Added scalar type support

Added SetScalar api to support scalar input Added 2 cases for scalar index Gather Type: New Feature Signed-off-by: Feiyue Chen <Feiyue.Chen@verisilicon.com>
VeriSilicon · Nov 3, 2023 · 603b4ca · 603b4ca
1 parent 1bb1e07
commit 603b4ca
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diff --git a/include/tim/vx/tensor.h b/include/tim/vx/tensor.h
@@ -161,7 +161,9 @@ class Tensor {
   virtual void unmap() = 0;
   virtual bool IsPlaceHolder() = 0;
   virtual bool IsConstTensor() = 0;
+  virtual bool IsScalar() = 0;
   virtual bool SaveTensorToTextByFp32(std::string filename) = 0;
+  virtual void SetScalar(int8_t is_scalar) = 0;
   virtual void* ConvertTensorToData(uint8_t* tensorData) = 0;
   virtual float* ConvertTensorToFloat32Data() = 0;
 };

diff --git a/src/tim/vx/ops/gather_test.cc b/src/tim/vx/ops/gather_test.cc
@@ -113,3 +113,85 @@ TEST(Gather, shape_2_2_indices_2) {
   EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
   EXPECT_EQ(golden, output);
 }
+
+TEST(Gather, scalar_index_input2D) {
+  auto ctx = tim::vx::Context::Create();
+
+  auto graph = ctx->CreateGraph();
+
+  tim::vx::ShapeType in_shape({5,2});
+  tim::vx::ShapeType index_shape({1});
+  tim::vx::ShapeType out_shape({5});
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, in_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec index_spec(tim::vx::DataType::INT32, index_shape,
+                                   tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, out_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto index_tensor = graph->CreateTensor(index_spec);
+  index_tensor->SetScalar(1);
+  auto output_tensor = graph->CreateTensor(output_spec);
+
+  std::vector<float> in_data = {
+    1,2,3,4,5,
+    6,7,8,9,10};
+
+  std::vector<int32_t> index = {1};
+  std::vector<float> golden = {6,7,8,9,10};
+
+  EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
+  EXPECT_TRUE(index_tensor->CopyDataToTensor(index.data(), index.size()));
+  auto op = graph->CreateOperation<tim::vx::ops::Gather>(1, 0);
+  (*op).BindInputs({input_tensor, index_tensor}).BindOutputs({output_tensor});
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  std::vector<float> output(golden.size());
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_EQ(golden, output);
+}
+
+TEST(Gather, scalar_index_input1D) {
+  auto ctx = tim::vx::Context::Create();
+
+  auto graph = ctx->CreateGraph();
+
+  tim::vx::ShapeType in_shape({5});
+  tim::vx::ShapeType index_shape({1});
+  tim::vx::ShapeType out_shape({});
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, in_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec index_spec(tim::vx::DataType::INT32, index_shape,
+                                   tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec gatherout_spec(tim::vx::DataType::FLOAT32, out_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, out_shape,
+                                   tim::vx::TensorAttribute::OUTPUT);
+
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto index_tensor = graph->CreateTensor(index_spec);
+  index_tensor->SetScalar(1);
+  auto gatherout_tensor = graph->CreateTensor(gatherout_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+
+  std::vector<float> in_data = {
+    1,2,3,4,5};
+
+  std::vector<int32_t> index = {1};
+  std::vector<float> golden = {2};
+
+  EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
+  EXPECT_TRUE(index_tensor->CopyDataToTensor(index.data(), index.size()));
+  auto gather = graph->CreateOperation<tim::vx::ops::Gather>(0);
+  (*gather).BindInputs({input_tensor, index_tensor}).BindOutputs({gatherout_tensor});
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+
+  std::vector<float> output(golden.size());
+  EXPECT_TRUE(gatherout_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_EQ(golden, output);
+}
diff --git a/src/tim/vx/tensor.cc b/src/tim/vx/tensor.cc
@@ -213,6 +213,14 @@ float* TensorImpl::ConvertTensorToFloat32Data() {
       graph_->graph(), vsi_nn_GetTensor(graph_->graph(), id_));
 }
 
+void TensorImpl::SetScalar(int8_t is_scalar) {
+  bool retn = vsi_nn_SetTensorIsScalar(vsi_nn_GetTensor(graph_->graph(), id_),is_scalar);
+  if (retn != VSI_SUCCESS) {
+    VSILOGE("Setting scalar fail!");
+  }
+  return;
+}
+
 bool TensorImpl::SwapHandle(void* new_ptr, bool is_new_ptr_malloc_by_ovxlib,
                             void** old_ptr) {
   bool retn = true;

diff --git a/src/tim/vx/tensor_private.h b/src/tim/vx/tensor_private.h
@@ -60,9 +60,14 @@ class TensorImpl : public Tensor {
   bool IsConstTensor() override {
     return spec_.attr_ == tim::vx::TensorAttribute::CONSTANT;
   }
+  bool IsScalar() override {
+    return vsi_nn_GetTensorIsScalar(vsi_nn_GetTensor(graph_->graph(), id_));
+  }
   bool SaveTensorToTextByFp32(std::string filename) override;
   void* ConvertTensorToData(uint8_t* tensorData) override;
   float* ConvertTensorToFloat32Data() override;
+  void SetScalar(int8_t is_scalar) override;
+
   GraphImpl* graph_;
   vsi_nn_tensor_id_t id_;
   TensorSpec spec_;
@@ -114,6 +119,9 @@ class TensorPlaceholder : public Tensor {
   bool IsConstTensor() override {
     return spec_.attr_ == tim::vx::TensorAttribute::CONSTANT;
   }
+  bool IsScalar() override {
+    return false;
+  }
   bool SaveTensorToTextByFp32(std::string filename) override {
     (void)filename;
     return false;
@@ -124,6 +132,7 @@ class TensorPlaceholder : public Tensor {
   }
   float* ConvertTensorToFloat32Data() override { return nullptr; }
 
+  void SetScalar(int8_t is_scalar) override { (void) is_scalar; return; }
   vsi_nn_tensor_id_t id_;
   TensorSpec spec_;
 };