!12579 [MS][LITE][CPU]bias_add_int8 accuracy issue

From: @fuzhiye
Reviewed-by: @zhang_xue_tong,@hangangqiang
Signed-off-by: @zhang_xue_tong

mindspore/lite/src/runtime/kernel/arm/int8/add_int8.h

@@ -33,7 +33,7 @@ class QuantizedAddCPUKernel : public LiteKernel {
       : LiteKernel(parameter, inputs, outputs, ctx, primitive) {
     arith_para_ = reinterpret_cast<ArithmeticParameter *>(parameter);
   }
-  ~QuantizedAddCPUKernel() override {}
+  ~QuantizedAddCPUKernel() override = default;
 
   int Init() override;
   int ReSize() override;

mindspore/lite/src/runtime/kernel/arm/int8/bias_add_int8.cc

@@ -15,10 +15,7 @@
  */
 
 #include "src/runtime/kernel/arm/int8/bias_add_int8.h"
-#include "nnacl/fp32/arithmetic_fp32.h"
-#include "nnacl/errorcode.h"
 #include "src/kernel_registry.h"
-#include "include/errorcode.h"
 
 using mindspore::lite::KernelRegistrar;
 using mindspore::lite::RET_ERROR;
@@ -26,52 +23,5 @@ using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_BiasAdd;
 
 namespace mindspore::kernel {
-int BiasAddInt8CPUKernel::Init() {
-  if (!InferShapeDone()) {
-    return RET_OK;
-  }
-  return ReSize();
-}
-
-int BiasAddInt8CPUKernel::ReSize() {
-  auto bias_param = reinterpret_cast<ArithmeticParameter *>(op_parameter_);
-  auto dims = in_tensors_.at(0)->shape();
-  bias_param->ndim_ = dims.size();
-  if (bias_param->ndim_ < 1 || bias_param->ndim_ > 5) {
-    MS_LOG(ERROR) << "input shape is invalid";
-    return RET_ERROR;
-  }
-  for (size_t i = 0; i < bias_param->ndim_; i++) {
-    bias_param->in_shape0_[i] = dims[i];
-    bias_param->in_shape1_[i] = 1;
-    bias_param->out_shape_[i] = dims[i];
-  }
-  bias_param->in_shape1_[bias_param->ndim_ - 1] = dims[bias_param->ndim_ - 1];
-  return RET_OK;
-}
-
-int BiasAddInt8CPUKernel::Run() {
-  auto in = reinterpret_cast<int8_t *>(in_tensors_.at(0)->MutableData());
-  auto bias = reinterpret_cast<int8_t *>(in_tensors_.at(1)->MutableData());
-  auto out = reinterpret_cast<int8_t *>(out_tensors_.at(0)->MutableData());
-  size_t data_size = in_tensors_.at(0)->ElementsNum();
-  auto tile_in = static_cast<int8_t *>(ctx_->allocator->Malloc(data_size));
-  if (tile_in == nullptr) {
-    MS_LOG(ERROR) << "Failed to malloc momery";
-    return NNACL_ERR;
-  }
-  auto tile_bias = static_cast<int8_t *>(ctx_->allocator->Malloc(data_size));
-  if (tile_bias == nullptr) {
-    MS_LOG(ERROR) << "Failed to malloc momery";
-    ctx_->allocator->Free(tile_in);
-    return NNACL_ERR;
-  }
-  BroadcastAddInt8(in, bias, tile_in, tile_bias, out, data_size,
-                   reinterpret_cast<ArithmeticParameter *>(op_parameter_));
-  ctx_->allocator->Free(tile_in);
-  ctx_->allocator->Free(tile_bias);
-  return NNACL_OK;
-}
-
 REG_KERNEL(kCPU, kNumberTypeInt8, PrimitiveType_BiasAdd, LiteKernelCreator<BiasAddInt8CPUKernel>)
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/arm/int8/bias_add_int8.h

@@ -17,26 +17,16 @@
 #define MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_INT8_BAIS_ADD_INT8_H_
 
 #include <vector>
-#include "src/lite_kernel.h"
-#include "nnacl/arithmetic.h"
-#include "nnacl/int8/add_int8.h"
-#include "nnacl/int8/arithmetic_int8.h"
+#include "src/runtime/kernel/arm/int8/add_int8.h"
 
 namespace mindspore::kernel {
-class BiasAddInt8CPUKernel : public LiteKernel {
+class BiasAddInt8CPUKernel : public QuantizedAddCPUKernel {
  public:
   BiasAddInt8CPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
                        const std::vector<lite::Tensor *> &outputs, const lite::InnerContext *ctx,
                        const mindspore::lite::PrimitiveC *primitive)
-      : LiteKernel(parameter, inputs, outputs, ctx, primitive), ctx_(ctx) {}
-  ~BiasAddInt8CPUKernel() = default;
-
-  int Init() override;
-  int ReSize() override;
-  int Run() override;
-
- private:
-  const lite::InnerContext *ctx_;
+      : QuantizedAddCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
+  ~BiasAddInt8CPUKernel() override = default;
 };
 }  // namespace mindspore::kernel