!6484 add hard tanh fp32

Merge pull request !6484 from zhaozhenlong/lite/issue/hard_tanh_fp32

mindspore/lite/nnacl/fp32/activation.c

@@ -116,3 +116,21 @@ int HSwish(const float *src, int length, float *dst) {
   }
   return NNACL_OK;
 }
+
+int HardTanh(const float *src, int length, float *dst, float min_val, float max_val) {
+  if (max_val <= min_val) {
+    return NNACL_ERR;
+  }
+  int i = 0;
+  for (i = 0; i < length; ++i) {
+    float in = src[i];
+    if (in < min_val) {
+      dst[i] = min_val;
+    } else if (in > max_val) {
+      dst[i] = max_val;
+    } else {
+      dst[i] = in;
+    }
+  }
+  return NNACL_OK;
+}

mindspore/lite/nnacl/fp32/activation.h

@@ -24,6 +24,8 @@ typedef struct ActivationParameter {
   OpParameter op_parameter_;
   int type_;
   float alpha_;
+  float min_val_;
+  float max_val_;
 } ActivationParameter;
 
 #ifdef __cplusplus
@@ -35,6 +37,7 @@ int LRelu(const float *src, int length, float *dst, float alpha);
 int Sigmoid(const float *src, int length, float *dst);
 int Tanh(const float *src, int length, float *dst);
 int HSwish(const float *src, int length, float *dst);
+int HardTanh(const float *src, int length, float *dst, float min_val, float max_val);
 #ifdef __cplusplus
 }
 #endif

mindspore/lite/schema/ops.fbs

@@ -57,7 +57,8 @@ enum ActivationType : byte {
     HSIGMOID = 13,
     THRESHOLDRELU = 14,
     LINEAR = 15,
-    UNKNOW = 16
+    HARD_TANH = 16,
+    UNKNOW = 17
 }
 enum ActivationGradType : byte {
     NO_ACTIVATION = 0,
@@ -155,6 +156,8 @@ table SoftMax {
 table Activation {
     type: ActivationType = 0;
     alpha: float = 0.2;
+    min_val: float = -1.0;
+    max_val: float = 1.0;
 }
 table ActivationGrad {
     type: ActivationType = 0;

mindspore/lite/src/ops/activation.cc

@@ -22,9 +22,13 @@ namespace lite {
 #ifdef PRIMITIVE_WRITEABLE
 int Activation::GetType() const { return this->primitive_->value.AsActivation()->type; }
 float Activation::GetAlpha() const { return this->primitive_->value.AsActivation()->alpha; }
+float Activation::GetMinVal() const { return this->primitive_->value.AsActivation()->min_val; }
+float Activation::GetMaxVal() const { return this->primitive_->value.AsActivation()->max_val; }
 
 void Activation::SetType(int type) { this->primitive_->value.AsActivation()->type = (schema::ActivationType)type; }
 void Activation::SetAlpha(float alpha) { this->primitive_->value.AsActivation()->alpha = alpha; }
+void Activation::SetMinVal(float min_val) { this->primitive_->value.AsActivation()->min_val = min_val; }
+void Activation::SetMaxVal(float max_val) { this->primitive_->value.AsActivation()->max_val = max_val; }
 
 int Activation::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
   if (this->primitive_ == nullptr) {
@@ -63,13 +67,15 @@ int Activation::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuff
     MS_LOG(ERROR) << "value_as_Activation return nullptr";
     return RET_ERROR;
   }
-  auto val_offset = schema::CreateActivation(*fbb, attr->type(), attr->alpha());
+  auto val_offset = schema::CreateActivation(*fbb, attr->type(), attr->alpha(), attr->min_val(), attr->max_val());
   auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_Activation, val_offset.o);
   fbb->Finish(prim_offset);
   return RET_OK;
 }
 int Activation::GetType() const { return this->primitive_->value_as_Activation()->type(); }
 float Activation::GetAlpha() const { return this->primitive_->value_as_Activation()->alpha(); }
+float Activation::GetMinVal() const { return this->primitive_->value_as_Activation()->min_val(); }
+float Activation::GetMaxVal() const { return this->primitive_->value_as_Activation()->max_val(); }
 #endif
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/ops/activation.h

@@ -33,6 +33,8 @@ class Activation : public PrimitiveC {
   int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
   void SetType(int type);
   void SetAlpha(float alpha);
+  void SetMinVal(float minVal);
+  void SetMaxVal(float maxVal);
 #else
   Activation() = default;
 
@@ -40,6 +42,8 @@ class Activation : public PrimitiveC {
 #endif
   int GetType() const;
   float GetAlpha() const;
+  float GetMinVal() const;
+  float GetMaxVal() const;
 };
 }  // namespace lite
 }  // namespace mindspore

mindspore/lite/src/populate_parameter.cc

@@ -636,6 +636,8 @@ OpParameter *PopulateActivationParameter(const mindspore::lite::PrimitiveC *prim
     reinterpret_cast<mindspore::lite::Activation *>(const_cast<mindspore::lite::PrimitiveC *>(primitive));
   act_param->type_ = static_cast<int>(activation->GetType());
   act_param->alpha_ = activation->GetAlpha();
+  act_param->min_val_ = activation->GetMinVal();
+  act_param->max_val_ = activation->GetMaxVal();
   return reinterpret_cast<OpParameter *>(act_param);
 }
 

mindspore/lite/src/runtime/kernel/arm/fp32/activation.cc

@@ -57,6 +57,8 @@ int ActivationCPUKernel::DoActivation(int task_id) {
     error_code = Tanh(input_addr + stride * task_id, count, output_addr + stride * task_id);
   } else if (type_ == schema::ActivationType_HSWISH) {
     error_code = HSwish(input_addr + stride * task_id, count, output_addr + stride * task_id);
+  } else if (type_ == schema::ActivationType_HARD_TANH) {
+    error_code = HardTanh(input_addr + stride * task_id, count, output_addr + stride * task_id, min_val_, max_val_);
   } else {
     MS_LOG(ERROR) << "Activation type error";
     return RET_ERROR;

mindspore/lite/src/runtime/kernel/arm/fp32/activation.h

@@ -30,6 +30,8 @@ class ActivationCPUKernel : public LiteKernel {
       : LiteKernel(param, inputs, outputs, ctx, primitive), thread_count_(ctx->thread_num_) {
     type_ = (reinterpret_cast<ActivationParameter *>(param))->type_;
     alpha_ = (reinterpret_cast<ActivationParameter *>(param))->alpha_;
+    min_val_ = (reinterpret_cast<ActivationParameter *>(param))->min_val_;
+    max_val_ = (reinterpret_cast<ActivationParameter *>(param))->max_val_;
   }
   ~ActivationCPUKernel() override = default;
 
@@ -42,6 +44,8 @@ class ActivationCPUKernel : public LiteKernel {
   int thread_count_;
   int type_;
   float alpha_;
+  float min_val_;
+  float max_val_;
 };
 }  // namespace mindspore::kernel
 

mindspore/lite/test/ut/src/runtime/kernel/arm/fp32/activation_fp32_test.cc

@@ -126,4 +126,93 @@ TEST_F(TestActivationFp32, HSwishFp32) {
   input0_tensor.SetData(nullptr);
   output0_tensor.SetData(nullptr);
 }
+
+TEST_F(TestActivationFp32, HardTanh1) {
+  std::vector<lite::Tensor *> inputs_tensor;
+  std::vector<lite::Tensor *> outputs_tensor;
+
+  ActivationParameter op_param;
+  op_param.op_parameter_.type_ = schema::PrimitiveType_Activation;
+  op_param.type_ = schema::ActivationType_HARD_TANH;
+  op_param.min_val_ = -1.0f;
+  op_param.max_val_ = 1.0f;
+
+  std::vector<float> input = {-2.0, -1.0, -0.5, 0.0, 0.5, 1.0, 5.0, 6.0};
+  std::vector<int> in_shape = {8};
+
+  lite::Tensor input0_tensor;
+  inputs_tensor.push_back(&input0_tensor);
+  input0_tensor.SetData(input.data());
+  input0_tensor.set_shape(in_shape);
+
+  std::vector<float> output(8);
+  std::vector<int> output_shape = {8};
+
+  lite::Tensor output0_tensor;
+  outputs_tensor.push_back(&output0_tensor);
+  output0_tensor.SetData(output.data());
+
+  kernel::KernelKey desc = {kernel::KERNEL_ARCH::kCPU, kNumberTypeFloat32, schema::PrimitiveType_Activation};
+  auto creator = lite::KernelRegistry::GetInstance()->GetCreator(desc);
+  ASSERT_NE(creator, nullptr);
+  lite::InnerContext ctx;
+  ctx.thread_num_ = 2;
+  ASSERT_EQ(lite::RET_OK, ctx.Init());
+  kernel::LiteKernel *kernel =
+    creator(inputs_tensor, outputs_tensor, reinterpret_cast<OpParameter *>(&op_param), &ctx, desc, nullptr);
+  ASSERT_NE(kernel, nullptr);
+  auto output_tensor_shape = output0_tensor.shape();
+  kernel->Run();
+
+  std::vector<float> expect_output = {-1.0, -1.0, -0.5, 0.0, 0.5, 1.0, 1.0, 1.0};
+  CompareOutputData(output.data(), expect_output.data(), 8, 0.00001);
+
+  input0_tensor.SetData(nullptr);
+  output0_tensor.SetData(nullptr);
+}
+
+TEST_F(TestActivationFp32, HardTanh2) {
+  std::vector<lite::Tensor *> inputs_tensor;
+  std::vector<lite::Tensor *> outputs_tensor;
+
+  ActivationParameter op_param;
+  op_param.op_parameter_.type_ = schema::PrimitiveType_Activation;
+  op_param.type_ = schema::ActivationType_HARD_TANH;
+  op_param.min_val_ = -2.0f;
+  op_param.max_val_ = 2.0f;
+
+  std::vector<float> input = {-3.0, -2.0, -1.0, 0.0, 1.0, 5.0, 6.0, 7.0};
+  std::vector<int> in_shape = {8};
+
+  lite::Tensor input0_tensor;
+  inputs_tensor.push_back(&input0_tensor);
+  input0_tensor.SetData(input.data());
+  input0_tensor.set_shape(in_shape);
+
+  std::vector<float> output(8);
+  std::vector<int> output_shape = {8};
+
+  lite::Tensor output0_tensor;
+  outputs_tensor.push_back(&output0_tensor);
+  output0_tensor.SetData(output.data());
+
+  kernel::KernelKey desc = {kernel::KERNEL_ARCH::kCPU, kNumberTypeFloat32, schema::PrimitiveType_Activation};
+  auto creator = lite::KernelRegistry::GetInstance()->GetCreator(desc);
+  ASSERT_NE(creator, nullptr);
+  lite::InnerContext ctx;
+  ctx.thread_num_ = 2;
+  ASSERT_EQ(lite::RET_OK, ctx.Init());
+  kernel::LiteKernel *kernel =
+    creator(inputs_tensor, outputs_tensor, reinterpret_cast<OpParameter *>(&op_param), &ctx, desc, nullptr);
+  ASSERT_NE(kernel, nullptr);
+  auto output_tensor_shape = output0_tensor.shape();
+  kernel->Run();
+
+  std::vector<float> expect_output = {-2.0, -2.0, -1.0, 0.0, 1.0, 2.0, 2.0, 2.0};
+  CompareOutputData(output.data(), expect_output.data(), 8, 0.00001);
+
+  input0_tensor.SetData(nullptr);
+  output0_tensor.SetData(nullptr);
+}
+
 }  // namespace mindspore