!4011 fix bug of pooing int8

Merge pull request !4011 from fuzhiye/tmp

mindspore/lite/src/runtime/kernel/arm/base/pooling_base.cc

@@ -37,15 +37,11 @@ int PoolingBaseCPUKernel::SetQuantParam() {
   auto in_quant_arg = input_tensor->GetQuantParams();
   auto *out_tensor = outputs_.at(kOutputIndex);
   auto out_quant_arg = out_tensor->GetQuantParams();
-  if (in_quant_arg.front().scale != out_quant_arg.front().scale ||
-      in_quant_arg.front().zeroPoint != out_quant_arg.front().zeroPoint) {
-    MS_LOG(ERROR) << "Scale/ZeroPoint of output must be equal to input's";
-    return RET_ERROR;
-  }
   pooling_quant_arg_[0][0].scale_ = in_quant_arg.front().scale;
   pooling_quant_arg_[0][0].zp_ = in_quant_arg.front().zeroPoint;
   pooling_quant_arg_[1][0].scale_ = out_quant_arg.front().scale;
   pooling_quant_arg_[1][0].zp_ = out_quant_arg.front().zeroPoint;
+  pooling_param_->quant_args_ = pooling_quant_arg_;
   return RET_OK;
 }
 

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_3x3_fp16.cc

@@ -56,7 +56,7 @@ int Convolution3x3FP16CPUKernel::InitWeightBias() {
   int iC4 = UP_DIV(input_channel, C4NUM);
   int oC8 = UP_DIV(output_channel, C8NUM);
   // init weight
-  size_t transformed_size = iC4 * C8NUM * oC8 * C8NUM * 36 * sizeof(float16_t);
+  size_t transformed_size = iC4 * C4NUM * oC8 * C8NUM * 36 * sizeof(float16_t);
   transformed_filter_addr_ = reinterpret_cast<float16_t *>(malloc(transformed_size));
   if (transformed_filter_addr_ == nullptr) {
     MS_LOG(ERROR) << "malloc transformed_filter_addr_ failed.";
@@ -101,6 +101,8 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   int k_plane = 36;
   int iC4 = UP_DIV(conv_param_->input_channel_, C4NUM);
   int oC8 = UP_DIV(conv_param_->output_channel_, C8NUM);
+
+  /*=============================tile_buffer_============================*/
   size_t tile_buffer_size = thread_count_ * tile_num * k_plane * iC4 * C4NUM * sizeof(float16_t);
   tile_buffer_ = reinterpret_cast<float16_t *>(malloc(tile_buffer_size));
   if (tile_buffer_ == nullptr) {
@@ -109,6 +111,7 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   }
   memset(tile_buffer_, 0, tile_buffer_size);
 
+  /*=============================block_unit_buffer_============================*/
   size_t block_unit_buffer_size = thread_count_ * k_plane * C4NUM * sizeof(float16_t);
   block_unit_buffer_ = reinterpret_cast<float16_t *>(malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
@@ -117,6 +120,7 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   }
   memset(block_unit_buffer_, 0, block_unit_buffer_size);
 
+  /*=============================tmp_dst_buffer_============================*/
   size_t tmp_dst_buffer_size = thread_count_ * tile_num * k_plane * oC8 * C8NUM * sizeof(float16_t);
   tmp_dst_buffer_ = reinterpret_cast<float16_t *>(malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
@@ -125,6 +129,7 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_dst_buffer_, 0, tmp_dst_buffer_size);
 
+  /*=============================tmp_out_============================*/
   size_t tmp_out_size = oC8 * C8NUM * conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ *
                         tile_num * sizeof(float16_t);
   tmp_out_ = reinterpret_cast<float16_t *>(malloc(tmp_out_size));
@@ -134,6 +139,7 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_out_, 0, tmp_out_size);
 
+  /*=============================fp16_input_============================*/
   size_t fp16_input_size = conv_param_->input_channel_ * conv_param_->input_batch_ * conv_param_->input_h_ *
                            conv_param_->input_w_ * sizeof(float16_t);
   fp16_input_ = reinterpret_cast<float16_t *>(malloc(fp16_input_size));
@@ -143,7 +149,7 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   }
   memset(fp16_input_, 0, fp16_input_size);
 
-  // init nhwc4 input
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size =
     iC4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
   nhwc4_input_ = malloc(nhwc4_input_size);
@@ -152,12 +158,19 @@ int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
     return RET_ERROR;
   }
   memset(nhwc4_input_, 0, nhwc4_input_size);
+
+  /*=============================fp16_out_============================*/
+  size_t fp16_output_size = conv_param_->output_channel_ * conv_param_->output_batch_ * conv_param_->output_h_ *
+                            conv_param_->output_w_ * sizeof(float16_t);
+  fp16_out_ = reinterpret_cast<float16_t *>(malloc(fp16_output_size));
+  if (fp16_out_ == nullptr) {
+    MS_LOG(ERROR) << "malloc fp16_out_ failed.";
+    return RET_ERROR;
+  }
   return RET_OK;
 }
 
 void Convolution3x3FP16CPUKernel::ConfigInputOutput() {
-  auto output_tensor = outputs_.at(kOutputIndex);
-  output_tensor->SetFormat(schema::Format_NHWC);
   auto input_tensor = inputs_.at(kInputIndex);
   auto input_format = input_tensor->GetFormat();
   schema::Format execute_format = schema::Format_NHWC4;
@@ -201,6 +214,15 @@ int Convolution3x3FP16CPUKernel::ReSize() {
   if (tmp_out_ != nullptr) {
     free(tmp_out_);
   }
+  if (fp16_out_ != nullptr) {
+    free(fp16_out_);
+  }
+  if (fp16_input_ != nullptr) {
+    free(fp16_input_);
+  }
+  if (nhwc4_input_ != nullptr) {
+    free(nhwc4_input_);
+  }
 
   auto ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
@@ -216,9 +238,8 @@ int Convolution3x3FP16CPUKernel::ReSize() {
 }
 
 int Convolution3x3FP16CPUKernel::RunImpl(int task_id) {
-  auto output_addr = reinterpret_cast<float16_t *>(outputs_.at(kOutputIndex)->Data());
   Conv3x3Fp16(reinterpret_cast<float16_t *>(nhwc4_input_), transformed_filter_addr_,
-              reinterpret_cast<float16_t *>(bias_data_), output_addr, tile_buffer_, block_unit_buffer_, tmp_dst_buffer_,
+              reinterpret_cast<float16_t *>(bias_data_), fp16_out_, tile_buffer_, block_unit_buffer_, tmp_dst_buffer_,
               tmp_out_, task_id, conv_param_);
   return RET_OK;
 }
@@ -234,12 +255,13 @@ int Convolution3x3Fp16Impl(int task_id, LiteParallelGroupEnv *penv, void *cdata)
 }
 
 int Convolution3x3FP16CPUKernel::Run() {
+  // cast fp32 input data to fp16
   auto input_tensor = inputs_.at(kInputIndex);
   auto ori_input_data = reinterpret_cast<float *>(input_tensor->Data());
-  // cast fp32 input data to fp16
   for (int i = 0; i < input_tensor->ElementsNum(); ++i) {
     fp16_input_[i] = (float16_t)ori_input_data[i];
   }
+
   int in_batch = conv_param_->input_batch_;
   int in_h = conv_param_->input_h_;
   int in_w = conv_param_->input_w_;
@@ -251,6 +273,13 @@ int Convolution3x3FP16CPUKernel::Run() {
     MS_LOG(ERROR) << "conv3x3 fp16 error error_code[" << error_code << "]";
     return RET_ERROR;
   }
+
+  // cast fp16 out to fp32 data
+  auto out_tensor = outputs_.at(kOutputIndex);
+  auto output_addr = reinterpret_cast<float *>(out_tensor->Data());
+  for (int j = 0; j < out_tensor->ElementsNum(); ++j) {
+    output_addr[j] = (float)fp16_out_[j];
+  }
   return RET_OK;
 }
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_3x3_fp16.h

@@ -36,6 +36,9 @@ class Convolution3x3FP16CPUKernel : public ConvolutionBaseCPUKernel {
     if (fp16_weight_ != nullptr) {
       free(fp16_weight_);
     }
+    if (fp16_out_ != nullptr) {
+        free(fp16_out_);
+    }
     if (transformed_filter_addr_ != nullptr) {
       free(transformed_filter_addr_);
     }
@@ -64,6 +67,7 @@ class Convolution3x3FP16CPUKernel : public ConvolutionBaseCPUKernel {
  private:
   float16_t *fp16_input_;
   float16_t *fp16_weight_;
+  float16_t *fp16_out_;
   float16_t *transformed_filter_addr_;
   float16_t *tile_buffer_;
   float16_t *block_unit_buffer_;

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_fp16.cc

@@ -37,9 +37,9 @@ int ConvolutionFP16CPUKernel::InitWeightBias() {
   int in_channel = conv_param_->input_channel_;
   int out_channel = conv_param_->output_channel_;
   int oc8 = UP_DIV(out_channel, C8NUM);
-  int channel_block = UP_DIV(in_channel, C4NUM);
+  int ic4 = UP_DIV(in_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
-  int pack_weight_size = oc8 * channel_block * C8NUM * C4NUM * kernel_plane;
+  int pack_weight_size = oc8 * ic4 * C8NUM * C4NUM * kernel_plane;
 
   // init weight
   float *origin_weight = reinterpret_cast<float *>(inputs_.at(kWeightIndex)->Data());
@@ -49,10 +49,10 @@ int ConvolutionFP16CPUKernel::InitWeightBias() {
     MS_LOG(ERROR) << "malloc fp16_weight_ failed.";
     return RET_ERROR;
   }
-  memset(fp16_weight_, 0, fp16_weight_size);
   for (int i = 0; i < fp16_weight_size / sizeof(float16_t); ++i) {
     fp16_weight_[i] = (float16_t)origin_weight[i];
   }
+
   packed_weight_ = reinterpret_cast<float16_t *>(malloc(pack_weight_size * sizeof(float16_t)));
   if (packed_weight_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed_weight_ failed.";
@@ -95,6 +95,8 @@ int ConvolutionFP16CPUKernel::InitTmpBuffer() {
   int output_tile_count = UP_DIV(output_count, cal_num);
   int unit_size = kernel_plane * channel_block * C4NUM;
   int packed_input_size = output_tile_count * cal_num * unit_size;
+
+  /*=============================packed_input_============================*/
   packed_input_ = reinterpret_cast<float16_t *>(malloc(in_batch * packed_input_size * sizeof(float16_t)));
   if (packed_input_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed_input_ failed.";
@@ -102,6 +104,7 @@ int ConvolutionFP16CPUKernel::InitTmpBuffer() {
   }
   memset(packed_input_, 0, in_batch * packed_input_size * sizeof(float16_t));
 
+  /*=============================fp16_input_============================*/
   size_t fp16_input_size =
     in_channel * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
   fp16_input_ = reinterpret_cast<float16_t *>(malloc(fp16_input_size));
@@ -109,8 +112,8 @@ int ConvolutionFP16CPUKernel::InitTmpBuffer() {
     MS_LOG(ERROR) << "malloc fp16_input_ failed.";
     return RET_ERROR;
   }
-  memset(fp16_input_, 0, fp16_input_size);
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size = channel_block * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ *
                             conv_param_->input_w_ * sizeof(float16_t);
   nhwc4_input_ = malloc(nhwc4_input_size);
@@ -120,11 +123,21 @@ int ConvolutionFP16CPUKernel::InitTmpBuffer() {
   }
   memset(nhwc4_input_, 0, nhwc4_input_size);
 
+  /*=============================tmp_output_block_============================*/
   tmp_output_block_ = reinterpret_cast<float16_t *>(malloc(cal_num * out_channel * sizeof(float16_t)));
   if (tmp_output_block_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_output_block_ failed.";
     return RET_ERROR;
   }
+
+  /*=============================fp16_out_============================*/
+  size_t fp16_output_size =
+    out_channel * conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ * sizeof(float16_t);
+  fp16_out_ = reinterpret_cast<float16_t *>(malloc(fp16_output_size));
+  if (fp16_out_ == nullptr) {
+    MS_LOG(ERROR) << "malloc fp16_out_ failed.";
+    return RET_ERROR;
+  }
   return RET_OK;
 }
 
@@ -137,8 +150,6 @@ void ConvolutionFP16CPUKernel::ConfigInputOutput() {
     MS_LOG(ERROR) << "layout convert func is nullptr.";
     return;
   }
-  auto output_tensor = outputs_.at(kOutputIndex);
-  output_tensor->SetFormat(schema::Format_NHWC);
 }
 
 int ConvolutionFP16CPUKernel::Init() {
@@ -171,6 +182,12 @@ int ConvolutionFP16CPUKernel::ReSize() {
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
   }
+  if (fp16_input_ != nullptr) {
+    free(fp16_input_);
+  }
+  if (fp16_out_ != nullptr) {
+    free(fp16_out_);
+  }
 
   auto ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
@@ -186,9 +203,8 @@ int ConvolutionFP16CPUKernel::ReSize() {
 }
 
 int ConvolutionFP16CPUKernel::RunImpl(int task_id) {
-  auto output_addr = reinterpret_cast<float16_t *>(outputs_.at(kOutputIndex)->Data());
   ConvFp16(reinterpret_cast<float16_t *>(nhwc4_input_), packed_input_, packed_weight_,
-           reinterpret_cast<float16_t *>(bias_data_), tmp_output_block_, output_addr, task_id, conv_param_);
+           reinterpret_cast<float16_t *>(bias_data_), tmp_output_block_, fp16_out_, task_id, conv_param_);
   return RET_OK;
 }
 
@@ -203,12 +219,13 @@ int ConvolutionFp16Impl(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
 }
 
 int ConvolutionFP16CPUKernel::Run() {
+  // cast fp32 input data to fp16
   auto input_tensor = inputs_.at(kInputIndex);
   auto ori_input_data = reinterpret_cast<float *>(input_tensor->Data());
-  // cast fp32 input data to fp16
   for (int i = 0; i < input_tensor->ElementsNum(); ++i) {
     fp16_input_[i] = (float16_t)ori_input_data[i];
   }
+
   int in_batch = conv_param_->input_batch_;
   int in_h = conv_param_->input_h_;
   int in_w = conv_param_->input_w_;
@@ -220,6 +237,13 @@ int ConvolutionFP16CPUKernel::Run() {
     MS_LOG(ERROR) << "conv fp16 error error_code[" << error_code << "]";
     return RET_ERROR;
   }
+
+  // cast fp16 out to fp32 data
+  auto out_tensor = outputs_.at(kOutputIndex);
+  auto output_addr = reinterpret_cast<float *>(out_tensor->Data());
+  for (int j = 0; j < out_tensor->ElementsNum(); ++j) {
+    output_addr[j] = (float)fp16_out_[j];
+  }
   return RET_OK;
 }
 

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_fp16.h

@@ -23,15 +23,11 @@
 #include "src/runtime/kernel/arm/base/convolution_base.h"
 
 namespace mindspore::kernel {
-typedef void (*FP16_GEMM_FUNC)(float16_t *output, float16_t *input, float16_t *weight, float16_t *bias, size_t step,
-                               size_t ic4, size_t oc8, size_t offset, size_t mode, size_t writeC4, size_t relu,
-                               size_t relu6);
-
 class ConvolutionFP16CPUKernel : public ConvolutionBaseCPUKernel {
  public:
   ConvolutionFP16CPUKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs,
                            const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx)
-    : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx) {}
+      : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx) {}
   ~ConvolutionFP16CPUKernel() override {
     if (fp16_input_ != nullptr) {
       free(fp16_input_);
@@ -39,6 +35,9 @@ class ConvolutionFP16CPUKernel : public ConvolutionBaseCPUKernel {
     if (fp16_weight_ != nullptr) {
       free(fp16_weight_);
     }
+    if (fp16_out_ != nullptr) {
+      free(fp16_out_);
+    }
     if (packed_input_ != nullptr) {
       free(packed_input_);
     }
@@ -59,15 +58,13 @@ class ConvolutionFP16CPUKernel : public ConvolutionBaseCPUKernel {
   void ConfigInputOutput();
 
  private:
-  bool support_fp16_ = true;
   float16_t *fp16_input_;
   float16_t *fp16_weight_;
+  float16_t *fp16_out_;
   float16_t *packed_input_;
   float16_t *packed_weight_;
   float16_t *tmp_output_block_;
-  FP16_GEMM_FUNC gemm_func_ = nullptr;
 };
 }  // namespace mindspore::kernel
 
 #endif  // MINDSPORE_LITE_SRC_RUNTIME_KERNEL_ARM_FP16_CONVOLUTION_FP16_H_
-

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

@@ -89,6 +89,7 @@ int ConvolutionCPUKernel::InitTmpBuffer() {
   int output_tile_count = UP_DIV(output_count, TILE_NUM);
   int unit_size = kernel_plane * ic4 * C4NUM;
   int packed_input_size = output_tile_count * TILE_NUM * unit_size;
+  /*=============================packed_input============================*/
   packed_input_ = reinterpret_cast<float *>(malloc(in_batch * packed_input_size * sizeof(float)));
   if (packed_input_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed input failed.";
@@ -96,6 +97,7 @@ int ConvolutionCPUKernel::InitTmpBuffer() {
   }
   memset(packed_input_, 0, in_batch * packed_input_size * sizeof(float));
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size =
     ic4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float);
   nhwc4_input_ = malloc(nhwc4_input_size);
@@ -105,7 +107,7 @@ int ConvolutionCPUKernel::InitTmpBuffer() {
   }
   memset(nhwc4_input_, 0, nhwc4_input_size);
 
-  // tmp out
+  /*=============================tmp_output_block_============================*/
   tmp_output_block_ = reinterpret_cast<float *>(malloc(TILE_NUM * out_channel * sizeof(float)));
   if (tmp_output_block_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp output block failed.";

mindspore/lite/src/runtime/kernel/arm/fp32/convolution_3x3.cc

@@ -94,6 +94,8 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
   int iC4 = UP_DIV(conv_param_->input_channel_, C4NUM);
   int oC4 = UP_DIV(conv_param_->output_channel_, C4NUM);
   int k_plane = 16;
+
+  /*=============================tile_buffer_============================*/
   size_t tile_buffer_size = thread_count_ * TILE_NUM * k_plane * iC4 * C4NUM * sizeof(float);
   tile_buffer_ = reinterpret_cast<float *>(malloc(tile_buffer_size));
   if (tile_buffer_ == nullptr) {
@@ -102,6 +104,7 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
   }
   memset(tile_buffer_, 0, tile_buffer_size);
 
+  /*=============================block_unit_buffer_============================*/
   size_t block_unit_buffer_size = thread_count_ * k_plane * C4NUM * sizeof(float);
   block_unit_buffer_ = reinterpret_cast<float *>(malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
@@ -110,6 +113,7 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
   }
   memset(block_unit_buffer_, 0, block_unit_buffer_size);
 
+  /*=============================tmp_dst_buffer_============================*/
   size_t tmp_dst_buffer_size = thread_count_ * TILE_NUM * k_plane * oC4 * C4NUM * sizeof(float);
   tmp_dst_buffer_ = reinterpret_cast<float *>(malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
@@ -118,6 +122,7 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_dst_buffer_, 0, tmp_dst_buffer_size);
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size =
     iC4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float);
   nhwc4_input_ = malloc(nhwc4_input_size);
@@ -127,6 +132,7 @@ int Convolution3x3CPUKernel::InitTmpBuffer() {
   }
   memset(nhwc4_input_, 0, nhwc4_input_size);
 
+  /*=============================nc4hw4_out_============================*/
   size_t nc4hw4_out_size =
     oC4 * C4NUM * conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ * sizeof(float);
   nc4hw4_out_ = reinterpret_cast<float *>(malloc(nc4hw4_out_size));

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

@@ -165,6 +165,7 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
   int ic4 = UP_DIV(channel_in, C4NUM);
   int oc4 = UP_DIV(channel_out, C4NUM);
 
+  /*=============================trans_input_============================*/
   size_t tile_buffer_size = thread_count_ * TILE_NUM * input_unit_ * input_unit_ * ic4 * C4NUM * sizeof(float);
   trans_input_ = reinterpret_cast<float *>(malloc(tile_buffer_size));
   if (trans_input_ == nullptr) {
@@ -173,6 +174,7 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
   }
   memset(trans_input_, 0, tile_buffer_size);
 
+  /*=============================gemm_out_============================*/
   gemm_out_ = reinterpret_cast<float *>(
     malloc(thread_count_ * TILE_NUM * input_unit_ * input_unit_ * oc4 * C4NUM * sizeof(float)));
   if (gemm_out_ == nullptr) {
@@ -180,6 +182,7 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
     return RET_ERROR;
   }
 
+  /*=============================tmp_out_data_============================*/
   int out_w_block = UP_DIV(output_w, output_unit_);
   int out_h_block = UP_DIV(output_h, output_unit_);
   tmp_out_data_ = reinterpret_cast<float *>(
@@ -189,7 +192,8 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
     return RET_ERROR;
   }
 
-  tmp_data_ = reinterpret_cast<float *>(malloc(C4NUM * input_unit_ * input_unit_ * sizeof(float)));
+  /*=============================tmp_data_============================*/
+  tmp_data_ = reinterpret_cast<float *>(malloc(thread_count_ * C4NUM * input_unit_ * input_unit_ * sizeof(float)));
   if (tmp_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_data_ failed.";
     return RET_ERROR;
@@ -201,6 +205,7 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
   tmp_buffer_address_list_[2] = tmp_out_data_;
   tmp_buffer_address_list_[3] = tmp_data_;
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size =
     ic4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float);
   nhwc4_input_ = malloc(nhwc4_input_size);

mindspore/lite/src/runtime/kernel/arm/int8/convolution_3x3_int8.cc

@@ -108,6 +108,7 @@ int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
   int output_w = conv_param_->output_w_;
   int output_h = conv_param_->output_h_;
 
+  /*=============================tile_buffer_============================*/
   size_t tile_buffer_size = thread_count_ * TILE_NUM * 16 * ic8 * C8NUM * sizeof(int16_t);
   tile_buffer_ = reinterpret_cast<int16_t *>(malloc(tile_buffer_size));
   if (tile_buffer_ == nullptr) {
@@ -116,6 +117,7 @@ int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
   }
   memset(tile_buffer_, 0, tile_buffer_size);
 
+  /*=============================block_unit_buffer_============================*/
   size_t block_unit_buffer_size = thread_count_ * 4 * 4 * C8NUM * sizeof(int16_t);
   block_unit_buffer_ = reinterpret_cast<int16_t *>(malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
@@ -124,6 +126,7 @@ int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
   }
   memset(block_unit_buffer_, 0, block_unit_buffer_size);
 
+  /*=============================tmp_dst_buffer_============================*/
   size_t tmp_dst_buffer_size = thread_count_ * TILE_NUM * 16 * oc4 * C4NUM * sizeof(int32_t);
   tmp_dst_buffer_ = reinterpret_cast<int32_t *>(malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
@@ -132,6 +135,7 @@ int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_dst_buffer_, 0, tmp_dst_buffer_size);
 
+  /*=============================tmp_out_============================*/
   size_t tmp_out_size = oc4 * C4NUM * output_batch * output_w * output_h * sizeof(uint8_t);
   tmp_out_ = reinterpret_cast<int8_t *>(malloc(tmp_out_size));
   if (tmp_out_ == nullptr) {
@@ -140,6 +144,7 @@ int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_out_, 0, tmp_out_size);
 
+  /*=============================input_data_============================*/
   size_t c8_input_size = in_batch * input_h * input_w * ic8 * C8NUM * sizeof(int16_t);
   input_data_ = reinterpret_cast<int16_t *>(malloc(c8_input_size));
   if (input_data_ == nullptr) {
@@ -238,4 +243,3 @@ int Convolution3x3Int8CPUKernel::Run() {
   return RET_OK;
 }
 }  // namespace mindspore::kernel
-

mindspore/lite/src/runtime/kernel/arm/int8/convolution_int8.cc

@@ -116,6 +116,7 @@ int ConvolutionInt8CPUKernel::InitTmpBuffer() {
   int unit_size = plane_c4 * C4NUM * ic4 * C4NUM;
   int packed_input_size = output_tile_count * tile_num_ * unit_size;
 
+  /*=============================packed_input_============================*/
   packed_input_ = reinterpret_cast<int8_t *>(malloc(conv_param_->input_batch_ * packed_input_size));
   if (packed_input_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed_input_ failed.";
@@ -123,6 +124,7 @@ int ConvolutionInt8CPUKernel::InitTmpBuffer() {
   }
   memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size);
 
+  /*=============================input_sum_============================*/
   input_sum_ = reinterpret_cast<int32_t *>(malloc(tile_num_ * thread_count_ * sizeof(int32_t)));
   if (input_sum_ == nullptr) {
     MS_LOG(ERROR) << "malloc input_sum_ failed.";
@@ -130,6 +132,7 @@ int ConvolutionInt8CPUKernel::InitTmpBuffer() {
   }
   memset(input_sum_, 0, tile_num_ * thread_count_ * sizeof(int32_t));
 
+  /*=============================tmp_dst_============================*/
   size_t tmp_dst_size = thread_count_ * tile_num_ * conv_param_->output_channel_ * sizeof(int32_t);
   tmp_dst_ = reinterpret_cast<int32_t *>(malloc(tmp_dst_size));
   if (tmp_dst_ == nullptr) {
@@ -138,12 +141,14 @@ int ConvolutionInt8CPUKernel::InitTmpBuffer() {
   }
   memset(tmp_dst_, 0, tmp_dst_size);
 
+  /*=============================tmp_out_============================*/
   tmp_out_ = reinterpret_cast<int8_t *>(malloc(thread_count_ * tile_num_ * conv_param_->output_channel_));
   if (tmp_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_ failed.";
     return RET_ERROR;
   }
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size = ic4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_;
   nhwc4_input_ = malloc(nhwc4_input_size);
   if (nhwc4_input_ == nullptr) {
@@ -209,6 +214,7 @@ int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
   int unit_size = kernel_plane * ic4 * C4NUM;
   int packed_input_size = output_tile_count * tile_num_ * unit_size;
 
+  /*=============================packed_input_============================*/
   packed_input_ = reinterpret_cast<int8_t *>(malloc(conv_param_->input_batch_ * packed_input_size));
   if (packed_input_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed_input_ failed.";
@@ -216,6 +222,7 @@ int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
   }
   memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size);
 
+  /*=============================input_sum_============================*/
   input_sum_ = reinterpret_cast<int32_t *>(malloc(tile_num_ * thread_count_ * sizeof(int32_t)));
   if (input_sum_ == nullptr) {
     MS_LOG(ERROR) << "malloc input_sum_ failed.";
@@ -223,6 +230,7 @@ int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
   }
   memset(input_sum_, 0, tile_num_ * thread_count_ * sizeof(int32_t));
 
+  /*=============================tmp_dst_============================*/
   size_t tmp_dst_size = thread_count_ * tile_num_ * conv_param_->output_channel_ * sizeof(int32_t);
   tmp_dst_ = reinterpret_cast<int32_t *>(malloc(tmp_dst_size));
   if (tmp_dst_ == nullptr) {
@@ -231,12 +239,14 @@ int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
   }
   memset(tmp_dst_, 0, tmp_dst_size);
 
+  /*=============================tmp_out_============================*/
   tmp_out_ = reinterpret_cast<int8_t *>(malloc(thread_count_ * tile_num_ * conv_param_->output_channel_));
   if (tmp_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_ failed.";
     return RET_ERROR;
   }
 
+  /*=============================nhwc4_input_============================*/
   size_t nhwc4_input_size = ic4 * C4NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_;
   nhwc4_input_ = malloc(nhwc4_input_size);
   if (nhwc4_input_ == nullptr) {

mindspore/lite/src/runtime/kernel/arm/opclib/fp16/conv_fp16.cc

@@ -54,7 +54,13 @@ void IndirectGemmFp16_16x8(float16_t *output, float16_t *input, float16_t *weigh
         }
       }
 
-      (output + out_tile_offset)[0] = tmp_out;
+      (output + out_tile_offset)[0] = tmp_out + bias[i];
+      if (relu) {
+        (output + out_tile_offset)[0] = (output + out_tile_offset)[0] < 0 ? 0 : (output + out_tile_offset)[0];
+      } else if (relu6) {
+        (output + out_tile_offset)[0] = (output + out_tile_offset)[0] < 0 ? 0 : (output + out_tile_offset)[0];
+        (output + out_tile_offset)[0] = (output + out_tile_offset)[0] > 6 ? 6 : (output + out_tile_offset)[0];
+      }
     }
   }
 }
@@ -111,7 +117,8 @@ void ConvFp16(float16_t *input_data, float16_t *packed_input, float16_t *packed_
   int out_h = conv_param->output_h_;
   int out_w = conv_param->output_w_;
   int out_channel = conv_param->output_channel_;
-
+  bool relu = conv_param->is_relu_;
+  bool relu6 = conv_param->is_relu6_;
   // todo
   int thread_count = conv_param->thread_num_;
   int tile_n = 16;
@@ -125,7 +132,6 @@ void ConvFp16(float16_t *input_data, float16_t *packed_input, float16_t *packed_
 
   // we accumulate 4 channels per time for input blocks
   int ic4 = UP_DIV(in_channel, C4NUM);
-  int oc8 = UP_DIV(in_channel, C8NUM);
   int conv_depth = kernel_h * kernel_w;
   // bytes from one output's i-th channel to the next output's i-th channel
   // we write 32 bytes per st1 instruction, after which the pointer in register will step 32B forward
@@ -137,19 +143,18 @@ void ConvFp16(float16_t *input_data, float16_t *packed_input, float16_t *packed_
     for (int thread_id = task_id; thread_id < output_tile_count; thread_id += thread_count) {
       int start_index = thread_id * tile_n;
       int real_cal_num = (output_count - start_index) < tile_n ? (output_count - start_index) : tile_n;
-      float16_t *gemm_input =
-        (float16_t *)(packed_input + thread_id * unit_size * tile_n + gemm_in_batch_offset);
+      float16_t *gemm_input = (float16_t *)(packed_input + thread_id * unit_size * tile_n + gemm_in_batch_offset);
       Im2ColPackUnitFp16(input_data + in_batch_offset, conv_param, gemm_input, real_cal_num, start_index);
 
       int out_offset = thread_id * tile_n * out_channel + out_batch_offset;
       if (real_cal_num == tile_n) {
         float16_t *gemm_output = output_data + out_offset;
         IndirectGemmFp16_16x8(gemm_output, gemm_input, packed_weight, bias_data, conv_depth, ic4, out_channel,
-                              oc8 * C8NUM * sizeof(float16_t), 0, 0, 0, 0);
+                              out_channel * sizeof(float16_t), 0, 0, relu, relu6);
       } else {
         // res part
         IndirectGemmFp16_16x8(tmp_out_block, gemm_input, packed_weight, bias_data, conv_depth, ic4, out_channel,
-                              oc8 * C8NUM * sizeof(float16_t), 0, 0, 0, 0);
+                              out_channel * sizeof(float16_t), 0, 0, relu, relu6);
         memcpy(output_data + out_offset, tmp_out_block, real_cal_num * out_channel * sizeof(float16_t));
       }
     }
@@ -196,6 +201,8 @@ void Conv3x3Fp16(float16_t *input_data, float16_t *transed_weight, const float16
 
   // get real output
   // todo
+  bool relu = conv_param->is_relu_;
+  bool relu6 = conv_param->is_relu6_;
   for (int batch = 0; batch < output_batch; batch++) {
     int batch_size = batch * output_channel * output_h * output_w;
     for (int h = 0; h < output_h; h++) {
@@ -207,10 +214,14 @@ void Conv3x3Fp16(float16_t *input_data, float16_t *transed_weight, const float16
                            C8NUM * (h * out_w_block * output_unit + w) + oc8_res;
           int dst_offset = (h * output_w + w) * output_channel + c;
           (output_data + dst_offset)[0] = (tmp_out + src_offset)[0];
+          if (relu) {
+            (output_data + dst_offset)[0] = (output_data + dst_offset)[0] < 0 ? 0 : (output_data + dst_offset)[0];
+          } else if (relu6) {
+            (output_data + dst_offset)[0] = (output_data + dst_offset)[0] < 0 ? 0 : (output_data + dst_offset)[0];
+            (output_data + dst_offset)[0] = (output_data + dst_offset)[0] > 6 ? 6 : (output_data + dst_offset)[0];
+          }
         }
       }
     }
   }
 }
-
-

mindspore/lite/src/runtime/kernel/arm/opclib/fp16/pack_fp16.cc

@@ -56,10 +56,14 @@ void Im2ColPackUnitFp16(float16_t *input_data, ConvParameter *conv_param, float1
         for (int m = 0; m < channel_block; m++) {
           int channel_block_stride = input_x_stride + m * C4NUM;
           int channel_block_offset = input_plane_offset + m * 16 * C4NUM;
+#ifdef ENABLE_ARM64
+          vst1_f16(packed_input + channel_block_offset, vld1_f16(input_data + channel_block_stride));
+#else
           (packed_input + channel_block_offset)[0] = (input_data + channel_block_stride)[0];
           (packed_input + channel_block_offset)[1] = (input_data + channel_block_stride)[1];
           (packed_input + channel_block_offset)[2] = (input_data + channel_block_stride)[2];
           (packed_input + channel_block_offset)[3] = (input_data + channel_block_stride)[3];
+#endif
         }  // channel_block loop
       }    // kernel_w loop
     }      // kernel_h loop

mindspore/lite/src/runtime/kernel/arm/opclib/fp16/winograd_transform_fp16.cc

@@ -459,25 +459,30 @@ void Conv3x3Fp16OutputUnit(const float16_t *gemm_out, const float16_t *bias_data
   float16x8_t t34 = vaddq_f16(vaddq_f16(vsubq_f16(s14, s24), vmulq_n_f16(vsubq_f16(s34, s44), 8)), s54);
   float16x8_t t35 = vaddq_f16(vaddq_f16(vsubq_f16(s15, s25), vmulq_n_f16(vsubq_f16(s35, s45), 8)), s55);
 
-  float16x8_t d00 = vaddq_f16(vaddq_f16(vaddq_f16(t00, t01), vaddq_f16(t02, t03)), t04);
-  float16x8_t d01 = vaddq_f16(vsubq_f16(t01, t02), vmulq_n_f16(vsubq_f16(t03, t04), 2));
-  float16x8_t d02 = vaddq_f16(vaddq_f16(t01, t02), vmulq_n_f16(vaddq_f16(t03, t04), 4));
-  float16x8_t d03 = vaddq_f16(vaddq_f16(vsubq_f16(t01, t02), vmulq_n_f16(vsubq_f16(t03, t04), 8)), t05);
-
-  float16x8_t d10 = vaddq_f16(vaddq_f16(vaddq_f16(t10, t11), vaddq_f16(t12, t13)), t14);
-  float16x8_t d11 = vaddq_f16(vsubq_f16(t11, t12), vmulq_n_f16(vsubq_f16(t13, t14), 2));
-  float16x8_t d12 = vaddq_f16(vaddq_f16(t11, t12), vmulq_n_f16(vaddq_f16(t13, t14), 4));
-  float16x8_t d13 = vaddq_f16(vaddq_f16(vsubq_f16(t11, t12), vmulq_n_f16(vsubq_f16(t13, t14), 8)), t15);
-
-  float16x8_t d20 = vaddq_f16(vaddq_f16(vaddq_f16(t20, t21), vaddq_f16(t22, t23)), t24);
-  float16x8_t d21 = vaddq_f16(vsubq_f16(t21, t22), vmulq_n_f16(vsubq_f16(t23, t24), 2));
-  float16x8_t d22 = vaddq_f16(vaddq_f16(t21, t22), vmulq_n_f16(vaddq_f16(t23, t24), 4));
-  float16x8_t d23 = vaddq_f16(vaddq_f16(vsubq_f16(t21, t22), vmulq_n_f16(vsubq_f16(t23, t24), 8)), t25);
-
-  float16x8_t d30 = vaddq_f16(vaddq_f16(vaddq_f16(t30, t31), vaddq_f16(t32, t33)), t34);
-  float16x8_t d31 = vaddq_f16(vsubq_f16(t31, t32), vmulq_n_f16(vsubq_f16(t33, t34), 2));
-  float16x8_t d32 = vaddq_f16(vaddq_f16(t31, t32), vmulq_n_f16(vaddq_f16(t33, t34), 4));
-  float16x8_t d33 = vaddq_f16(vaddq_f16(vsubq_f16(t31, t32), vmulq_n_f16(vsubq_f16(t33, t34), 8)), t35);
+  float16x8_t bias_ptr = vld1q_f16(bias_data);
+  float16x8_t d00 = vaddq_f16(vaddq_f16(vaddq_f16(vaddq_f16(t00, t01), vaddq_f16(t02, t03)), t04), bias_ptr);
+  float16x8_t d01 = vaddq_f16(vaddq_f16(vsubq_f16(t01, t02), vmulq_n_f16(vsubq_f16(t03, t04), 2)), bias_ptr);
+  float16x8_t d02 = vaddq_f16(vaddq_f16(vaddq_f16(t01, t02), vmulq_n_f16(vaddq_f16(t03, t04), 4)), bias_ptr);
+  float16x8_t d03 =
+    vaddq_f16(vaddq_f16(vaddq_f16(vsubq_f16(t01, t02), vmulq_n_f16(vsubq_f16(t03, t04), 8)), t05), bias_ptr);
+
+  float16x8_t d10 = vaddq_f16(vaddq_f16(vaddq_f16(vaddq_f16(t10, t11), vaddq_f16(t12, t13)), t14), bias_ptr);
+  float16x8_t d11 = vaddq_f16(vaddq_f16(vsubq_f16(t11, t12), vmulq_n_f16(vsubq_f16(t13, t14), 2)), bias_ptr);
+  float16x8_t d12 = vaddq_f16(vaddq_f16(vaddq_f16(t11, t12), vmulq_n_f16(vaddq_f16(t13, t14), 4)), bias_ptr);
+  float16x8_t d13 =
+    vaddq_f16(vaddq_f16(vaddq_f16(vsubq_f16(t11, t12), vmulq_n_f16(vsubq_f16(t13, t14), 8)), t15), bias_ptr);
+
+  float16x8_t d20 = vaddq_f16(vaddq_f16(vaddq_f16(vaddq_f16(t20, t21), vaddq_f16(t22, t23)), t24), bias_ptr);
+  float16x8_t d21 = vaddq_f16(vaddq_f16(vsubq_f16(t21, t22), vmulq_n_f16(vsubq_f16(t23, t24), 2)), bias_ptr);
+  float16x8_t d22 = vaddq_f16(vaddq_f16(vaddq_f16(t21, t22), vmulq_n_f16(vaddq_f16(t23, t24), 4)), bias_ptr);
+  float16x8_t d23 =
+    vaddq_f16(vaddq_f16(vaddq_f16(vsubq_f16(t21, t22), vmulq_n_f16(vsubq_f16(t23, t24), 8)), t25), bias_ptr);
+
+  float16x8_t d30 = vaddq_f16(vaddq_f16(vaddq_f16(vaddq_f16(t30, t31), vaddq_f16(t32, t33)), t34), bias_ptr);
+  float16x8_t d31 = vaddq_f16(vaddq_f16(vsubq_f16(t31, t32), vmulq_n_f16(vsubq_f16(t33, t34), 2)), bias_ptr);
+  float16x8_t d32 = vaddq_f16(vaddq_f16(vaddq_f16(t31, t32), vmulq_n_f16(vaddq_f16(t33, t34), 4)), bias_ptr);
+  float16x8_t d33 =
+    vaddq_f16(vaddq_f16(vaddq_f16(vsubq_f16(t31, t32), vmulq_n_f16(vsubq_f16(t33, t34), 8)), t35), bias_ptr);
 
   vst1q_f16(output_data, d00);
   vst1q_f16(output_data + 8, d01);

mindspore/lite/src/runtime/kernel/arm/opclib/fp32/conv.cc

@@ -103,6 +103,9 @@ void ConvWinogardFp32(float *input_data, float *trans_weight, const float *bias_
   float *gemm_out = buffer_list[1];
   float *tmp_out_data = buffer_list[2];
   float *tmp_data = buffer_list[3];
+  int trans_input_offset = TILE_NUM * input_unit_square * ic4 * C4NUM;
+  int gemm_out_offset = TILE_NUM * input_unit_square * oc4 * C4NUM;
+  int tmp_data_offset = input_unit_square * C4NUM;
   // step 1 : filter transform (pre-processed offline)
   // step 2 : input transform (online)
   for (int b = 0; b < in_batch; b++) {
@@ -110,15 +113,16 @@ void ConvWinogardFp32(float *input_data, float *trans_weight, const float *bias_
       int out_tile_index = thread_id * TILE_NUM;
       int cal_num = output_count - thread_id * TILE_NUM;
       cal_num = cal_num > TILE_NUM ? TILE_NUM : cal_num;
-      WinogradInputTransform(input_data, trans_input, tmp_data, cal_num, out_tile_index, out_w_block, conv_param,
+      WinogradInputTransform(input_data, trans_input + task_id * trans_input_offset,
+                             tmp_data + task_id * tmp_data_offset, cal_num, out_tile_index, out_w_block, conv_param,
                              input_trans_func);
       // step 3 : gemm
-      gemm_func(gemm_out, trans_input, trans_weight, nullptr, input_unit_square, ic4, oc4 * C4NUM, output_offset, 1, 1,
-                0, 0);
+      gemm_func(gemm_out + task_id * gemm_out_offset, trans_input + task_id * trans_input_offset, trans_weight, nullptr,
+                input_unit_square, ic4, oc4 * C4NUM, output_offset, 1, 1, 0, 0);
 
       // step 4 : output transform
-      WinogradOutputTransform(gemm_out, tmp_out_data, bias_data, cal_num, out_tile_index, out_w_block, conv_param,
-                              output_trans_func);
+      WinogradOutputTransform(gemm_out + task_id * gemm_out_offset, tmp_out_data, bias_data, cal_num, out_tile_index,
+                              out_w_block, conv_param, output_trans_func);
     }
   }
   // get real output
@@ -191,20 +195,25 @@ void Conv3x3Fp32(float *input_data, float *transed_weight, const float *bias_dat
   float *block_unit_buffer = buffer_list[1];
   float *tmp_dst_buffer = buffer_list[2];
   float *nc4hw4_out = buffer_list[3];
+  int tile_buffer_offset = TILE_NUM * input_unit_square * ic4 * C4NUM;
+  int block_unit_buffer_offset = input_unit_square * C4NUM;
+  int tmp_dst_buffer_offset = TILE_NUM * input_unit_square * oc4 * C4NUM;
 
   int input_batch = conv_param->input_batch_;
   for (int batch = 0; batch < input_batch; batch++) {
     for (int thread_id = task_id; thread_id < output_tile_count; thread_id += thread_count) {
       int start_index = thread_id * TILE_NUM;
       int real_cal_num = (output_count - start_index) < TILE_NUM ? (output_count - start_index) : TILE_NUM;
-      Conv3x3Fp32InputTransform(input_data, tile_buffer, block_unit_buffer, start_index, real_cal_num, out_w_block,
-                                conv_param);
+      Conv3x3Fp32InputTransform(input_data, tile_buffer + task_id * tile_buffer_offset,
+                                block_unit_buffer + task_id * block_unit_buffer_offset, start_index, real_cal_num,
+                                out_w_block, conv_param);
 
-      gemm_func(tmp_dst_buffer, tile_buffer, transed_weight, nullptr, input_unit_square, ic4, oc4 * C4NUM,
+      gemm_func(tmp_dst_buffer + task_id * tmp_dst_buffer_offset, tile_buffer + task_id * tile_buffer_offset,
+                transed_weight, nullptr, input_unit_square, ic4, oc4 * C4NUM,
                 oc4 * C4NUM * input_unit_square * sizeof(float), 1, 1, 0, 0);
 
-      Conv3x3Fp32OutputTransform(tmp_dst_buffer, nc4hw4_out, bias_data, start_index, real_cal_num, out_w_block,
-                                 conv_param);
+      Conv3x3Fp32OutputTransform(tmp_dst_buffer + task_id * tmp_dst_buffer_offset, nc4hw4_out, bias_data, start_index,
+                                 real_cal_num, out_w_block, conv_param);
     }
     PackNC4HW4ToNHWCFp32(nc4hw4_out, output_data, 1, conv_param->output_h_ * conv_param->output_w_, output_channel);
   }

mindspore/lite/src/runtime/kernel/arm/opclib/int8/pooling_int8.cc

@@ -31,8 +31,13 @@ void AvgPoolingInt8(const int8_t *input_ptr, int8_t *output_ptr, PoolingParamete
   int output_h = pooling_param->output_h_;
   int output_batch = pooling_param->output_batch_;
   int out_plane = output_w * output_h;
-  int16_t out_min = INT8_MIN;
-  int16_t out_max = INT8_MAX;
+  float input_scale = pooling_param->quant_args_[0][0].scale_;
+  int input_zp = pooling_param->quant_args_[0][0].zp_;
+  float output_scale = pooling_param->quant_args_[1][0].scale_;
+  int output_zp = pooling_param->quant_args_[1][0].zp_;
+  double real_multiplier = input_scale / output_scale;
+  int8_t out_min = INT8_MIN;
+  int8_t out_max = INT8_MAX;
 
   for (int batch = 0; batch < output_batch; batch++) {
     int in_batch_offset = batch * in_h * in_w * channel;
@@ -60,9 +65,10 @@ void AvgPoolingInt8(const int8_t *input_ptr, int8_t *output_ptr, PoolingParamete
           }  // win_w loop
         }    // win_h loop
         int16_t tmp_out = round((float)tmp_avg / (float)real_count);
-        int16_t real_out = tmp_out < out_min ? out_min : tmp_out;
+        tmp_out = (int8_t)(round((tmp_out - input_zp) * real_multiplier) + output_zp);
+        int8_t real_out = tmp_out < out_min ? out_min : tmp_out;
         real_out = real_out > out_max ? out_max : real_out;
-        *(output_ptr + out_channel_offset) = (int8_t)real_out;
+        *(output_ptr + out_channel_offset) = real_out;
       }  // in_channel loop
     }    // out_plane loop
   }      // out_batch loop