Support alpha in elu (#354)

https://github.com/VeriSilicon/TIM-VX/issues/305

Signed-off-by: Chen Xin <jack.chen@verisilicon.com>

include/tim/vx/ops/activations.h

@@ -79,7 +79,6 @@ namespace ops {
 DECLARE_NO_PARAMETER_ACTIVATION(Relu)
 DECLARE_NO_PARAMETER_ACTIVATION(Relu1)
 DECLARE_NO_PARAMETER_ACTIVATION(Relu6)
-DECLARE_NO_PARAMETER_ACTIVATION(Elu)
 DECLARE_NO_PARAMETER_ACTIVATION(Tanh)
 DECLARE_NO_PARAMETER_ACTIVATION(Sigmoid)
 DECLARE_NO_PARAMETER_ACTIVATION(Swish)
@@ -89,6 +88,16 @@ DECLARE_NO_PARAMETER_ACTIVATION(SoftRelu)
 
 #undef DEFINE_NO_PARAMETER_ACTIVATION
 
+class Elu : public DirectMapOp {
+ public:
+  Elu(Graph* graph, float alpha);
+  std::shared_ptr<Operation> Clone(
+      std::shared_ptr<Graph>& graph) const override;
+
+ protected:
+  float alpha_;
+};
+
 class Prelu : public DirectMapOp {
  public:
   Prelu(Graph* graph, int axis);

src/tim/vx/ops/activations.cc

@@ -40,14 +40,21 @@ namespace ops {
 DEFINE_NO_PARAMETER_ACTIVATION(Relu, VSI_NN_OP_RELU)
 DEFINE_NO_PARAMETER_ACTIVATION(Relu1, VSI_NN_OP_RELU1)
 DEFINE_NO_PARAMETER_ACTIVATION(Relu6, VSI_NN_OP_RELU6)
-DEFINE_NO_PARAMETER_ACTIVATION(Elu, VSI_NN_OP_ELU)
 DEFINE_NO_PARAMETER_ACTIVATION(Sigmoid, VSI_NN_OP_SIGMOID)
 DEFINE_NO_PARAMETER_ACTIVATION(Mish, VSI_NN_OP_MISH)
 DEFINE_NO_PARAMETER_ACTIVATION(SoftRelu, VSI_NN_OP_SOFTRELU)
 
-
 #undef DEFINE_NO_PARAMETER_ACTIVATION
 
+Elu::Elu(Graph* graph, float alpha)
+    : DirectMapOp(graph, VSI_NN_OP_ELU), alpha_(alpha) {
+  this->impl()->node()->nn_param.elu.alpha = alpha_;
+}
+
+std::shared_ptr<Operation> Elu::Clone(std::shared_ptr<Graph>& graph) const {
+  return graph->CreateOperation<Elu>(this->alpha_);
+}
+
 HardSwish::HardSwish(Graph* graph) : DirectMapOp(graph, VSI_NN_OP_SWISH) {
   this->impl()->node()->nn_param.swish.type = VSI_NN_HSWISH;
   this->impl()->node()->nn_param.swish.beta = 1.0f;
@@ -63,8 +70,7 @@ Swish::Swish(Graph* graph) : DirectMapOp(graph, VSI_NN_OP_SWISH) {
   this->impl()->node()->nn_param.swish.beta = 1.0f;
 }
 
-std::shared_ptr<Operation> Swish::Clone(
+std::shared_ptr<Operation> Swish::Clone(std::shared_ptr<Graph>& graph) const {
-    std::shared_ptr<Graph>& graph) const {
   return graph->CreateOperation<Swish>();
 }
 
@@ -83,7 +89,8 @@ HardSigmoid::HardSigmoid(Graph* graph, float alpha, float beta)
   this->impl()->node()->nn_param.hard_sigmoid.beta = beta_;
 }
 
-std::shared_ptr<Operation> HardSigmoid::Clone(std::shared_ptr<Graph>& graph) const {
+std::shared_ptr<Operation> HardSigmoid::Clone(
+    std::shared_ptr<Graph>& graph) const {
   return graph->CreateOperation<HardSigmoid>(this->alpha_, this->beta_);
 }
 
@@ -122,7 +129,8 @@ Gelu::Gelu(Graph* graph, bool approximate)
 }
 
 std::shared_ptr<Operation> Gelu::Clone(std::shared_ptr<Graph>& graph) const {
-  return graph->CreateOperation<Gelu>(this->impl()->node()->nn_param.gelu.approximate);
+  return graph->CreateOperation<Gelu>(
+      this->impl()->node()->nn_param.gelu.approximate);
 }
 
 }  // namespace ops

src/tim/vx/ops/activations_test.cc

@@ -207,17 +207,14 @@ TEST(HardSigmoid, shape_5_1_uint8_Quantized) {
   auto input_tensor = graph->CreateTensor(input_spec);
   auto output_tensor = graph->CreateTensor(output_spec);
 
-  std::vector<uint8_t> in_data = {65, 255, 140, 92, 142,
+  std::vector<uint8_t> in_data = {65,  255, 140, 92,  142, 122, 117,
-                                  122, 117, 167, 132, 117,
+                                  167, 132, 117, 44,  99,  109, 96,
-                                  44, 99, 109, 96, 216,
+                                  216, 222, 135, 126, 113, 100};
-                                  222, 135, 126, 113, 100};
+  std::vector<uint8_t> golden_data = {222, 240, 229, 225, 229, 227, 227,
-  std::vector<uint8_t> golden_data = {222, 240, 229, 225, 229,
+                                      232, 228, 227, 220, 225, 226, 225,
-                                      227, 227, 232, 228, 227,
+                                      236, 237, 229, 228, 227, 225};
-                                      220, 225, 226, 225, 236,
-                                      237, 229, 228, 227, 225};
 
-  EXPECT_TRUE(
+  EXPECT_TRUE(input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
-      input_tensor->CopyDataToTensor(in_data.data(), in_data.size()));
   auto op = graph->CreateOperation<tim::vx::ops::HardSigmoid>(0.2, 0.5);
   (*op).BindInput(input_tensor).BindOutput(output_tensor);
 
@@ -228,3 +225,32 @@ TEST(HardSigmoid, shape_5_1_uint8_Quantized) {
   EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
   EXPECT_TRUE(ArraysMatch(golden_data, output, (uint8_t)1));
 }
+
+TEST(Elu, shape_5_1_fp32) {
+  auto ctx = tim::vx::Context::Create();
+  auto graph = ctx->CreateGraph();
+
+  tim::vx::ShapeType io_shape({5, 1});
+  tim::vx::TensorSpec input_spec(tim::vx::DataType::FLOAT32, io_shape,
+                                 tim::vx::TensorAttribute::INPUT);
+  tim::vx::TensorSpec output_spec(tim::vx::DataType::FLOAT32, io_shape,
+                                  tim::vx::TensorAttribute::OUTPUT);
+
+  auto input_tensor = graph->CreateTensor(input_spec);
+  auto output_tensor = graph->CreateTensor(output_spec);
+
+  std::vector<float> in_data = {-2.5, -0.1, 0, 0.55, 99};
+  std::vector<float> golden = {-0.458957, -0.0475813, 0, 0.55, 99};
+
+  EXPECT_TRUE(
+      input_tensor->CopyDataToTensor(in_data.data(), in_data.size() * 4));
+
+  auto op = graph->CreateOperation<tim::vx::ops::Elu>(0.5);
+  (*op).BindInputs({input_tensor}).BindOutputs({output_tensor});
+
+  EXPECT_TRUE(graph->Compile());
+  EXPECT_TRUE(graph->Run());
+  std::vector<float> output(5, 0);
+  EXPECT_TRUE(output_tensor->CopyDataFromTensor(output.data()));
+  EXPECT_TRUE(ArraysMatch(golden, output, 1e-5f));
+}