integrate conv2d ir

mindspore/lite/nnacl/fp32/exp_fp32.c

@@ -49,7 +49,8 @@ void ExpFp32(const float *src, float *dst, int num) {
   float32x4_t param3 = vdupq_n_f32(1.0f / 6);
   float32x4_t param4 = vdupq_n_f32(0.5f);
   float32x4_t param5 = vdupq_n_f32(1.0f);
-  for (; i < num - C4NUM; i += C4NUM) {
+  int count = (num / C4NUM) * C4NUM;
+  for (; i < count; i += C4NUM) {
     float32x4_t input4 = vmaxq_f32(minv, vminq_f32(maxv, vld1q_f32(src + i)));
     int32x4_t integer4 = vcvtq_s32_f32(vdivq_f32(input4, param0));
     float32x4_t decimal4 = vsubq_f32(input4, vmulq_f32(vcvtq_f32_s32(integer4), param0));

mindspore/lite/nnacl/fp32/softmax_fp32.c

@@ -15,6 +15,7 @@
  */
 #include "nnacl/fp32/softmax_fp32.h"
 #include <math.h>
+#include <float.h>
 #include "nnacl/fp32/exp_fp32.h"
 
 void SoftmaxNorm(const float *src, float *dst, int batch, int channel) {
@@ -22,15 +23,15 @@ void SoftmaxNorm(const float *src, float *dst, int batch, int channel) {
   for (int i = 0; i < batch; i++, cur_batch_offset += channel) {
     int j = 0;
 #ifdef ENABLE_ARM64
-    float32x4_t max4 = vld1q_f32(src + cur_batch_offset);
-    j += C4NUM;
-    for (; j < channel - C4NUM; j += C4NUM) {
+    float32x4_t max4 = vdupq_n_f32(-FLT_MAX);
+    int count = (channel / C4NUM) * C4NUM;
+    for (; j < count; j += C4NUM) {
       float32x4_t input4 = vld1q_f32(src + cur_batch_offset + j);
       max4 = vmaxq_f32(max4, input4);
     }
-    float max = channel >= C4NUM ? vmaxvq_f32(max4) : src[cur_batch_offset];
+    float max = vmaxvq_f32(max4);
 #else
-    float max = src[cur_batch_offset];
+    float max = -FLT_MAX;
 #endif
     for (; j < channel; j++) {
       float input = src[cur_batch_offset + j];
@@ -40,7 +41,8 @@ void SoftmaxNorm(const float *src, float *dst, int batch, int channel) {
     }
     int k = 0;
 #ifdef ENABLE_NEON
-    for (; k < channel - C4NUM; k += C4NUM) {
+    int count2 = (channel / C4NUM) * C4NUM;
+    for (; k < count2; k += C4NUM) {
       float32x4_t input4 = vld1q_f32(src + cur_batch_offset + k);
       float32x4_t output4 = vsubq_f32(input4, vdupq_n_f32(max));
       vst1q_f32(dst + cur_batch_offset + k, output4);
@@ -60,7 +62,8 @@ void SumAndDiv(const float *src, float *dst, int batch, int channel) {
     int j = 0;
 #ifdef ENABLE_NEON
     float32x4_t sum4 = vdupq_n_f32(0);
-    for (; j < channel - C4NUM; j += C4NUM) {
+    int count = (channel / C4NUM) * C4NUM;
+    for (; j < count; j += C4NUM) {
       sum4 = vaddq_f32(sum4, vld1q_f32(src + cur_batch_offset + j));
     }
     sum = sum4[0] + sum4[1] + sum4[2] + sum4[3];
@@ -71,7 +74,7 @@ void SumAndDiv(const float *src, float *dst, int batch, int channel) {
     int k = 0;
 #ifdef ENABLE_NEON
     const float div = 1.0f / sum;
-    for (; k < channel - C4NUM; k += C4NUM) {
+    for (; k < count; k += C4NUM) {
       vst1q_f32(dst + cur_batch_offset + k, vmulq_n_f32(vld1q_f32(src + cur_batch_offset + k), div));
     }
 #endif

mindspore/lite/schema/ops.fbs

@@ -203,7 +203,7 @@ table Conv2D {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     activationType: ActivationType = 0;
 }
 
@@ -243,7 +243,7 @@ table Conv2DGradFilter {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     filter_shape: [int];
     activationType: ActivationType = 0;
 }
@@ -264,7 +264,7 @@ table Conv2DGradInput {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     input_shape: [int];
     activationType: ActivationType = 0;
 }
@@ -285,7 +285,7 @@ table GroupConv2DGradInput {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     input_shape: [int];
     activationType: ActivationType = 0;
 }
@@ -394,7 +394,7 @@ table DepthwiseConv2D {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool  = false;
+    hasBias: bool  = false;  // DEPRECATED
     activationType: ActivationType = 0;
 }
 
@@ -413,7 +413,7 @@ table DeDepthwiseConv2D {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool  = false;
+    hasBias: bool  = false;  // DEPRECATED
     activationType: ActivationType = 0;
 }
 
@@ -478,7 +478,7 @@ table DeConv2D {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     activationType: ActivationType = 0;
 }
 
@@ -498,7 +498,7 @@ table DeConv2DGradFilter {
     padRight: int;
     dilateW: int;
     dilateH: int;
-    hasBias: bool = false;
+    hasBias: bool = false;  // DEPRECATED
     activationType: ActivationType = 0;
 }
 

mindspore/lite/src/ops/conv2d.cc

@@ -53,7 +53,6 @@ int Conv2D::GetPadLeft() const { return this->primitive_->value.AsConv2D()->padL
 int Conv2D::GetPadRight() const { return this->primitive_->value.AsConv2D()->padRight; }
 int Conv2D::GetDilateW() const { return this->primitive_->value.AsConv2D()->dilateW; }
 int Conv2D::GetDilateH() const { return this->primitive_->value.AsConv2D()->dilateH; }
-bool Conv2D::GetHasBias() const { return this->primitive_->value.AsConv2D()->hasBias; }
 int Conv2D::GetActivationType() const { return this->primitive_->value.AsConv2D()->activationType; }
 
 void Conv2D::SetFormat(int format) { this->primitive_->value.AsConv2D()->format = (schema::Format)format; }
@@ -71,7 +70,6 @@ void Conv2D::SetPadLeft(int pad_left) { this->primitive_->value.AsConv2D()->padL
 void Conv2D::SetPadRight(int pad_right) { this->primitive_->value.AsConv2D()->padRight = pad_right; }
 void Conv2D::SetDilateW(int dilate_w) { this->primitive_->value.AsConv2D()->dilateW = dilate_w; }
 void Conv2D::SetDilateH(int dilate_h) { this->primitive_->value.AsConv2D()->dilateH = dilate_h; }
-void Conv2D::SetHasBias(bool has_bias) { this->primitive_->value.AsConv2D()->hasBias = has_bias; }
 void Conv2D::SetActivationType(int activation_type) {
   this->primitive_->value.AsConv2D()->activationType = (schema::ActivationType)activation_type;
 }
@@ -330,7 +328,6 @@ int Conv2D::GetPadLeft() const { return this->primitive_->value_as_Conv2D()->pad
 int Conv2D::GetPadRight() const { return this->primitive_->value_as_Conv2D()->padRight(); }
 int Conv2D::GetDilateW() const { return this->primitive_->value_as_Conv2D()->dilateW(); }
 int Conv2D::GetDilateH() const { return this->primitive_->value_as_Conv2D()->dilateH(); }
-bool Conv2D::GetHasBias() const { return this->primitive_->value_as_Conv2D()->hasBias(); }
 int Conv2D::GetActivationType() const { return this->primitive_->value_as_Conv2D()->activationType(); }
 
 PrimitiveC *Conv2DCreator(const schema::Primitive *primitive) { return PrimitiveC::NewPrimitiveC<Conv2D>(primitive); }

mindspore/lite/src/ops/conv2d.h

@@ -49,7 +49,6 @@ class Conv2D : public PrimitiveC {
   virtual void SetPadRight(int pad_right);
   virtual void SetDilateW(int dilate_w);
   virtual void SetDilateH(int dilate_h);
-  virtual void SetHasBias(bool has_bias);
   virtual void SetActivationType(int activation_type);
 
  private:
@@ -82,7 +81,6 @@ class Conv2D : public PrimitiveC {
   virtual int GetPadRight() const;
   virtual int GetDilateW() const;
   virtual int GetDilateH() const;
-  virtual bool GetHasBias() const;
   virtual int GetActivationType() const;
 
  protected:

mindspore/lite/src/ops/conv2d_grad_filter.cc

@@ -37,7 +37,6 @@ int Conv2DGradFilter::GetPadLeft() const { return this->primitive_->value.AsConv
 int Conv2DGradFilter::GetPadRight() const { return this->primitive_->value.AsConv2DGradFilter()->padRight; }
 int Conv2DGradFilter::GetDilateW() const { return this->primitive_->value.AsConv2DGradFilter()->dilateW; }
 int Conv2DGradFilter::GetDilateH() const { return this->primitive_->value.AsConv2DGradFilter()->dilateH; }
-bool Conv2DGradFilter::GetHasBias() const { return this->primitive_->value.AsConv2DGradFilter()->hasBias; }
 
 int Conv2DGradFilter::GetActivationType() const { return this->primitive_->value.AsConv2DGradFilter()->activationType; }
 
@@ -66,7 +65,6 @@ void Conv2DGradFilter::SetPadRight(int pad_right) {
 }
 void Conv2DGradFilter::SetDilateW(int dilate_w) { this->primitive_->value.AsConv2DGradFilter()->dilateW = dilate_w; }
 void Conv2DGradFilter::SetDilateH(int dilate_h) { this->primitive_->value.AsConv2DGradFilter()->dilateH = dilate_h; }
-void Conv2DGradFilter::SetHasBias(bool has_bias) { this->primitive_->value.AsConv2DGradFilter()->hasBias = has_bias; }
 std::vector<int> Conv2DGradFilter::GetFilterShape() const {
   return this->primitive_->value.AsConv2DGradFilter()->filter_shape;
 }
@@ -206,7 +204,6 @@ int Conv2DGradFilter::GetPadLeft() const { return this->primitive_->value_as_Con
 int Conv2DGradFilter::GetPadRight() const { return this->primitive_->value_as_Conv2DGradFilter()->padRight(); }
 int Conv2DGradFilter::GetDilateW() const { return this->primitive_->value_as_Conv2DGradFilter()->dilateW(); }
 int Conv2DGradFilter::GetDilateH() const { return this->primitive_->value_as_Conv2DGradFilter()->dilateH(); }
-bool Conv2DGradFilter::GetHasBias() const { return this->primitive_->value_as_Conv2DGradFilter()->hasBias(); }
 std::vector<int> Conv2DGradFilter::GetFilterShape() const {
   auto fb_vector = this->primitive_->value_as_Conv2DGradFilter()->filter_shape();
   return std::vector<int>(fb_vector->begin(), fb_vector->end());

mindspore/lite/src/ops/conv2d_grad_filter.h

@@ -48,7 +48,6 @@ class Conv2DGradFilter : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
   int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
@@ -70,7 +69,6 @@ class Conv2DGradFilter : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   int GetActivationType() const;
   std::vector<int> GetFilterShape() const;
 };

mindspore/lite/src/ops/conv2d_grad_input.cc

@@ -38,7 +38,6 @@ int Conv2DGradInput::GetPadLeft() const { return this->primitive_->value.AsConv2
 int Conv2DGradInput::GetPadRight() const { return this->primitive_->value.AsConv2DGradInput()->padRight; }
 int Conv2DGradInput::GetDilateW() const { return this->primitive_->value.AsConv2DGradInput()->dilateW; }
 int Conv2DGradInput::GetDilateH() const { return this->primitive_->value.AsConv2DGradInput()->dilateH; }
-bool Conv2DGradInput::GetHasBias() const { return this->primitive_->value.AsConv2DGradInput()->hasBias; }
 std::vector<int> Conv2DGradInput::GetInputShape() const {
   return this->primitive_->value.AsConv2DGradInput()->input_shape;
 }
@@ -67,7 +66,6 @@ void Conv2DGradInput::SetPadLeft(int pad_left) { this->primitive_->value.AsConv2
 void Conv2DGradInput::SetPadRight(int pad_right) { this->primitive_->value.AsConv2DGradInput()->padRight = pad_right; }
 void Conv2DGradInput::SetDilateW(int dilate_w) { this->primitive_->value.AsConv2DGradInput()->dilateW = dilate_w; }
 void Conv2DGradInput::SetDilateH(int dilate_h) { this->primitive_->value.AsConv2DGradInput()->dilateH = dilate_h; }
-void Conv2DGradInput::SetHasBias(bool has_bias) { this->primitive_->value.AsConv2DGradInput()->hasBias = has_bias; }
 void Conv2DGradInput::SetActivationType(int activation_type) {
   this->primitive_->value.AsConv2DGradInput()->activationType = (schema::ActivationType)activation_type;
 }
@@ -207,7 +205,6 @@ int Conv2DGradInput::GetPadLeft() const { return this->primitive_->value_as_Conv
 int Conv2DGradInput::GetPadRight() const { return this->primitive_->value_as_Conv2DGradInput()->padRight(); }
 int Conv2DGradInput::GetDilateW() const { return this->primitive_->value_as_Conv2DGradInput()->dilateW(); }
 int Conv2DGradInput::GetDilateH() const { return this->primitive_->value_as_Conv2DGradInput()->dilateH(); }
-bool Conv2DGradInput::GetHasBias() const { return this->primitive_->value_as_Conv2DGradInput()->hasBias(); }
 std::vector<int> Conv2DGradInput::GetInputShape() const {
   auto fb_vector = this->primitive_->value_as_Conv2DGradInput()->input_shape();
   return std::vector<int>(fb_vector->begin(), fb_vector->end());

mindspore/lite/src/ops/conv2d_grad_input.h

@@ -48,7 +48,6 @@ class Conv2DGradInput : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
   int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
@@ -70,7 +69,6 @@ class Conv2DGradInput : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   int GetActivationType() const;
   std::vector<int> GetInputShape() const;
 };

mindspore/lite/src/ops/deconv2d.cc

@@ -47,7 +47,6 @@ int DeConv2D::GetPadLeft() const { return this->primitive_->value.AsDeConv2D()->
 int DeConv2D::GetPadRight() const { return this->primitive_->value.AsDeConv2D()->padRight; }
 int DeConv2D::GetDilateW() const { return this->primitive_->value.AsDeConv2D()->dilateW; }
 int DeConv2D::GetDilateH() const { return this->primitive_->value.AsDeConv2D()->dilateH; }
-bool DeConv2D::GetHasBias() const { return this->primitive_->value.AsDeConv2D()->hasBias; }
 int DeConv2D::GetActivationType() const { return this->primitive_->value.AsDeConv2D()->activationType; }
 
 void DeConv2D::SetFormat(int format) { this->primitive_->value.AsDeConv2D()->format = (schema::Format)format; }
@@ -65,7 +64,6 @@ void DeConv2D::SetPadLeft(int pad_left) { this->primitive_->value.AsDeConv2D()->
 void DeConv2D::SetPadRight(int pad_right) { this->primitive_->value.AsDeConv2D()->padRight = pad_right; }
 void DeConv2D::SetDilateW(int dilate_w) { this->primitive_->value.AsDeConv2D()->dilateW = dilate_w; }
 void DeConv2D::SetDilateH(int dilate_h) { this->primitive_->value.AsDeConv2D()->dilateH = dilate_h; }
-void DeConv2D::SetHasBias(bool has_bias) { this->primitive_->value.AsDeConv2D()->hasBias = has_bias; }
 void DeConv2D::SetActivationType(int activation_type) {
   this->primitive_->value.AsDeConv2D()->activationType = (schema::ActivationType)activation_type;
 }
@@ -297,7 +295,6 @@ int DeConv2D::GetPadLeft() const { return this->primitive_->value_as_DeConv2D()-
 int DeConv2D::GetPadRight() const { return this->primitive_->value_as_DeConv2D()->padRight(); }
 int DeConv2D::GetDilateW() const { return this->primitive_->value_as_DeConv2D()->dilateW(); }
 int DeConv2D::GetDilateH() const { return this->primitive_->value_as_DeConv2D()->dilateH(); }
-bool DeConv2D::GetHasBias() const { return this->primitive_->value_as_DeConv2D()->hasBias(); }
 int DeConv2D::GetActivationType() const { return this->primitive_->value_as_DeConv2D()->activationType(); }
 
 PrimitiveC *DeConv2DCreator(const schema::Primitive *primitive) {

mindspore/lite/src/ops/deconv2d.h

@@ -46,7 +46,6 @@ class DeConv2D : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
   void PopulaterDeConv2DSingleGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group);
   void PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group,
@@ -71,7 +70,6 @@ class DeConv2D : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   int GetActivationType() const;
 
   int PadUp() const { return this->pad_u_; }

mindspore/lite/src/ops/dedepthwise_conv2d.cc

@@ -39,7 +39,6 @@ int DeDepthwiseConv2D::GetPadLeft() const { return this->primitive_->value.AsDeD
 int DeDepthwiseConv2D::GetPadRight() const { return this->primitive_->value.AsDeDepthwiseConv2D()->padRight; }
 int DeDepthwiseConv2D::GetDilateW() const { return this->primitive_->value.AsDeDepthwiseConv2D()->dilateW; }
 int DeDepthwiseConv2D::GetDilateH() const { return this->primitive_->value.AsDeDepthwiseConv2D()->dilateH; }
-bool DeDepthwiseConv2D::GetHasBias() const { return this->primitive_->value.AsDeDepthwiseConv2D()->hasBias; }
 int DeDepthwiseConv2D::GetActivationType() const {
   return this->primitive_->value.AsDeDepthwiseConv2D()->activationType;
 }
@@ -68,7 +67,6 @@ void DeDepthwiseConv2D::SetPadRight(int pad_right) {
 }
 void DeDepthwiseConv2D::SetDilateW(int dilate_w) { this->primitive_->value.AsDeDepthwiseConv2D()->dilateW = dilate_w; }
 void DeDepthwiseConv2D::SetDilateH(int dilate_h) { this->primitive_->value.AsDeDepthwiseConv2D()->dilateH = dilate_h; }
-void DeDepthwiseConv2D::SetHasBias(bool has_bias) { this->primitive_->value.AsDeDepthwiseConv2D()->hasBias = has_bias; }
 void DeDepthwiseConv2D::SetActivationType(int activation_type) {
   this->primitive_->value.AsDeDepthwiseConv2D()->activationType = static_cast<schema::ActivationType>(activation_type);
 }
@@ -108,7 +106,6 @@ int DeDepthwiseConv2D::GetPadLeft() const { return this->primitive_->value_as_De
 int DeDepthwiseConv2D::GetPadRight() const { return this->primitive_->value_as_DeDepthwiseConv2D()->padRight(); }
 int DeDepthwiseConv2D::GetDilateW() const { return this->primitive_->value_as_DeDepthwiseConv2D()->dilateW(); }
 int DeDepthwiseConv2D::GetDilateH() const { return this->primitive_->value_as_DeDepthwiseConv2D()->dilateH(); }
-bool DeDepthwiseConv2D::GetHasBias() const { return this->primitive_->value_as_DeDepthwiseConv2D()->hasBias(); }
 int DeDepthwiseConv2D::GetActivationType() const {
   return this->primitive_->value_as_DeDepthwiseConv2D()->activationType();
 }

mindspore/lite/src/ops/dedepthwise_conv2d.h

@@ -45,7 +45,6 @@ class DeDepthwiseConv2D : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
@@ -65,7 +64,6 @@ class DeDepthwiseConv2D : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   int GetActivationType() const;
 
   int PadUp() const { return this->pad_u_; }

mindspore/lite/src/ops/depthwise_conv2d.cc

@@ -44,7 +44,6 @@ int DepthwiseConv2D::GetPadLeft() const { return this->primitive_->value.AsDepth
 int DepthwiseConv2D::GetPadRight() const { return this->primitive_->value.AsDepthwiseConv2D()->padRight; }
 int DepthwiseConv2D::GetDilateW() const { return this->primitive_->value.AsDepthwiseConv2D()->dilateW; }
 int DepthwiseConv2D::GetDilateH() const { return this->primitive_->value.AsDepthwiseConv2D()->dilateH; }
-bool DepthwiseConv2D::GetHasBias() const { return this->primitive_->value.AsDepthwiseConv2D()->hasBias; }
 int DepthwiseConv2D::GetActivationType() const { return this->primitive_->value.AsDepthwiseConv2D()->activationType; }
 
 void DepthwiseConv2D::SetFormat(int format) {
@@ -69,7 +68,6 @@ void DepthwiseConv2D::SetPadLeft(int pad_left) { this->primitive_->value.AsDepth
 void DepthwiseConv2D::SetPadRight(int pad_right) { this->primitive_->value.AsDepthwiseConv2D()->padRight = pad_right; }
 void DepthwiseConv2D::SetDilateW(int dilate_w) { this->primitive_->value.AsDepthwiseConv2D()->dilateW = dilate_w; }
 void DepthwiseConv2D::SetDilateH(int dilate_h) { this->primitive_->value.AsDepthwiseConv2D()->dilateH = dilate_h; }
-void DepthwiseConv2D::SetHasBias(bool has_bias) { this->primitive_->value.AsDepthwiseConv2D()->hasBias = has_bias; }
 void DepthwiseConv2D::SetActivationType(int activation_type) {
   this->primitive_->value.AsDepthwiseConv2D()->activationType = static_cast<schema::ActivationType>(activation_type);
 }
@@ -183,7 +181,6 @@ int DepthwiseConv2D::GetPadLeft() const { return this->primitive_->value_as_Dept
 int DepthwiseConv2D::GetPadRight() const { return this->primitive_->value_as_DepthwiseConv2D()->padRight(); }
 int DepthwiseConv2D::GetDilateW() const { return this->primitive_->value_as_DepthwiseConv2D()->dilateW(); }
 int DepthwiseConv2D::GetDilateH() const { return this->primitive_->value_as_DepthwiseConv2D()->dilateH(); }
-bool DepthwiseConv2D::GetHasBias() const { return this->primitive_->value_as_DepthwiseConv2D()->hasBias(); }
 int DepthwiseConv2D::GetActivationType() const {
   return this->primitive_->value_as_DepthwiseConv2D()->activationType();
 }

mindspore/lite/src/ops/depthwise_conv2d.h

@@ -47,7 +47,6 @@ class DepthwiseConv2D : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
@@ -68,7 +67,6 @@ class DepthwiseConv2D : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   int GetActivationType() const;
 
   int PadUp() const { return this->pad_u_; }

mindspore/lite/src/ops/group_conv2d_grad_input.cc

@@ -38,7 +38,6 @@ int GroupConv2DGradInput::GetPadLeft() const { return this->primitive_->value.As
 int GroupConv2DGradInput::GetPadRight() const { return this->primitive_->value.AsGroupConv2DGradInput()->padRight; }
 int GroupConv2DGradInput::GetDilateW() const { return this->primitive_->value.AsGroupConv2DGradInput()->dilateW; }
 int GroupConv2DGradInput::GetDilateH() const { return this->primitive_->value.AsGroupConv2DGradInput()->dilateH; }
-bool GroupConv2DGradInput::GetHasBias() const { return this->primitive_->value.AsGroupConv2DGradInput()->hasBias; }
 std::vector<int> GroupConv2DGradInput::GetInputShape() const {
   return this->primitive_->value.AsGroupConv2DGradInput()->input_shape;
 }
@@ -87,9 +86,6 @@ void GroupConv2DGradInput::SetDilateW(int dilate_w) {
 void GroupConv2DGradInput::SetDilateH(int dilate_h) {
   this->primitive_->value.AsGroupConv2DGradInput()->dilateH = dilate_h;
 }
-void GroupConv2DGradInput::SetHasBias(bool has_bias) {
-  this->primitive_->value.AsGroupConv2DGradInput()->hasBias = has_bias;
-}
 void GroupConv2DGradInput::SetActivationType(int activation_type) {
   this->primitive_->value.AsGroupConv2DGradInput()->activationType = (schema::ActivationType)activation_type;
 }
@@ -135,7 +131,6 @@ int GroupConv2DGradInput::GetPadLeft() const { return this->primitive_->value_as
 int GroupConv2DGradInput::GetPadRight() const { return this->primitive_->value_as_GroupConv2DGradInput()->padRight(); }
 int GroupConv2DGradInput::GetDilateW() const { return this->primitive_->value_as_GroupConv2DGradInput()->dilateW(); }
 int GroupConv2DGradInput::GetDilateH() const { return this->primitive_->value_as_GroupConv2DGradInput()->dilateH(); }
-bool GroupConv2DGradInput::GetHasBias() const { return this->primitive_->value_as_GroupConv2DGradInput()->hasBias(); }
 std::vector<int> GroupConv2DGradInput::GetInputShape() const {
   auto fb_vector = this->primitive_->value_as_GroupConv2DGradInput()->input_shape();
   return std::vector<int>(fb_vector->begin(), fb_vector->end());

mindspore/lite/src/ops/group_conv2d_grad_input.h

@@ -48,7 +48,6 @@ class GroupConv2DGradInput : public PrimitiveC {
   void SetPadRight(int pad_right);
   void SetDilateW(int dilate_w);
   void SetDilateH(int dilate_h);
-  void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
 #else
   int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
@@ -69,7 +68,6 @@ class GroupConv2DGradInput : public PrimitiveC {
   int GetPadRight() const;
   int GetDilateW() const;
   int GetDilateH() const;
-  bool GetHasBias() const;
   std::vector<int> GetInputShape() const;
   int GetActivationType() const;
 };

mindspore/lite/test/models_onnx.cfg

@@ -3,7 +3,7 @@ mtk_emotions-d2012-75.8%.onnx
 mtk_face_features_v3.onnx
 emotion-ferplus-8.onnx
 rcnn-ilsvrc13-9.onnx
-#efficientnet-lite4-11.onnx
+efficientnet-lite4-11.onnx
 mobilenetv2-7.onnx
 shufflenet-v2-10.onnx
 squeezenet1.1-7.onnx

mindspore/lite/test/models_onnx_fp16.cfg

@@ -3,7 +3,7 @@ mtk_emotions-d2012-75.8%.onnx 20
 mtk_face_features_v3.onnx 20
 emotion-ferplus-8.onnx 1
 #rcnn-ilsvrc13-9.onnx 0.1
-#efficientnet-lite4-11.onnx 2
+efficientnet-lite4-11.onnx 2
 mobilenetv2-7.onnx 8
 shufflenet-v2-10.onnx 5
 squeezenet1.1-7.onnx 1

mindspore/lite/test/ut/tools/converter/parser/tflite/tflite_conv_parser_test.cc

@@ -37,7 +37,6 @@ TEST_F(TestTfliteParserConv, AttrValue) {
   ASSERT_EQ(val->format, schema::Format_NHWC);
   ASSERT_EQ(val->group, 1);
   ASSERT_EQ(val->activationType, schema::ActivationType_NO_ACTIVATION);
-  ASSERT_EQ(val->hasBias, true);
   ASSERT_EQ(val->channelIn, 1);
   ASSERT_EQ(val->channelOut, 4);
   ASSERT_EQ(val->kernelH, 3);

mindspore/lite/test/ut/tools/converter/parser/tflite/tflite_deconv_parser_test.cc

@@ -37,7 +37,6 @@ TEST_F(TestTfliteParserDeConv, AttrValue) {
   ASSERT_EQ(val->format, schema::Format_NHWC);
   ASSERT_EQ(val->group, 1);
   ASSERT_EQ(val->activationType, schema::ActivationType_NO_ACTIVATION);
-  ASSERT_EQ(val->hasBias, true);
 
   ASSERT_EQ(val->channelIn, 1);
   ASSERT_EQ(val->channelOut, 4);

mindspore/lite/test/ut/tools/converter/parser/tflite/tflite_depthwise_conv_parser_test.cc

@@ -37,7 +37,6 @@ TEST_F(TestTfliteParserDepthwiseConv1, AttrValue) {
   ASSERT_EQ(val->format, schema::Format_NHWC);
   ASSERT_EQ(val->group, 0);
   ASSERT_EQ(val->activationType, schema::ActivationType_NO_ACTIVATION);
-  ASSERT_EQ(val->hasBias, true);
   ASSERT_EQ(val->channelIn, 1);
   ASSERT_EQ(val->channelOut, 4);
   ASSERT_EQ(val->kernelH, 3);
@@ -71,7 +70,6 @@ TEST_F(TestTfliteParserDepthwiseConv2, AttrValue) {
   auto val = meta_graph->nodes.front()->primitive->value.AsDepthwiseConv2D();
   ASSERT_EQ(val->format, schema::Format_NHWC);
   ASSERT_EQ(val->activationType, schema::ActivationType_NO_ACTIVATION);
-  ASSERT_EQ(val->hasBias, true);
   ASSERT_EQ(val->channelIn, 2);
   ASSERT_EQ(val->channelMultiplier, 1);
   ASSERT_EQ(val->kernelH, 3);

mindspore/lite/test/ut/tools/optimizer/fusion/conv_biasadd_fusion_test.cc

@@ -157,9 +157,6 @@ TEST_F(ConvBiasAddFusionTest, TestConvAddNode) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
-  for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsConv2D()->hasBias, true);
-  }
   MS_LOG(INFO) << "Passed";
 }
 
@@ -171,9 +168,6 @@ TEST_F(ConvBiasAddFusionTest, TestDeptiwiseConvAddNode) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
-  for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsDepthwiseConv2D()->hasBias, true);
-  }
 }
 
 TEST_F(ConvBiasAddFusionTest, TestBadCase_ConvAdd) {
@@ -184,10 +178,5 @@ TEST_F(ConvBiasAddFusionTest, TestBadCase_ConvAdd) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 2);
-  for (auto &cnode : new_meta_graph->nodes) {
-    if (cnode->primitive->value.type == schema::PrimitiveType_DepthwiseConv2D) {
-      ASSERT_EQ(cnode->primitive->value.AsDepthwiseConv2D()->hasBias, false);
-    }
-  }
 }
 }  // namespace mindspore

mindspore/lite/test/ut/tools/optimizer/fusion/conv_bn_fusion_test.cc

@@ -274,9 +274,6 @@ TEST_F(ConvBNFusionTest, TestConvAddNode) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
-  for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsConv2D()->hasBias, true);
-  }
 }
 
 TEST_F(ConvBNFusionTest, TestDeptiwiseConvAddNode) {
@@ -287,8 +284,5 @@ TEST_F(ConvBNFusionTest, TestDeptiwiseConvAddNode) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
-  for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsDepthwiseConv2D()->hasBias, true);
-  }
 }
 }  // namespace mindspore

mindspore/lite/test/ut/tools/optimizer/fusion/conv_scale_fusion_test.cc

@@ -200,9 +200,6 @@ TEST_F(ConvScaleFusionTest, TestConvScaleNode) {
   ASSERT_NE(nullptr, new_graph);
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
-  for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsConv2D()->hasBias, true);
-  }
   delete anf_transform;
 }
 
@@ -215,7 +212,6 @@ TEST_F(ConvScaleFusionTest, TestDeptiwiseConvScaleNode) {
   auto new_meta_graph = lite::Export(new_graph);
   ASSERT_EQ(new_meta_graph->nodes.size(), 1);
   for (auto &cnode : new_meta_graph->nodes) {
-    ASSERT_EQ(cnode->primitive->value.AsDepthwiseConv2D()->hasBias, true);
     ASSERT_EQ(cnode->inputIndex.size(), 3);
   }
   delete anf_transform;

mindspore/lite/tools/converter/parser/caffe/caffe_convolution_parser.cc

@@ -43,7 +43,6 @@ STATUS CaffeConvolutionParser::ParseGroupConvolution(schema::PrimitiveT *primiti
   depthwiseConv2DParam->padRight = attr->padRight;
   depthwiseConv2DParam->dilateW = attr->dilateW;
   depthwiseConv2DParam->dilateH = attr->dilateH;
-  depthwiseConv2DParam->hasBias = attr->hasBias;
   depthwiseConv2DParam->activationType = attr->activationType;
   delete attr;
   primitiveT->value.type = schema::PrimitiveType_DepthwiseConv2D;
@@ -104,7 +103,6 @@ PrimitiveC *CaffeConvolutionParser::ParseLitePrimitive(const caffe::LayerParamet
   attr->kernelH = kernel[0];
   attr->kernelW = kernel[1];
 
-  attr->hasBias = convParam.bias_term();
   attr->group = CaffeConvBaseParser::ParseGroup(convParam, proto.type());
   auto ret = CaffeConvBaseParser::ParseChannelOut(convParam, &(attr->channelOut));
   if (ret != RET_OK) {

mindspore/lite/tools/converter/parser/caffe/caffe_deconvolution_parser.cc

@@ -43,7 +43,6 @@ STATUS CaffeDeconvolutionParser::ParseGroupDeconvolution(schema::PrimitiveT *pri
   deDepthwiseConv2DParam->padRight = attr->padRight;
   deDepthwiseConv2DParam->dilateW = attr->dilateW;
   deDepthwiseConv2DParam->dilateH = attr->dilateH;
-  deDepthwiseConv2DParam->hasBias = attr->hasBias;
   deDepthwiseConv2DParam->activationType = attr->activationType;
   delete attr;
   primitive->value.type = schema::PrimitiveType_DeDepthwiseConv2D;
@@ -100,7 +99,6 @@ PrimitiveC *CaffeDeconvolutionParser::ParseLitePrimitive(const caffe::LayerParam
   attr->kernelH = kernel[0];
   attr->kernelW = kernel[1];
 
-  attr->hasBias = convParam.bias_term();
   attr->group = CaffeConvBaseParser::ParseGroup(convParam, proto.type());
   auto ret = CaffeConvBaseParser::ParseChannelOut(convParam, &(attr->channelOut));
   if (ret != RET_OK) {

mindspore/lite/tools/converter/parser/onnx/onnx_conv_parser.cc

@@ -46,7 +46,6 @@ bool OnnxConvParser::ParseGroupConvolution(const std::unique_ptr<schema::Conv2DT
   depthwiseConv2DParam->padRight = attr->padRight;
   depthwiseConv2DParam->dilateW = attr->dilateW;
   depthwiseConv2DParam->dilateH = attr->dilateH;
-  depthwiseConv2DParam->hasBias = attr->hasBias;
   depthwiseConv2DParam->activationType = attr->activationType;
 
   primitive->value.type = schema::PrimitiveType_DepthwiseConv2D;
@@ -162,7 +161,6 @@ lite::PrimitiveC *OnnxConvParser::ParseLitePrimitive(const onnx::GraphProto &onn
     attr->channelOut = dims.at(0);
     attr->channelIn = dims.at(3) * attr->group;
   }
-  attr->hasBias = onnx_node.input().size() == 3;
   if (onnx_node.op_type() == "ConvRelu" || onnx_node.op_type() == "Int8ConvRelu") {
     attr->activationType = schema::ActivationType_RELU;
   } else {

mindspore/lite/tools/converter/parser/onnx/onnx_deconv_parser.cc

@@ -46,7 +46,6 @@ bool OnnxDeConvParser::ParseGroupDeConvolution(const std::unique_ptr<schema::DeC
   deDepthwiseConv2DParam->padRight = attr->padRight;
   deDepthwiseConv2DParam->dilateW = attr->dilateW;
   deDepthwiseConv2DParam->dilateH = attr->dilateH;
-  deDepthwiseConv2DParam->hasBias = attr->hasBias;
   deDepthwiseConv2DParam->activationType = attr->activationType;
 
   primitive->value.type = schema::PrimitiveType_DeDepthwiseConv2D;
@@ -146,7 +145,6 @@ lite::PrimitiveC *OnnxDeConvParser::ParseLitePrimitive(const onnx::GraphProto &o
   attr->channelOut = weight_shape[1] * attr->group;
 
   attr->format = schema::Format::Format_NCHW;
-  attr->hasBias = onnx_node.input().size() == 3;
 
   auto primitive = std::make_unique<schema::PrimitiveT>();
   if (primitive == nullptr) {

mindspore/lite/tools/converter/parser/tflite/tflite_conv_parser.cc

@@ -41,7 +41,6 @@ lite::PrimitiveC *TfliteConvParser::ParseLitePrimitive(const std::unique_ptr<tfl
   attr->padMode = GetPadMode(tflite_attr->padding);
   attr->format = schema::Format::Format_NHWC;
   attr->activationType = GetActivationFunctionType(tflite_attr->fused_activation_function);
-  attr->hasBias = true;
 
   // get the conv op weight tensor
   auto weight_index = tflite_op->inputs[1];

mindspore/lite/tools/converter/parser/tflite/tflite_deconv_parser.cc

@@ -43,11 +43,6 @@ PrimitiveC *TfliteDeConvParser::ParseLitePrimitive(const std::unique_ptr<tflite:
   attr->padMode = GetPadMode(tflite_attr->padding);
   attr->format = schema::Format::Format_NHWC;
   attr->activationType = schema::ActivationType_NO_ACTIVATION;
-  if (tflite_op->inputs.size() > 3) {
-    attr->hasBias = true;
-  } else {
-    attr->hasBias = false;
-  }
 
   // get the conv op weight tensor
   auto weight_index = tflite_op->inputs[1];

mindspore/lite/tools/converter/parser/tflite/tflite_depthwise_conv_parser.cc

@@ -41,7 +41,6 @@ lite::PrimitiveC *TfliteDepthwiseConv2DParser::ParseLitePrimitive(const std::uni
   attr->padMode = GetPadMode(tflite_attr->padding);
   attr->format = schema::Format::Format_NHWC;
   attr->activationType = GetActivationFunctionType(tflite_attr->fused_activation_function);
-  attr->hasBias = true;
   attr->channelMultiplier = tflite_attr->depth_multiplier;
 
   // get the data tensor

mindspore/lite/tools/converter/quantizer/post_training_quantizer.cc

@@ -1470,25 +1470,6 @@ STATUS PostTrainingQuantizer::BiasCorrection(const FuncGraphPtr &func_graph) {
         parameter->set_default_param(param_value);
         cnode->add_input(parameter);
         DoBiasQuant(parameter, primitive_c);
-
-        auto op_type = (schema::PrimitiveType)primitive_c->Type();
-        if (op_type == schema::PrimitiveType_Conv2D) {
-          auto conv2d = primitive_c->primitiveT()->value.AsConv2D();
-          if (conv2d == nullptr) {
-            MS_LOG(ERROR) << "conv2d is null";
-            delete[] tensor_data;
-            return RET_ERROR;
-          }
-          conv2d->hasBias = true;
-        } else if (op_type == schema::PrimitiveType_DepthwiseConv2D) {
-          auto depthwise_conv2d = primitive_c->primitiveT()->value.AsDepthwiseConv2D();
-          if (depthwise_conv2d == nullptr) {
-            MS_LOG(ERROR) << "conv2d is null";
-            delete[] tensor_data;
-            return RET_ERROR;
-          }
-          depthwise_conv2d->hasBias = true;
-        }
         delete[] tensor_data;
       } else {
         MS_LOG(ERROR) << "unexpected input_quant_params size: " << input_quant_params.size();

mindspore/lite/tools/optimizer/fusion/conv_biasadd_fusion.cc

@@ -194,29 +194,6 @@ const AnfNodePtr ConvBiasaddFusion::Process(const FuncGraphPtr &func_graph, cons
     lite::ReturnCode::GetSingleReturnCode()->UpdateReturnCode(ret);
     return nullptr;
   }
-  auto primitive_c = GetValueNode<std::shared_ptr<lite::PrimitiveC>>(conv_node->input(0));
-  MS_ASSERT(primitive_c != nullptr);
-  auto type = primitive_c->Type();
-  if (type == schema::PrimitiveType_Conv2D) {
-    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::Conv2D>>(primitive_c));
-    auto primc = utils::cast<std::shared_ptr<mindspore::lite::Conv2D>>(primitive_c);
-    MS_ASSERT(primc != nullptr);
-    primc->SetHasBias(true);
-  } else if (type == schema::PrimitiveType_DepthwiseConv2D) {
-    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::DepthwiseConv2D>>(primitive_c));
-    auto primc = utils::cast<std::shared_ptr<mindspore::lite::DepthwiseConv2D>>(primitive_c);
-    MS_ASSERT(primc != nullptr);
-    primc->SetHasBias(true);
-  } else if (type == schema::PrimitiveType_DeConv2D) {
-    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::DeConv2D>>(primitive_c));
-    auto primc = utils::cast<std::shared_ptr<mindspore::lite::DeConv2D>>(primitive_c);
-    MS_ASSERT(primc != nullptr);
-    primc->SetHasBias(true);
-  } else {
-    MS_LOG(ERROR) << "Unsupported opType, " << type;
-    lite::ReturnCode::GetSingleReturnCode()->UpdateReturnCode(ret);
-    return nullptr;
-  }
   return conv_node;
 }
 }  // namespace mindspore::opt

mindspore/lite/tools/optimizer/fusion/conv_transform_fusion.cc

@@ -98,23 +98,6 @@ const AnfNodePtr ConvTransformFusion::Process(const FuncGraphPtr &func_graph, co
   GenNewConvTensor(func_graph, conv_node, kernel_nums, trans_scale, trans_bias);
   delete[] trans_bias;
   delete[] trans_scale;
-  auto primitive_c = GetValueNode<std::shared_ptr<lite::PrimitiveC>>(conv_node->input(0));
-  MS_ASSERT(primitive_c != nullptr);
-  auto type = primitive_c->Type();
-  if (type == schema::PrimitiveType_Conv2D) {
-    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::Conv2D>>(primitive_c));
-    auto primc = utils::cast<std::shared_ptr<mindspore::lite::Conv2D>>(primitive_c);
-    MS_ASSERT(primc != nullptr);
-    primc->SetHasBias(true);
-  } else if (type == schema::PrimitiveType_DepthwiseConv2D) {
-    MS_ASSERT(utils::isa<std::shared_ptr<mindspore::lite::DepthwiseConv2D>>(primitive_c));
-    auto primc = utils::cast<std::shared_ptr<mindspore::lite::DepthwiseConv2D>>(primitive_c);
-    MS_ASSERT(primc != nullptr);
-    primc->SetHasBias(true);
-  } else {
-    MS_LOG(ERROR) << "Unsupported opType, " << type;
-    return nullptr;
-  }
   pre_node->set_abstract(abstr);
   return pre_node;
 }

mindspore/lite/tools/optimizer/graph/group_depthwise_op_convert_pass.cc

@@ -92,7 +92,6 @@ bool GroupDepthwiseOpConvertPass::Run(const FuncGraphPtr &graph) {
       conv_attr->padRight = attr->padRight;
       conv_attr->dilateH = attr->dilateH;
       conv_attr->dilateW = attr->dilateW;
-      conv_attr->hasBias = attr->hasBias;
       conv_attr->activationType = attr->activationType;
 
       depthwise_primitivec->primitiveT()->value.type = schema::PrimitiveType_Conv2D;