graph::operand::Set &_ctx;
 };
 
 } // namespace cpu

diff --git a/runtimes/neurun/src/backend/cpu/StageGenerator.cc b/runtimes/neurun/src/backend/cpu/StageGenerator.cc
index 0993bda..66060e8 100644 (file)
--- a/runtimes/neurun/src/backend/cpu/StageGenerator.cc
+++ b/runtimes/neurun/src/backend/cpu/StageGenerator.cc
@@ -27,7 +27,7 @@ namespace cpu
 {
 
 StageGenerator::StageGenerator(
-    const ::internal::tflite::operand::Set &operand_ctx,
+    const neurun::graph::operand::Set &operand_ctx,
     const std::shared_ptr<TensorBuilder> &tensor_builder,
     const std::shared_ptr<::internal::common::TensorBuilder> &common_tensor_builder)
     : _ctx(operand_ctx), _tensor_builder(tensor_builder),

diff --git a/runtimes/neurun/src/backend/cpu/StageGenerator.h b/runtimes/neurun/src/backend/cpu/StageGenerator.h
index 7b33a4a..1426671 100644 (file)
--- a/runtimes/neurun/src/backend/cpu/StageGenerator.h
+++ b/runtimes/neurun/src/backend/cpu/StageGenerator.h
@@ -3,7 +3,7 @@
 
 #include "internal/IStageGenerator.h"
 
-#include "internal/Model.h"
+#include "graph/operand/Set.h"
 #include "internal/cpu.h"
 #include "TensorBuilder.h"
 
@@ -19,7 +19,7 @@ namespace cpu
 class StageGenerator : public ::internal::IStageGenerator
 {
 public:
-  StageGenerator(const ::internal::tflite::operand::Set &ctx,
+  StageGenerator(const neurun::graph::operand::Set &ctx,
                  const std::shared_ptr<TensorBuilder> &tensor_builder,
                  const std::shared_ptr<::internal::common::TensorBuilder> &common_tensor_builder);
 
@@ -45,7 +45,7 @@ public:
   generate(const ::internal::tflite::op::TensorConvert::AclToCommon::Node &node) override;
 
 private:
-  const ::internal::tflite::operand::Set &_ctx;
+  const neurun::graph::operand::Set &_ctx;
   std::shared_ptr<TensorBuilder> _tensor_builder;
   std::shared_ptr<::internal::common::TensorBuilder> _common_tensor_builder;
 };

diff --git a/runtimes/neurun/src/compilation.cc b/runtimes/neurun/src/compilation.cc
index c9efb42..990bf92 100644 (file)
--- a/runtimes/neurun/src/compilation.cc
+++ b/runtimes/neurun/src/compilation.cc
@@ -1,5 +1,6 @@
 #include <NeuralNetworks.h>
 
+#include <algorithm>
 #include <typeindex>
 
 #include <arm_compute/core/CL/ICLTensor.h>
@@ -166,7 +167,7 @@ std::shared_ptr<::internal::common::TensorBuilder> BackendResolver::getCommonTen
 class Planner : public ::internal::tflite::op::NodeVisitor
 {
 public:
-  Planner(const ::internal::tflite::operand::Set &ctx, IPlanBuilder &builder,
+  Planner(const neurun::graph::operand::Set &ctx, IPlanBuilder &builder,
           BackendResolver &backend_resolver)
       : _ctx{ctx}, _builder{builder}, _backend_resolver(backend_resolver)
   {
@@ -186,7 +187,7 @@ public:
   void visit(const ::internal::tflite::op::TensorConvert::AclToCommon::Node &node) override;
 
 private:
-  const ::internal::tflite::operand::Set &_ctx;
+  const neurun::graph::operand::Set &_ctx;
   IPlanBuilder &_builder;
   BackendResolver &_backend_resolver;
 };
@@ -609,9 +610,6 @@ void PlanBuilder::finalize(BackendResolver &backend_resolver)
   auto tensor_builders = backend_resolver.getAllTensorBuilders();
   auto common_tensor_builder = backend_resolver.getCommonTensorBuilder();
 
-  // Mark tensors
-  const auto &operations = _plan.model().operations();
-
   // Prepare tensors
   for (auto &tensor_builder : tensor_builders)
   {
@@ -656,7 +654,18 @@ int ANeuralNetworksCompilation::finish()
 
   auto &plan = this->plan();
   const auto &operands = plan.model().operands();
-  auto &operations = plan.model().operations();
+
+  // Get linearized ops
+  std::vector<const ::internal::tflite::op::Node *> operations;
+  {
+    plan.model().iteratePostDfs([&](const neurun::graph::operation::Node &node) {
+      auto op = node.op();
+      operations.emplace_back(op);
+      //      dynamic_cast<const ::internal::tflite::op::Conv2D::implicit::Node*>(op)
+    });
+
+    std::reverse(std::begin(operations), std::end(operations));
+  }
 
   ::internal::BackendManager backend_manager{plan};
   BackendResolver backend_resolver{backend_manager};
@@ -664,21 +673,24 @@ int ANeuralNetworksCompilation::finish()
 
   for (uint32_t n = 0; n < operations.size(); ++n)
   {
-    const auto &op = operations.at(n);
+    const auto &op = *operations.at(n);
     auto tensor_builder = backend_resolver.getTensorBuilder(typeid(op));
     op.accept(TensorMarker{*tensor_builder});
   }
 
+#if 0 // Tensor Conversion disabled
   auto tensor_builders = backend_resolver.getAllTensorBuilders();
 
   for (auto tensor_builder : tensor_builders)
   {
     tensor_builder->insertTensorConvertNodes(operations);
   }
+#endif
 
   for (uint32_t n = 0; n < operations.size(); ++n)
   {
-    operations.at(n).accept(Planner{operands, plan_builder, backend_resolver});
+    const auto &op = *operations.at(n);
+    op.accept(Planner{operands, plan_builder, backend_resolver});
   }
 
   // TODO Add optimization passes

diff --git a/runtimes/neurun/src/compilation.h b/runtimes/neurun/src/compilation.h
index dc7e00b..609d8a1 100644 (file)
--- a/runtimes/neurun/src/compilation.h
+++ b/runtimes/neurun/src/compilation.h
@@ -1,13 +1,13 @@
 #ifndef __COMPILATION_H__
 #define __COMPILATION_H__
 
-#include "internal/Model.h"
 #include "internal/Plan.h"
+#include "graph/Graph.h"
 
 struct ANeuralNetworksCompilation
 {
 public:
-  ANeuralNetworksCompilation(const std::shared_ptr<internal::tflite::Model> &model)
+  ANeuralNetworksCompilation(const std::shared_ptr<neurun::graph::Graph> &model)
       : _plan{new internal::Plan{model}}
   {
     // DO NOTHING

diff --git a/runtimes/neurun/src/execution.h b/runtimes/neurun/src/execution.h
index 45d2011..91b20a2 100644 (file)
--- a/runtimes/neurun/src/execution.h
+++ b/runtimes/neurun/src/execution.h
@@ -10,8 +10,8 @@ struct ANeuralNetworksExecution
 public:
   ANeuralNetworksExecution(const std::shared_ptr<const internal::Plan> &plan) : _plan{plan}
   {
-    _sources.resize(_plan->model().inputs.size());
-    _sinks.resize(_plan->model().outputs.size());
+    _sources.resize(_plan->model().inputs().size());
+    _sinks.resize(_plan->model().outputs().size());
   }
 
 public:

diff --git a/runtimes/neurun/src/frontend/compilation.cc b/runtimes/neurun/src/frontend/compilation.cc
index c0639a3..af14604 100644 (file)
--- a/runtimes/neurun/src/frontend/compilation.cc
+++ b/runtimes/neurun/src/frontend/compilation.cc
@@ -16,7 +16,7 @@ int ANeuralNetworksCompilation_create(ANeuralNetworksModel *model,
     return ANEURALNETWORKS_UNEXPECTED_NULL;
   }
 
-  std::shared_ptr<internal::tflite::Model> internal;
+  std::shared_ptr<neurun::graph::Graph> internal;
 
   model->release(internal);
 

diff --git a/runtimes/neurun/src/frontend/execution.cc b/runtimes/neurun/src/frontend/execution.cc
index a3d4ced..0a4de81 100644 (file)
--- a/runtimes/neurun/src/frontend/execution.cc
+++ b/runtimes/neurun/src/frontend/execution.cc
@@ -51,7 +51,7 @@ int ANeuralNetworksExecution_setInput(ANeuralNetworksExecution *execution, int32
 
   // NOTE The current implemenation assumes that every input is a feature map.
   // TODO Remove this assumption
-  const auto operand_index = execution->plan().model().inputs.at(index);
+  const auto operand_index = execution->plan().model().inputs().at(index);
 
   if (operands.at(operand_index).shape().rank() == 2)
   {
@@ -95,7 +95,7 @@ int ANeuralNetworksExecution_setOutput(ANeuralNetworksExecution *execution, int3
 
   // NOTE The current implemenation assumes that every output is a feature map.
   // TODO Remove this assumption
-  const auto operand_index = execution->plan().model().outputs.at(index);
+  const auto operand_index = execution->plan().model().outputs().list().at(index);
 
   if (operands.at(operand_index).shape().rank() == 2)
   {
@@ -138,11 +138,12 @@ int ANeuralNetworksExecution_startCompute(ANeuralNetworksExecution *execution,
   const auto &model = plan.model();
 
   // Set input(s)
-  for (uint32_t n = 0; n < model.inputs.size(); ++n)
+  for (uint32_t n = 0; n < model.inputs().size(); ++n)
   {
     auto setter = [&](::arm_compute::ITensor &tensor) { execution->source(n).push(tensor); };
 
-    auto objects = plan.common_operands().at(model.inputs.at(n));
+    ::internal::tflite::operand::Index index{model.inputs().at(n).asInt()};
+    auto objects = plan.operands().at(index);
 
     for (auto object : objects)
     {
@@ -158,11 +159,12 @@ int ANeuralNetworksExecution_startCompute(ANeuralNetworksExecution *execution,
   }
 
   // Get output(s)
-  for (uint32_t n = 0; n < model.outputs.size(); ++n)
+  for (uint32_t n = 0; n < model.outputs().size(); ++n)
   {
     auto getter = [&](::arm_compute::ITensor &tensor) { execution->sink(n).pull(tensor); };
 
-    auto objects = plan.common_operands().at(model.outputs.at(n));
+    ::internal::tflite::operand::Index index{model.outputs().at(n).asInt()};
+    auto objects = plan.operands().at(index);
 
     for (auto object : objects)
     {

diff --git a/runtimes/neurun/src/frontend/model.cc b/runtimes/neurun/src/frontend/model.cc
index 446b977..3900570 100644 (file)
--- a/runtimes/neurun/src/frontend/model.cc
+++ b/runtimes/neurun/src/frontend/model.cc
@@ -5,8 +5,18 @@
 #include <stdexcept>
 #include <new>
 
+#include "nnfw/std/memory.h"
+
+#include "graph/Graph.h"
 #include "model.h"
 #include "memory.h"
+#include "graph/operation/AvgPool2D.h"
+#include "graph/operation/Concat.h"
+#include "graph/operation/Conv2D.h"
+#include "graph/operation/FullyConnected.h"
+#include "graph/operation/MaxPool2D.h"
+#include "graph/operation/Reshape.h"
+#include "graph/operation/Softmax.h"
 
 int ANeuralNetworksModel_create(ANeuralNetworksModel **model)
 {
@@ -83,7 +93,7 @@ int ANeuralNetworksModel_addOperand(ANeuralNetworksModel *model,
 
   shape.set(type->type, type->scale, type->zeroPoint);
 
-  model->deref().operands().append(shape);
+  model->deref().addOperand(shape);
 
   // NOTE We do NOT allocate CLTensor here as we do not how to interpret this one.
   //      TensorFlow Lite may interpret a rank-4 tensor either as a feature map (with batch) or
@@ -105,16 +115,18 @@ int ANeuralNetworksModel_setOperandValue(ANeuralNetworksModel *model, int32_t in
     return ANEURALNETWORKS_BAD_STATE;
   }
 
-  const internal::tflite::operand::Index ind{index};
-  auto &obj = model->deref().operands().at(ind);
-
-  using internal::tflite::operand::CachedData;
+  const neurun::graph::operand::Index ind(index);
 
+  auto &obj = model->deref().operands().at(ind);
   if (!obj.setAsConstant())
   {
     return ANEURALNETWORKS_BAD_DATA;
   }
-  obj.data<CachedData>(reinterpret_cast<const uint8_t *>(buffer), length);
+
+  using internal::tflite::operand::CachedData;
+
+  model->deref().setOperandValue(
+      ind, nnfw::make_unique<CachedData>(reinterpret_cast<const uint8_t *>(buffer), length));
 
   return ANEURALNETWORKS_NO_ERROR;
 }
@@ -133,16 +145,19 @@ int ANeuralNetworksModel_setOperandValueFromMemory(ANeuralNetworksModel *model,
     return ANEURALNETWORKS_BAD_STATE;
   }
 
-  const internal::tflite::operand::Index ind{index};
-  auto &obj = model->deref().operands().at(ind);
-
-  using internal::tflite::operand::ExternalData;
+  const neurun::graph::operand::Index ind(index);
 
+  auto &obj = model->deref().operands().at(ind);
   if (!obj.setAsConstant())
   {
     return ANEURALNETWORKS_BAD_DATA;
   }
-  obj.data<ExternalData>(reinterpret_cast<const uint8_t *>(memory->base() + offset), length);
+
+  using internal::tflite::operand::ExternalData;
+
+  model->deref().setOperandValue(
+      ind, nnfw::make_unique<ExternalData>(
+               reinterpret_cast<const uint8_t *>(memory->base() + offset), length));
 
   return ANEURALNETWORKS_NO_ERROR;
 }
@@ -183,6 +198,8 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
     }
   }
 
+  auto &graph = model->deref();
+
   switch (type)
   {
     case ANEURALNETWORKS_CONV_2D:
@@ -197,11 +214,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
       {
         using internal::tflite::op::Conv2D::implicit::Param;
         using internal::tflite::op::Conv2D::implicit::Node;
+        using GraphNode = neurun::graph::operation::Conv2D::Implicit::Node;
 
-        // Add 'operations'
-        auto &operations = model->deref().operations();
-
-        operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+        graph.addOperation(nnfw::make_unique<GraphNode>(
+            nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
       }
       else
       {
@@ -222,11 +238,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
       {
         using internal::tflite::op::MaxPool2D::implicit::Param;
         using internal::tflite::op::MaxPool2D::implicit::Node;
+        using GraphNode = neurun::graph::operation::MaxPool2D::Implicit::Node;
 
-        // Add 'operations'
-        auto &operations = model->deref().operations();
-
-        operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+        graph.addOperation(nnfw::make_unique<GraphNode>(
+            nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
       }
       else
       {
@@ -247,11 +262,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
       {
         using internal::tflite::op::AvgPool2D::implicit::Param;
         using internal::tflite::op::AvgPool2D::implicit::Node;
+        using GraphNode = neurun::graph::operation::AvgPool2D::Implicit::Node;
 
-        // Add 'operations'
-        auto &operations = model->deref().operations();
-
-        operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+        graph.addOperation(nnfw::make_unique<GraphNode>(
+            nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
       }
       else
       {
@@ -264,11 +278,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
     {
       using internal::tflite::op::Concat::Param;
       using internal::tflite::op::Concat::Node;
+      using GraphNode = neurun::graph::operation::Concat::Node;
 
-      // Add 'operations'
-      auto &operations = model->deref().operations();
-
-      operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+      graph.addOperation(nnfw::make_unique<GraphNode>(
+          nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
 
       break;
     }
@@ -276,11 +289,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
     {
       using internal::tflite::op::Reshape::Param;
       using internal::tflite::op::Reshape::Node;
+      using GraphNode = neurun::graph::operation::Reshape::Node;
 
-      // Add 'operations'
-      auto &operations = model->deref().operations();
-
-      operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+      graph.addOperation(nnfw::make_unique<GraphNode>(
+          nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
 
       break;
     }
@@ -288,11 +300,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
     {
       using internal::tflite::op::FullyConnected::Param;
       using internal::tflite::op::FullyConnected::Node;
+      using GraphNode = neurun::graph::operation::FullyConnected::Node;
 
-      // Add 'operations'
-      auto &operations = model->deref().operations();
-
-      operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+      graph.addOperation(nnfw::make_unique<GraphNode>(
+          nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
 
       break;
     }
@@ -300,11 +311,10 @@ int ANeuralNetworksModel_addOperation(ANeuralNetworksModel *model,
     {
       using internal::tflite::op::Softmax::Param;
       using internal::tflite::op::Softmax::Node;
+      using GraphNode = neurun::graph::operation::Softmax::Node;
 
-      // Add 'operations'
-      auto &operations = model->deref().operations();
-
-      operations.emplace_back<Node>(Param{inputCount, inputs, outputCount, outputs});
+      graph.addOperation(nnfw::make_unique<GraphNode>(
+          nnfw::make_unique<Node>(Param{inputCount, inputs, outputCount, outputs})));
 
       break;
     }
@@ -381,8 +391,8 @@ int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel *model, u
   //      Below, static_cast<int>(...) is introduced to eliminate compiler warning.
   for (uint32_t n = 0; n < inputCount; ++n)
   {
-    const ::internal::tflite::operand::Index ind{static_cast<int>(inputs[n])};
-    model->deref().inputs.emplace_back(ind);
+    const neurun::graph::operand::Index ind{static_cast<uint32_t>(inputs[n])};
+    model->deref().addInput(ind);
 
     auto &obj = model->deref().operands().at(ind);
     if (!obj.setAsModelInput())
@@ -393,8 +403,8 @@ int ANeuralNetworksModel_identifyInputsAndOutputs(ANeuralNetworksModel *model, u
 
   for (uint32_t n = 0; n < outputCount; ++n)
   {
-    const ::internal::tflite::operand::Index ind{static_cast<int>(outputs[n])};
-    model->deref().outputs.emplace_back(ind);
+    const neurun::graph::operand::Index ind{static_cast<uint32_t>(outputs[n])};
+    model->deref().addOutput(ind);
 
     auto &obj = model->deref().operands().at(ind);
     // Model output cannot become model input

diff --git a/runtimes/neurun/src/graph/Graph.h b/runtimes/neurun/src/graph/Graph.h
index 0c35843..a4b762e 100644 (file)
--- a/runtimes/neurun/src/graph/Graph.h
+++ b/runtimes/neurun/src/graph/Graph.h
@@ -32,6 +32,7 @@ public:
   const operand::IndexSet &inputs() const { return _inputs; }
   const operand::IndexSet &outputs() const { return _outputs; }
   const operand::Set &operands() const { return _operands; }
+  operand::Set &operands() { return _operands; } // TODO Remove this non-const accessor
 
 public:
   // TODO Introduce Iterator class to support many kinds of interation

diff --git a/runtimes/neurun/src/internal/ITensorBuilder.h b/runtimes/neurun/src/internal/ITensorBuilder.h
index 90e3f49..13206b0 100644 (file)
--- a/runtimes/neurun/src/internal/ITensorBuilder.h
+++ b/runtimes/neurun/src/internal/ITensorBuilder.h
@@ -5,6 +5,7 @@
 #include <arm_compute/core/TensorInfo.h>
 
 #include "internal/Model.h"
+#include "graph/operand/Index.h"
 
 namespace internal
 {

diff --git a/runtimes/neurun/src/internal/Model.h b/runtimes/neurun/src/internal/Model.h
index 0df6dbd..b852bac 100644 (file)
--- a/runtimes/neurun/src/internal/Model.h
+++ b/runtimes/neurun/src/internal/Model.h
@@ -1,6 +1,8 @@
 #ifndef __INTERNAL_MODEL_H__
 #define __INTERNAL_MODEL_H__
 
+#include "graph/operand/Index.h"
+
 namespace internal
 {
 namespace tflite
@@ -16,6 +18,10 @@ public:
     // DO NOTHING
   }
 
+  // NOTE Temporary casting operator for legacy code compatibility
+public:
+  operator neurun::graph::operand::Index() const { return neurun::graph::operand::Index{_value}; }
+
 public:
   int asInt(void) const { return _value; }
 

diff --git a/runtimes/neurun/src/internal/Plan.h b/runtimes/neurun/src/internal/Plan.h
index 547b7e7..a950db5 100644 (file)
--- a/runtimes/neurun/src/internal/Plan.h
+++ b/runtimes/neurun/src/internal/Plan.h
@@ -1,7 +1,7 @@
 #ifndef __INTERNAL_PLAN_H__
 #define __INTERNAL_PLAN_H__
 
-#include "internal/Model.h"
+#include "graph/Graph.h"
 #include "internal/IObject.h"
 
 #include <map>
@@ -77,14 +77,14 @@ namespace internal
 class Plan
 {
 public:
-  Plan(const std::shared_ptr<::internal::tflite::Model> &model) : _model(model)
+  Plan(const std::shared_ptr<neurun::graph::Graph> &model) : _model(model)
   {
     // DO NOTHING
   }
 
 public:
-  ::internal::tflite::Model &model(void) { return *_model; }
-  const ::internal::tflite::Model &model(void) const { return *_model; }
+  neurun::graph::Graph &model(void) { return *_model; }
+  const neurun::graph::Graph &model(void) const { return *_model; }
 
 public:
   operand::Context &operands(void) { return _operands; }
@@ -99,7 +99,7 @@ public:
   const op::Sequence &operations(void) const { return _ops; }
 
 private:
-  std::shared_ptr<::internal::tflite::Model> _model;
+  std::shared_ptr<neurun::graph::Graph> _model;
   operand::Context _operands;
   operand::Context _common_operands;
   op::Sequence _ops;

diff --git a/runtimes/neurun/src/internal/Sink.h b/runtimes/neurun/src/internal/Sink.h
index cecf1e6..4c6f691 100644 (file)
--- a/runtimes/neurun/src/internal/Sink.h
+++ b/runtimes/neurun/src/internal/Sink.h
@@ -35,8 +35,11 @@ public:
 public:
   void pull(::arm_compute::ITensor &tensor) const override
   {
+// NOTE Leave common tensor conversion code before Graph IR supports tensor conversion
+#if 0
     // Only for common tensor now
-    assert(typeid(tensor) == typeid(::internal::common::Tensor));
+     assert(typeid(tensor) == typeid(::internal::common::Tensor));
+#endif
 
     float *base = reinterpret_cast<float *>(_base);
 
@@ -69,6 +72,32 @@ public:
 public:
   void pull(::arm_compute::ITensor &tensor) const override
   {
+    // TODO: This is just workaround codes, It needs to refactor.
+    if (typeid(tensor) == typeid(::internal::cpu::Tensor))
+    {
+      const ::internal::nnapi::feature::Reader<float> from{_shape, tensor.buffer(), _size};
+      ::internal::nnapi::feature::View<float> into{_shape, _base, _size};
+
+      ::nnfw::util::feature::iterate(_shape)
+          << [&](uint32_t bat, uint32_t ch, uint32_t row, uint32_t col) {
+               const auto value = from.at(bat, ch, row, col);
+               into.at(bat, ch, row, col) = value;
+             };
+    }
+    else if (typeid(tensor) == typeid(::arm_compute::CLTensor))
+    {
+      const ::internal::arm_compute::feature::View<float> from{&tensor};
+      ::internal::nnapi::feature::View<float> into{_shape, _base, _size};
+
+      ::nnfw::util::feature::iterate(_shape)
+          << [&](uint32_t bat, uint32_t ch, uint32_t row, uint32_t col) {
+               const auto value = from.at(bat, ch, row, col);
+               into.at(bat, ch, row, col) = value;
+             };
+    }
+
+// NOTE Leave common tensor conversion code before Graph IR supports tensor conversion
+#if 0
     // Only for common tensor now
     assert(typeid(tensor) == typeid(::internal::common::Tensor));
 
@@ -81,6 +110,7 @@ public:
              const auto value = from.at(batch, ch, row, col);
              into.at(batch, ch, row, col) = value;
            };
+#endif
   }
 
 private:

diff --git a/runtimes/neurun/src/internal/Source.h b/runtimes/neurun/src/internal/Source.h
index 8ca0203..e5270ad 100644 (file)
--- a/runtimes/neurun/src/internal/Source.h
+++ b/runtimes/neurun/src/internal/Source.h
@@ -38,8 +38,11 @@ public:
 public:
   void push(::arm_compute::ITensor &tensor) const override
   {
+// NOTE Leave common tensor conversion code before Graph IR supports tensor conversion
+#if 0
     // Only for common tensor now
     assert(typeid(tensor) == typeid(::internal::common::Tensor));
+#endif
 
     auto base = reinterpret_cast<const float *>(_base);
 
@@ -72,6 +75,32 @@ public:
 public:
   void push(::arm_compute::ITensor &tensor) const override
   {
+    // TODO: This is just workaround codes, It needs to refactor.
+    if (typeid(tensor) == typeid(::internal::cpu::Tensor))
+    {
+      const ::internal::nnapi::feature::Reader<float> from{_shape, _base, _size};
+      ::internal::nnapi::feature::View<float> into{_shape, tensor.buffer(), _size};
+
+      ::nnfw::util::feature::iterate(_shape)
+          << [&](uint32_t bat, uint32_t ch, uint32_t row, uint32_t col) {
+               const auto value = from.at(bat, ch, row, col);
+               into.at(bat, ch, row, col) = value;
+             };
+    }
+    else if (typeid(tensor) == typeid(::arm_compute::CLTensor))
+    {
+      const ::internal::nnapi::feature::Reader<float> from{_shape, _base, _size};
+      ::internal::arm_compute::feature::View<float> into{&tensor};
+
+      ::nnfw::util::feature::iterate(_shape)
+          << [&](uint32_t bat, uint32_t ch, uint32_t row, uint32_t col) {
+               const auto value = from.at(bat, ch, row, col);
+               into.at(bat, ch, row, col) = value;
+             };
+    }
+
+// NOTE Leave common tensor conversion code before Graph IR supports tensor conversion
+#if 0
     // Only for common tensor now
     assert(typeid(tensor) == typeid(::internal::common::Tensor));
 
@@ -84,6 +113,7 @@ public:
              const auto value = from.at(batch, ch, row, col);
              into.at(batch, ch, row, col) = value;
            };
+#endif
   }
 
 private:

diff --git a/runtimes/neurun/src/model.cc b/runtimes/neurun/src/model.cc
index 32c16c0..f3ad0b4 100644 (file)
--- a/runtimes/neurun/src/model.cc
+++ b/runtimes/neurun/src/model.cc
@@ -3,7 +3,7 @@
 //
 // ANeuralNetworksModel
 //
-ANeuralNetworksModel::ANeuralNetworksModel() : _model{new internal::tflite::Model}, _finished(false)
+ANeuralNetworksModel::ANeuralNetworksModel() : _model{new neurun::graph::Graph}, _finished(false)
 {
   // DO NOTHING
 }

diff --git a/runtimes/neurun/src/model.h b/runtimes/neurun/src/model.h
index e9c1009..b94dc36 100644 (file)
--- a/runtimes/neurun/src/model.h
+++ b/runtimes/neurun/src/model.h
@@ -3,7 +3,7 @@
 
 #include <NeuralNetworks.h>
 
-#include "internal/Model.h"
+#include "graph/Graph.h"
 
 struct ANeuralNetworksModel
 {
@@ -11,15 +11,15 @@ public:
   ANeuralNetworksModel();
 
 public:
-  internal::tflite::Model &deref(void) { return *_model; }
+  neurun::graph::Graph &deref(void) { return *_model; }
   ResultCode finish();
   bool isFinished() { return _finished; }
 
 public:
-  void release(std::shared_ptr<internal::tflite::Model> &model) { model = _model; }
+  void release(std::shared_ptr<neurun::graph::Graph> &model) { model = _model; }
 
 private:
-  std::shared_ptr<internal::tflite::Model> _model;
+  std::shared_ptr<neurun::graph::Graph> _model;
   bool _finished;
 };