1.molloc buffer using memory pool

2.rewrite resize func

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

@@ -93,6 +93,18 @@ int ConvolutionBaseCPUKernel::Init() {
   return RET_OK;
 }
 
+int ConvolutionBaseCPUKernel::CheckResizeValid() {
+  // ===============check in channel================= //
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto filter_in_channel = filter_tensor->Channel();
+  int resize_in_channel = in_tensors_.at(kInputIndex)->Channel();
+  if (filter_in_channel != resize_in_channel) {
+    MS_LOG(ERROR) << "Channel of resized input should be equal to in channel of filter.";
+    return RET_ERROR;
+  }
+  return RET_OK;
+}
+
 int ConvolutionBaseCPUKernel::CheckLayout(lite::tensor::Tensor *input_tensor) {
   auto data_type = input_tensor->data_type();
   auto input_format = input_tensor->GetFormat();

mindspore/lite/src/runtime/kernel/arm/base/convolution_base.h

@@ -58,6 +58,7 @@ class ConvolutionBaseCPUKernel : public LiteKernel {
   int SetFilterTensorQuantParam();
   int SetOutputTensorQuantParam();
   int SetQuantMultiplier();
+  int CheckResizeValid();
   void FreeQuantParam();
 
  protected:

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

@@ -50,11 +50,14 @@ void ProcessFilterFp16(float16_t *origin_weight, float16_t *dst_weight, ConvPara
 }
 
 int Convolution3x3FP16CPUKernel::InitWeightBias() {
-  auto input_channel = conv_param_->input_channel_;
-  int output_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
   int iC8 = UP_DIV(input_channel, C8NUM);
   int oC8 = UP_DIV(output_channel, C8NUM);
-  // init weight
+  // ===========================init weight========================== //
   size_t transformed_size = iC8 * C8NUM * oC8 * C8NUM * 36 * sizeof(float16_t);
   transformed_filter_addr_ = reinterpret_cast<float16_t *>(malloc(transformed_size));
   if (transformed_filter_addr_ == nullptr) {
@@ -69,7 +72,7 @@ int Convolution3x3FP16CPUKernel::InitWeightBias() {
   }
   ProcessFilterFp16(execute_weight_, transformed_filter_addr_, conv_param_);
 
-  // init bias
+  // =============================init bias========================= //
   size_t new_bias_size = oC8 * C8NUM * sizeof(float16_t);
   bias_data_ = malloc(new_bias_size);
   if (bias_data_ == nullptr) {
@@ -92,55 +95,32 @@ int Convolution3x3FP16CPUKernel::InitWeightBias() {
 int Convolution3x3FP16CPUKernel::InitTmpBuffer() {
   const int tile_num = 16;
   const int k_plane = 36;
-  int iC8 = UP_DIV(conv_param_->input_channel_, C8NUM);
   int oC8 = UP_DIV(conv_param_->output_channel_, C8NUM);
-
-  /*=============================tile_buffer_============================*/
-  size_t tile_buffer_size = thread_count_ * tile_num * k_plane * iC8 * C8NUM * sizeof(float16_t);
-  tile_buffer_ = reinterpret_cast<float16_t *>(malloc(tile_buffer_size));
-  if (tile_buffer_ == nullptr) {
-    MS_LOG(ERROR) << "malloc tile_buffer_ failed.";
-    return RET_ERROR;
-  }
-  memset(tile_buffer_, 0, tile_buffer_size);
-
+  MS_ASSERT(ctx_->allocator != nullptr);
   /*=============================block_unit_buffer_============================*/
   size_t block_unit_buffer_size = thread_count_ * k_plane * C8NUM * sizeof(float16_t);
-  block_unit_buffer_ = reinterpret_cast<float16_t *>(malloc(block_unit_buffer_size));
+  block_unit_buffer_ = reinterpret_cast<float16_t *>(ctx_->allocator->Malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc block_unit_buffer_ failed.";
     return RET_ERROR;
   }
-  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));
+  tmp_dst_buffer_ = reinterpret_cast<float16_t *>(ctx_->allocator->Malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_dst_buffer_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_dst_buffer_, 0, tmp_dst_buffer_size);
 
   /*=============================tmp_out_============================*/
   int new_out_plane = UP_DIV(conv_param_->output_h_, C4NUM) * UP_DIV(conv_param_->output_w_, C4NUM) * C4NUM * C4NUM;
   size_t tmp_out_size = oC8 * C8NUM * conv_param_->output_batch_ * new_out_plane * sizeof(float16_t);
-  tmp_out_ = reinterpret_cast<float16_t *>(malloc(tmp_out_size));
+  tmp_out_ = reinterpret_cast<float16_t *>(ctx_->allocator->Malloc(tmp_out_size));
   if (tmp_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_out_, 0, tmp_out_size);
-
-  /*=============================nhwc4_input_============================*/
-  size_t nhwc8_input_size =
-    iC8 * C8NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
-  nhwc4_input_ = malloc(nhwc8_input_size);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc8_input_size);
 
   return RET_OK;
 }
@@ -160,12 +140,22 @@ int Convolution3x3FP16CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
   return ReSize();
 }
 
 int Convolution3x3FP16CPUKernel::ReSize() {
-  FreeTmpBuffer();
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
 
+  FreeTmpBuffer();
   if (tile_buffer_ != nullptr) {
     free(tile_buffer_);
     tile_buffer_ = nullptr;
@@ -174,21 +164,35 @@ int Convolution3x3FP16CPUKernel::ReSize() {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
-  auto ret = ConvolutionBaseCPUKernel::Init();
+
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return ret;
   }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
+  const int tile_num = 16;
+  const int k_plane = 36;
+  int iC8 = UP_DIV(conv_param_->input_channel_, C8NUM);
+
+  /*=============================nhwc4_input_============================*/
+  size_t nhwc8_input_size =
+    iC8 * C8NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
+  nhwc4_input_ = malloc(nhwc8_input_size);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
     return RET_ERROR;
   }
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  memset(nhwc4_input_, 0, nhwc8_input_size);
+
+  /*=============================tile_buffer_============================*/
+  size_t tile_buffer_size = thread_count_ * tile_num * k_plane * iC8 * C8NUM * sizeof(float16_t);
+  tile_buffer_ = reinterpret_cast<float16_t *>(malloc(tile_buffer_size));
+  if (tile_buffer_ == nullptr) {
+    MS_LOG(ERROR) << "malloc tile_buffer_ failed.";
     return RET_ERROR;
   }
+  memset(tile_buffer_, 0, tile_buffer_size);
+
   return RET_OK;
 }
 
@@ -220,6 +224,11 @@ int Convolution3x3FP16CPUKernel::Run() {
     MS_LOG(ERROR) << "Get execute tensor failed.";
     return ret;
   }
+  ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
   int in_batch = conv_param_->input_batch_;
   int in_h = conv_param_->input_h_;
   int in_w = conv_param_->input_w_;
@@ -229,6 +238,7 @@ int Convolution3x3FP16CPUKernel::Run() {
   int error_code = LiteBackendParallelLaunch(Convolution3x3Fp16Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv3x3 fp16 error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
 
@@ -248,6 +258,7 @@ int Convolution3x3FP16CPUKernel::Run() {
 
   ConvolutionBaseFP16CPUKernel::IfCastOutput();
   ConvolutionBaseFP16CPUKernel::FreeTmpBuffer();
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

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

@@ -30,23 +30,11 @@ class Convolution3x3FP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
                               const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
                               const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~Convolution3x3FP16CPUKernel() override { FreeTmpBuffer(); }
-
-  int Init() override;
-  int ReSize() override;
-  int Run() override;
-  int RunImpl(int task_id);
-  int InitWeightBias();
-  int InitTmpBuffer();
-  void ConfigInputOutput();
-
- private:
-  void FreeTmpBuffer() {
+  ~Convolution3x3FP16CPUKernel() override {
     if (fp16_weight_ != nullptr) {
       free(fp16_weight_);
       fp16_weight_ = nullptr;
     }
-
     if (transformed_filter_addr_ != nullptr) {
       free(transformed_filter_addr_);
       transformed_filter_addr_ = nullptr;
@@ -55,16 +43,28 @@ class Convolution3x3FP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
       free(tile_buffer_);
       tile_buffer_ = nullptr;
     }
+  }
+
+  int Init() override;
+  int ReSize() override;
+  int Run() override;
+  int RunImpl(int task_id);
+  int InitWeightBias();
+  int InitTmpBuffer();
+  void ConfigInputOutput();
+
+ private:
+  void FreeTmpBuffer() {
     if (block_unit_buffer_ != nullptr) {
-      free(block_unit_buffer_);
+      ctx_->allocator->Free(block_unit_buffer_);
       block_unit_buffer_ = nullptr;
     }
     if (tmp_dst_buffer_ != nullptr) {
-      free(tmp_dst_buffer_);
+      ctx_->allocator->Free(tmp_dst_buffer_);
       tmp_dst_buffer_ = nullptr;
     }
     if (tmp_out_ != nullptr) {
-      free(tmp_out_);
+      ctx_->allocator->Free(tmp_out_);
       tmp_out_ = nullptr;
     }
   }

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

@@ -143,14 +143,19 @@ int ConvolutionFP16CPUKernel::Init() {
 }
 
 int ConvolutionFP16CPUKernel::ReSize() {
-  FreeTmpBuffer();
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
 
+  FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init fail!ret: " << ret;
     return ret;

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_sw_fp16.cc

@@ -59,16 +59,19 @@ int ConvolutionSWFP16CPUKernel::ProcessFilter() {
 }
 
 int ConvolutionSWFP16CPUKernel::InitWeightBias() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_channel = conv_param_->input_channel_;
-  int out_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  int kernel_h = filter_tensor->Height();
+  int kernel_w = filter_tensor->Width();
+  int in_channel = filter_tensor->Channel();
+  int out_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = in_channel;
+  conv_param_->output_channel_ = out_channel;
   int oc4 = UP_DIV(out_channel, C4NUM);
   int ic4 = UP_DIV(in_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
   int pack_weight_size = oc4 * ic4 * C4NUM * C4NUM * kernel_plane;
 
-  // init weight
+  // ========================init weight==================== //
   packed_weight_ = reinterpret_cast<float16_t *>(malloc(pack_weight_size * sizeof(float16_t)));
   if (packed_weight_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed_weight_ failed.";
@@ -81,7 +84,7 @@ int ConvolutionSWFP16CPUKernel::InitWeightBias() {
     return ret;
   }
 
-  // init bias
+  // =======================init bias====================== //
   bias_data_ = malloc(oc4 * C4NUM * sizeof(float16_t));
   if (bias_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc bias_data_ failed.";
@@ -101,29 +104,16 @@ int ConvolutionSWFP16CPUKernel::InitWeightBias() {
 }
 
 int ConvolutionSWFP16CPUKernel::InitTmpBuffer() {
-  int in_channel = conv_param_->input_channel_;
   int out_channel = conv_param_->output_channel_;
-  int channel_block = UP_DIV(in_channel, C4NUM);
   int oc4 = UP_DIV(out_channel, C4NUM);
 
-  /*=============================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);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
-
   /*=============================tmp_output_block_============================*/
-  tmp_output_block_ = reinterpret_cast<float16_t *>(malloc(conv_param_->output_batch_ * conv_param_->output_h_ *
-                                                           conv_param_->output_w_ * oc4 * C4NUM * sizeof(float16_t)));
+  tmp_output_block_ = reinterpret_cast<float16_t *>(ctx_->allocator->Malloc(
+    conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ * oc4 * C4NUM * sizeof(float16_t)));
   if (tmp_output_block_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_output_block_ failed.";
     return RET_ERROR;
   }
-
   return RET_OK;
 }
 
@@ -142,32 +132,44 @@ int ConvolutionSWFP16CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
+  ConfigInputOutput();
   return ReSize();
 }
 
 int ConvolutionSWFP16CPUKernel::ReSize() {
-  FreeTmpBuffer();
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
 
+  FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
-  auto ret = ConvolutionBaseCPUKernel::Init();
+
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init fail!ret: " << ret;
     return ret;
   }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
-    return RET_ERROR;
-  }
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+
+  /*=============================nhwc4_input_============================*/
+  int ic4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  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);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
     return RET_ERROR;
   }
-  ConfigInputOutput();
+  memset(nhwc4_input_, 0, nhwc4_input_size);
 
   // init sliding window param
   slidingWindow_param_ = new SlidingWindowParam;
@@ -202,6 +204,11 @@ int ConvolutionSWFP16CPUKernel::Run() {
     MS_LOG(ERROR) << "Get Execute tensor failed.";
     return ret;
   }
+  ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
 
   int in_batch = conv_param_->input_batch_;
   int in_h = conv_param_->input_h_;
@@ -212,6 +219,7 @@ int ConvolutionSWFP16CPUKernel::Run() {
   int error_code = LiteBackendParallelLaunch(ConvolutionSWFp16Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv fp16 error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
 
@@ -224,6 +232,7 @@ int ConvolutionSWFP16CPUKernel::Run() {
   }
   ConvolutionBaseFP16CPUKernel::IfCastOutput();
   ConvolutionBaseFP16CPUKernel::FreeTmpBuffer();
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_sw_fp16.h

@@ -28,7 +28,16 @@ class ConvolutionSWFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
                              const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
                              const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~ConvolutionSWFP16CPUKernel() override { FreeTmpBuffer(); }
+  ~ConvolutionSWFP16CPUKernel() override {
+    if (fp16_weight_ != nullptr) {
+      free(fp16_weight_);
+      fp16_weight_ = nullptr;
+    }
+    if (packed_weight_ != nullptr) {
+      free(packed_weight_);
+      packed_weight_ = nullptr;
+    }
+  }
 
   int Init() override;
   int ReSize() override;
@@ -41,16 +50,8 @@ class ConvolutionSWFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (fp16_weight_ != nullptr) {
-      free(fp16_weight_);
-      fp16_weight_ = nullptr;
-    }
-    if (packed_weight_ != nullptr) {
-      free(packed_weight_);
-      packed_weight_ = nullptr;
-    }
     if (tmp_output_block_ != nullptr) {
-      free(tmp_output_block_);
+      ctx_->allocator->Free(tmp_output_block_);
       tmp_output_block_ = nullptr;
     }
     if (slidingWindow_param_ != nullptr) {

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_winograd_fp16.cc

@@ -110,10 +110,15 @@ void WinogradFilterTransformFp16(const float16_t *weight_data, Matrix *trans_wei
 }
 
 int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
-  int output_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  int in_channel = filter_tensor->Channel();
+  int out_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = in_channel;
+  conv_param_->output_channel_ = out_channel;
+
   int oc_block, oc_block_num;
   oc_block = C8NUM;
-  oc_block_num = UP_DIV(output_channel, C8NUM);
+  oc_block_num = UP_DIV(out_channel, C8NUM);
 
   // init weight
   auto ret = MallocFilterMatrix(oc_block, oc_block_num);
@@ -139,7 +144,7 @@ int ConvolutionWinogradFP16CPUKernel::InitWeightBias() {
   auto fp16_bias_data = reinterpret_cast<float16_t *>(bias_data_);
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias = reinterpret_cast<float *>(in_tensors_.at(kBiasIndex)->Data());
-    for (int i = 0; i < output_channel; ++i) {
+    for (int i = 0; i < out_channel; ++i) {
       fp16_bias_data[i] = (float16_t)ori_bias[i];
     }
   } else {
@@ -188,25 +193,14 @@ int ConvolutionWinogradFP16CPUKernel::MallocFilterMatrix(int oc_block, int oc_bl
 
 int ConvolutionWinogradFP16CPUKernel::InitTmpBuffer() {
   int cal_num = 16;
-  int channel_in = conv_param_->input_channel_;
   int channel_out = conv_param_->output_channel_;
   int output_h = conv_param_->output_h_;
   int output_w = conv_param_->output_w_;
-  int ic8 = UP_DIV(channel_in, C8NUM);
   int oc8 = UP_DIV(channel_out, C8NUM);
 
-  /*=============================trans_input_============================*/
-  size_t tile_buffer_size = thread_count_ * cal_num * input_unit_ * input_unit_ * ic8 * C8NUM * sizeof(float16_t);
-  trans_input_ = reinterpret_cast<float16_t *>(malloc(tile_buffer_size));
-  if (trans_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc trans_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(trans_input_, 0, tile_buffer_size);
-
   /*=============================gemm_out_============================*/
   gemm_out_ = reinterpret_cast<float16_t *>(
-    malloc(thread_count_ * cal_num * input_unit_ * input_unit_ * oc8 * C8NUM * sizeof(float16_t)));
+    ctx_->allocator->Malloc(thread_count_ * cal_num * input_unit_ * input_unit_ * oc8 * C8NUM * sizeof(float16_t)));
   if (gemm_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc gemm_out_ failed.";
     return RET_ERROR;
@@ -215,36 +209,26 @@ int ConvolutionWinogradFP16CPUKernel::InitTmpBuffer() {
   /*=============================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<float16_t *>(malloc(conv_param_->output_batch_ * out_w_block * out_h_block *
-                                                       output_unit_ * output_unit_ * oc8 * C8NUM * sizeof(float16_t)));
+  tmp_out_data_ = reinterpret_cast<float16_t *>(
+    ctx_->allocator->Malloc(conv_param_->output_batch_ * out_w_block * out_h_block * output_unit_ * output_unit_ * oc8 *
+                            C8NUM * sizeof(float16_t)));
   if (tmp_out_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_data_ failed.";
     return RET_ERROR;
   }
 
   /*=============================tmp_data_============================*/
-  tmp_data_ =
-    reinterpret_cast<float16_t *>(malloc(thread_count_ * C8NUM * input_unit_ * input_unit_ * sizeof(float16_t)));
+  tmp_data_ = reinterpret_cast<float16_t *>(
+    ctx_->allocator->Malloc(thread_count_ * C8NUM * input_unit_ * input_unit_ * sizeof(float16_t)));
   if (tmp_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_data_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_data_, 0, C8NUM * input_unit_ * input_unit_ * sizeof(float16_t));
 
   tmp_buffer_address_list_[0] = trans_input_;
   tmp_buffer_address_list_[1] = gemm_out_;
   tmp_buffer_address_list_[2] = tmp_out_data_;
   tmp_buffer_address_list_[3] = tmp_data_;
-
-  /*=============================nhwc4_input_============================*/
-  size_t nhwc8_input_size =
-    ic8 * C8NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
-  nhwc4_input_ = malloc(nhwc8_input_size);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc8_input_size);
   return RET_OK;
 }
 
@@ -270,17 +254,37 @@ int ConvolutionWinogradFP16CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  kernel_unit_ = conv_param_->kernel_h_;
+  input_unit_ = output_unit_ + kernel_unit_ - 1;
+  conv_param_->input_unit_ = input_unit_;
+  conv_param_->output_unit_ = output_unit_;
+
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
   return ReSize();
 }
 
 int ConvolutionWinogradFP16CPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
+
   FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
+  if (trans_input_ != nullptr) {
+    free(trans_input_);
+    trans_input_ = nullptr;
+  }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return RET_ERROR;
@@ -290,17 +294,28 @@ int ConvolutionWinogradFP16CPUKernel::ReSize() {
   conv_param_->input_unit_ = input_unit_;
   conv_param_->output_unit_ = output_unit_;
 
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
+  int cal_num = 16;
+  int channel_in = conv_param_->input_channel_;
+  int ic8 = UP_DIV(channel_in, C8NUM);
+  /*=============================nhwc4_input_============================*/
+  size_t nhwc8_input_size =
+    ic8 * C8NUM * conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * sizeof(float16_t);
+  nhwc4_input_ = malloc(nhwc8_input_size);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
     return RET_ERROR;
   }
-  // malloc tmp buffer
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  memset(nhwc4_input_, 0, nhwc8_input_size);
+
+  /*=============================trans_input_============================*/
+  size_t tile_buffer_size = thread_count_ * cal_num * input_unit_ * input_unit_ * ic8 * C8NUM * sizeof(float16_t);
+  trans_input_ = reinterpret_cast<float16_t *>(malloc(tile_buffer_size));
+  if (trans_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc trans_input_ failed.";
     return RET_ERROR;
   }
+  memset(trans_input_, 0, tile_buffer_size);
+
   ret = ConfigInputOutput();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConfigInputOutput failed.";
@@ -339,6 +354,12 @@ int ConvolutionWinogradFP16CPUKernel::Run() {
     return ret;
   }
 
+  ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
+
   int in_batch = conv_param_->input_batch_;
   int in_h = conv_param_->input_h_;
   int in_w = conv_param_->input_w_;
@@ -348,6 +369,7 @@ int ConvolutionWinogradFP16CPUKernel::Run() {
   int error_code = LiteBackendParallelLaunch(ConvolutionWinogradFp16Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv winograd error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
 
@@ -364,6 +386,7 @@ int ConvolutionWinogradFP16CPUKernel::Run() {
   }
   ConvolutionBaseFP16CPUKernel::IfCastOutput();
   ConvolutionBaseFP16CPUKernel::FreeTmpBuffer();
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

mindspore/lite/src/runtime/kernel/arm/fp16/convolution_winograd_fp16.h

@@ -33,7 +33,20 @@ class ConvolutionWinogradFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
                                    const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
                                    const mindspore::lite::PrimitiveC *primitive, int out_unit)
       : ConvolutionBaseFP16CPUKernel(parameter, inputs, outputs, ctx, primitive), output_unit_(out_unit) {}
-  ~ConvolutionWinogradFP16CPUKernel() override { FreeTmpBuffer(); }
+  ~ConvolutionWinogradFP16CPUKernel() override {
+    if (fp16_weight_ != nullptr) {
+      free(fp16_weight_);
+      fp16_weight_ = nullptr;
+    }
+    if (trans_input_ != nullptr) {
+      free(trans_input_);
+      trans_input_ = nullptr;
+    }
+    if (trans_weight_ != nullptr) {
+      delete trans_weight_;
+      trans_weight_ = nullptr;
+    }
+  }
 
   int Init() override;
   int ReSize() override;
@@ -46,30 +59,18 @@ class ConvolutionWinogradFP16CPUKernel : public ConvolutionBaseFP16CPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (fp16_weight_ != nullptr) {
-      free(fp16_weight_);
-      fp16_weight_ = nullptr;
-    }
     if (tmp_data_ != nullptr) {
-      free(tmp_data_);
+      ctx_->allocator->Free(tmp_data_);
       tmp_data_ = nullptr;
     }
-    if (trans_input_ != nullptr) {
-      free(trans_input_);
-      trans_input_ = nullptr;
-    }
     if (gemm_out_ != nullptr) {
-      free(gemm_out_);
+      ctx_->allocator->Free(gemm_out_);
       gemm_out_ = nullptr;
     }
     if (tmp_out_data_ != nullptr) {
-      free(tmp_out_data_);
+      ctx_->allocator->Free(tmp_out_data_);
       tmp_out_data_ = nullptr;
     }
-    if (trans_weight_ != nullptr) {
-      delete trans_weight_;
-      trans_weight_ = nullptr;
-    }
   }
   int kernel_unit_;
   int input_unit_;

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

@@ -35,10 +35,13 @@ using mindspore::schema::PrimitiveType_Conv2D;
 
 namespace mindspore::kernel {
 int ConvolutionCPUKernel::InitWeightBias() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_channel = conv_param_->input_channel_;
-  int out_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  int kernel_h = filter_tensor->Height();
+  int kernel_w = filter_tensor->Width();
+  int in_channel = filter_tensor->Channel();
+  int out_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = in_channel;
+  conv_param_->output_channel_ = out_channel;
   int ic4 = UP_DIV(in_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
   int oc_block, oc_block_num;
@@ -52,7 +55,7 @@ int ConvolutionCPUKernel::InitWeightBias() {
   int pack_weight_size = oc_block_num * oc_block * ic4 * C4NUM * kernel_plane;
 
   // =====================init weight==========================//
-  auto origin_weight = reinterpret_cast<float *>(in_tensors_.at(kWeightIndex)->Data());
+  auto origin_weight = reinterpret_cast<float *>(filter_tensor->Data());
   packed_weight_ = reinterpret_cast<float *>(malloc(pack_weight_size * sizeof(float)));
   if (packed_weight_ == nullptr) {
     MS_LOG(ERROR) << "malloc packed weight failed.";
@@ -67,7 +70,7 @@ int ConvolutionCPUKernel::InitWeightBias() {
     MS_LOG(ERROR) << "malloc bias failed.";
     return RET_ERROR;
   }
-  memset(bias_data_, 0, oc_block_num * oc_block * sizeof(float));
+
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias = reinterpret_cast<float *>(in_tensors_.at(kBiasIndex)->Data());
     memcpy(bias_data_, ori_bias, out_channel * sizeof(float));
@@ -78,39 +81,11 @@ int ConvolutionCPUKernel::InitWeightBias() {
 }
 
 int ConvolutionCPUKernel::InitTmpBuffer() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_batch = conv_param_->input_batch_;
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
   int out_channel = conv_param_->output_channel_;
-  int kernel_plane = kernel_h * kernel_w;
-
-  // malloc packed_inputs
-  int output_count = conv_param_->output_h_ * conv_param_->output_w_;
-  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.";
-    return RET_ERROR;
-  }
-  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);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
+  MS_ASSERT(ctx_->allocator != nullptr);
 
   /*=============================tmp_output_block_============================*/
-  tmp_output_block_ = reinterpret_cast<float *>(malloc(TILE_NUM * out_channel * sizeof(float)));
+  tmp_output_block_ = reinterpret_cast<float *>(ctx_->allocator->Malloc(TILE_NUM * out_channel * sizeof(float)));
   if (tmp_output_block_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp output block failed.";
     return RET_ERROR;
@@ -134,34 +109,59 @@ int ConvolutionCPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
+  ConfigInputOutput();
   return ReSize();
 }
 
 int ConvolutionCPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
+
   FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
-
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  if (packed_input_ != nullptr) {
+    free(packed_input_);
+    packed_input_ = nullptr;
+  }
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return RET_ERROR;
   }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
+
+  /*=============================nhwc4_input_============================*/
+  int ic4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  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);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
     return RET_ERROR;
   }
-  // init tmp input, output
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  memset(nhwc4_input_, 0, nhwc4_input_size);
+
+  /*=============================packed_input============================*/
+  int output_count = conv_param_->output_h_ * conv_param_->output_w_;
+  int output_tile_count = UP_DIV(output_count, TILE_NUM);
+  int unit_size = conv_param_->kernel_h_ * conv_param_->kernel_w_ * ic4 * C4NUM;
+  int packed_input_size = output_tile_count * TILE_NUM * unit_size;
+  packed_input_ = reinterpret_cast<float *>(malloc(conv_param_->input_batch_ * packed_input_size * sizeof(float)));
+  if (packed_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc packed input failed.";
     return RET_ERROR;
   }
-  // config input output
-  ConfigInputOutput();
+  memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size * sizeof(float));
   return RET_OK;
 }
 
@@ -192,19 +192,25 @@ int ConvolutionCPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
     return prepare_ret;
   }
+  // ============Init buffer using memory pool allocator=============//
+  auto ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
+
   auto input_tensor = in_tensors_.at(kInputIndex);
   auto ori_input_data = input_tensor->Data();
-  int in_batch = conv_param_->input_batch_;
-  int in_h = conv_param_->input_h_;
-  int in_w = conv_param_->input_w_;
-  int in_channel = conv_param_->input_channel_;
-  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, in_batch, in_h * in_w, in_channel);
+  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, conv_param_->input_batch_,
+                      conv_param_->input_h_ * conv_param_->input_w_, conv_param_->input_channel_);
 
   int error_code = LiteBackendParallelLaunch(ConvolutionImpl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
+  FreeTmpBuffer();
   return RET_OK;
 }
 

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

@@ -30,7 +30,16 @@ class ConvolutionCPUKernel : public ConvolutionBaseCPUKernel {
                        const std::vector<lite::tensor::Tensor *> &outputs, const lite::Context *ctx,
                        const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~ConvolutionCPUKernel() override { FreeTmpBuffer(); }
+  ~ConvolutionCPUKernel() override {
+    if (packed_weight_ != nullptr) {
+      free(packed_weight_);
+      packed_weight_ = nullptr;
+    }
+    if (packed_input_ != nullptr) {
+      free(packed_input_);
+      packed_input_ = nullptr;
+    }
+  }
 
   int Init() override;
   int ReSize() override;
@@ -42,18 +51,10 @@ class ConvolutionCPUKernel : public ConvolutionBaseCPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (packed_input_ != nullptr) {
-      free(packed_input_);
-      packed_input_ = nullptr;
-    }
     if (tmp_output_block_ != nullptr) {
-      free(tmp_output_block_);
+      ctx_->allocator->Free(tmp_output_block_);
       tmp_output_block_ = nullptr;
     }
-    if (packed_weight_ != nullptr) {
-      free(packed_weight_);
-      packed_weight_ = nullptr;
-    }
   }
   float *packed_input_ = nullptr;
   float *packed_weight_ = nullptr;

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

@@ -49,8 +49,11 @@ void ProcessFilter(float *origin_weight, float *dst_weight, ConvParameter *conv_
 }
 
 int Convolution3x3CPUKernel::InitWeightBias() {
-  auto input_channel = conv_param_->input_channel_;
-  auto output_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
   int iC4 = UP_DIV(input_channel, C4NUM);
   int oC4 = UP_DIV(output_channel, C4NUM);
   int oc_block, oc_block_num;
@@ -91,56 +94,35 @@ int Convolution3x3CPUKernel::InitWeightBias() {
 }
 
 int Convolution3x3CPUKernel::InitTmpBuffer() {
-  int iC4 = UP_DIV(conv_param_->input_channel_, C4NUM);
   int oC4 = UP_DIV(conv_param_->output_channel_, C4NUM);
   const 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) {
-    MS_LOG(ERROR) << "malloc tile buffer failed.";
-    return RET_ERROR;
-  }
-  memset(tile_buffer_, 0, tile_buffer_size);
+  MS_ASSERT(ctx_->allocator != nullptr);
 
   /*=============================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));
+  block_unit_buffer_ = reinterpret_cast<float *>(ctx_->allocator->Malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc block_unit_buffer_ failed.";
     return RET_ERROR;
   }
-  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));
+  tmp_dst_buffer_ = reinterpret_cast<float *>(ctx_->allocator->Malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_dst_buffer_ failed.";
     return RET_ERROR;
   }
-  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);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
-    return RET_ERROR;
-  }
-  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));
+  nc4hw4_out_ = reinterpret_cast<float *>(ctx_->allocator->Malloc(nc4hw4_out_size));
   if (nc4hw4_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc nc4hw4_out_ failed.";
     return RET_ERROR;
   }
-  memset(nc4hw4_out_, 0, nc4hw4_out_size);
+
   tmp_buffer_address_list_[0] = tile_buffer_;
   tmp_buffer_address_list_[1] = block_unit_buffer_;
   tmp_buffer_address_list_[2] = tmp_dst_buffer_;
@@ -162,28 +144,57 @@ int Convolution3x3CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.ret: " << ret;
+    return RET_ERROR;
+  }
+  ConfigInputOutput();
   return ReSize();
 }
 
 int Convolution3x3CPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
+
   FreeTmpBuffer();
+  if (nhwc4_input_ != nullptr) {
+    free(nhwc4_input_);
+    nhwc4_input_ = nullptr;
+  }
+  if (tile_buffer_ != nullptr) {
+    free(tile_buffer_);
+    tile_buffer_ = nullptr;
+  }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.ret: " << ret;
     return RET_ERROR;
   }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.ret: " << ret;
+
+  int iC4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  /*=============================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);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
     return RET_ERROR;
   }
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.ret: " << ret;
+  memset(nhwc4_input_, 0, nhwc4_input_size);
+
+  /*=============================tile_buffer_============================*/
+  size_t tile_buffer_size = thread_count_ * TILE_NUM * C16NUM * iC4 * C4NUM * sizeof(float);
+  tile_buffer_ = reinterpret_cast<float *>(malloc(tile_buffer_size));
+  if (tile_buffer_ == nullptr) {
+    MS_LOG(ERROR) << "malloc tile buffer failed.";
     return RET_ERROR;
   }
-  ConfigInputOutput();
+  memset(tile_buffer_, 0, tile_buffer_size);
   return RET_OK;
 }
 
@@ -214,17 +225,21 @@ int Convolution3x3CPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
     return prepare_ret;
   }
+
+  auto ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.ret: " << ret;
+    return RET_ERROR;
+  }
   auto input_tensor = in_tensors_.at(kInputIndex);
   auto ori_input_data = input_tensor->Data();
-  int in_batch = conv_param_->input_batch_;
-  int in_h = conv_param_->input_h_;
-  int in_w = conv_param_->input_w_;
-  int in_channel = conv_param_->input_channel_;
-  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, in_batch, in_h * in_w, in_channel);
+  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, conv_param_->input_batch_,
+                      conv_param_->input_h_ * conv_param_->input_w_, conv_param_->input_channel_);
 
   int error_code = LiteBackendParallelLaunch(Convolution3x3Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv3x3 error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
 
@@ -241,6 +256,7 @@ int Convolution3x3CPUKernel::Run() {
     PackNC4HW4ToNHWCFp32(nc4hw4_out_, output_addr, conv_param_->output_batch_,
                          conv_param_->output_h_ * conv_param_->output_w_, conv_param_->output_channel_);
   }
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

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

@@ -29,8 +29,15 @@ class Convolution3x3CPUKernel : public ConvolutionBaseCPUKernel {
                           const std::vector<lite::tensor::Tensor *> &outputs, const lite::Context *ctx,
                           const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~Convolution3x3CPUKernel() override { FreeTmpBuffer(); }
-
+  ~Convolution3x3CPUKernel() override {
+    if (transformed_filter_addr_ != nullptr) {
+      free(transformed_filter_addr_);
+    }
+    if (tile_buffer_ != nullptr) {
+      free(tile_buffer_);
+      tile_buffer_ = nullptr;
+    }
+  }
   int Init() override;
   int ReSize() override;
   int Run() override;
@@ -41,24 +48,16 @@ class Convolution3x3CPUKernel : public ConvolutionBaseCPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (tile_buffer_ != nullptr) {
-      free(tile_buffer_);
-      tile_buffer_ = nullptr;
-    }
     if (block_unit_buffer_ != nullptr) {
-      free(block_unit_buffer_);
+      ctx_->allocator->Free(block_unit_buffer_);
       block_unit_buffer_ = nullptr;
     }
     if (tmp_dst_buffer_ != nullptr) {
-      free(tmp_dst_buffer_);
+      ctx_->allocator->Free(tmp_dst_buffer_);
       tmp_dst_buffer_ = nullptr;
     }
-    if (nhwc4_input_ != nullptr) {
-      free(nhwc4_input_);
-      nhwc4_input_ = nullptr;
-    }
     if (nc4hw4_out_ != nullptr) {
-      free(nc4hw4_out_);
+      ctx_->allocator->Free(nc4hw4_out_);
       nc4hw4_out_ = nullptr;
     }
   }

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

@@ -30,14 +30,17 @@ using mindspore::lite::RET_OK;
 using mindspore::schema::PrimitiveType_Conv2D;
 
 int ConvolutionSWCPUKernel::InitWeightBias() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_channel = conv_param_->input_channel_;
-  int out_channel = conv_param_->output_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  int kernel_h = filter_tensor->Height();
+  int kernel_w = filter_tensor->Width();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
+  int ic4 = UP_DIV(input_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
   int oc_block = C4NUM;
-  int oc_block_num = UP_DIV(out_channel, C4NUM);
+  int oc_block_num = UP_DIV(output_channel, C4NUM);
   int pack_weight_size = oc_block_num * oc_block * ic4 * C4NUM * kernel_plane;
 
   // ==================================init weight======================================//
@@ -48,13 +51,13 @@ int ConvolutionSWCPUKernel::InitWeightBias() {
     return RET_ERROR;
   }
   memset(packed_weight_, 0, pack_weight_size * sizeof(float));
-  for (int oc = 0; oc < out_channel; ++oc) {
-    int src_oc_offset = oc * kernel_h * kernel_w * in_channel;
+  for (int oc = 0; oc < output_channel; ++oc) {
+    int src_oc_offset = oc * kernel_h * kernel_w * input_channel;
     int dst_oc_offset = oc * kernel_h * kernel_w * ic4 * C4NUM;
     for (int i = 0; i < kernel_h * kernel_w; ++i) {
-      const float *src = origin_weight + src_oc_offset + i * in_channel;
+      const float *src = origin_weight + src_oc_offset + i * input_channel;
       float *dst = packed_weight_ + dst_oc_offset + i * ic4 * C4NUM;
-      memcpy(dst, src, in_channel * sizeof(float));
+      memcpy(dst, src, input_channel * sizeof(float));
     }
   }
 
@@ -67,7 +70,7 @@ int ConvolutionSWCPUKernel::InitWeightBias() {
   memset(bias_data_, 0, oc_block_num * oc_block * sizeof(float));
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias = reinterpret_cast<float *>(in_tensors_.at(kBiasIndex)->Data());
-    memcpy(bias_data_, ori_bias, out_channel * sizeof(float));
+    memcpy(bias_data_, ori_bias, output_channel * sizeof(float));
   } else {
     MS_ASSERT(in_tensors_.size() == kInputSize1);
   }
@@ -75,24 +78,13 @@ int ConvolutionSWCPUKernel::InitWeightBias() {
 }
 
 int ConvolutionSWCPUKernel::InitTmpBuffer() {
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
   int out_channel = conv_param_->output_channel_;
   int oc4 = UP_DIV(out_channel, C4NUM);
-
-  /*=============================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);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
+  MS_ASSERT(ctx_->allocator != nullptr);
 
   /*=============================tmp_output_block_============================*/
-  tmp_output_block_ = reinterpret_cast<float *>(
-    malloc(conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ * oc4 * C4NUM * sizeof(float)));
+  tmp_output_block_ = reinterpret_cast<float *>(ctx_->allocator->Malloc(
+    conv_param_->output_batch_ * conv_param_->output_h_ * conv_param_->output_w_ * oc4 * C4NUM * sizeof(float)));
   if (tmp_output_block_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp output block failed.";
     return RET_ERROR;
@@ -110,39 +102,49 @@ int ConvolutionSWCPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
+  // config input output
+  ConfigInputOutput();
   return ReSize();
 }
 
 int ConvolutionSWCPUKernel::ReSize() {
-  FreeTmpBuffer();
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
 
+  FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return RET_ERROR;
   }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
-    return RET_ERROR;
-  }
-  // init tmp input, output
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  /*=============================nhwc4_input_============================*/
+  int ic4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  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);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
     return RET_ERROR;
   }
+  memset(nhwc4_input_, 0, nhwc4_input_size);
+
   // init sliding window param
   slidingWindow_param_ = new SlidingWindowParam;
   InitSlidingParamConv(slidingWindow_param_, conv_param_, C4NUM);
 
-  // config input output
-  ConfigInputOutput();
   return RET_OK;
 }
 
@@ -169,20 +171,25 @@ int ConvolutionSWCPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
     return prepare_ret;
   }
+
+  // init tmp input, output
+  auto ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
   auto input_tensor = in_tensors_.at(kInputIndex);
   auto ori_input_data = input_tensor->Data();
-  int in_batch = conv_param_->input_batch_;
-  int in_h = conv_param_->input_h_;
-  int in_w = conv_param_->input_w_;
-  int in_channel = conv_param_->input_channel_;
-  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, in_batch, in_h * in_w, in_channel);
+  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, conv_param_->input_batch_,
+                      conv_param_->input_h_ * conv_param_->input_w_, conv_param_->input_channel_);
 
   int error_code = LiteBackendParallelLaunch(ConvolutionSWImpl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
-  // output nhwc4
+
   auto out_tensor = out_tensors_.front();
   auto out_data = reinterpret_cast<float *>(out_tensor->Data());
   int oc4_res = conv_param_->output_channel_ % C4NUM;
@@ -190,6 +197,7 @@ int ConvolutionSWCPUKernel::Run() {
     PackNHWC4ToNHWCFp32(tmp_output_block_, out_data, conv_param_->output_batch_,
                         conv_param_->output_h_ * conv_param_->output_w_, conv_param_->output_channel_);
   }
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

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

@@ -32,7 +32,12 @@ class ConvolutionSWCPUKernel : public ConvolutionBaseCPUKernel {
                          const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
 
-  ~ConvolutionSWCPUKernel() override { FreeTmpBuffer(); }
+  ~ConvolutionSWCPUKernel() override {
+    if (packed_weight_ != nullptr) {
+      free(packed_weight_);
+      packed_weight_ = nullptr;
+    }
+  }
 
   int Init() override;
   int ReSize() override;
@@ -44,12 +49,8 @@ class ConvolutionSWCPUKernel : public ConvolutionBaseCPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (packed_weight_ != nullptr) {
-      free(packed_weight_);
-      packed_weight_ = nullptr;
-    }
     if (tmp_output_block_ != nullptr) {
-      free(tmp_output_block_);
+      ctx_->allocator->Free(tmp_output_block_);
       tmp_output_block_ = nullptr;
     }
     if (slidingWindow_param_ != nullptr) {

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

@@ -30,12 +30,12 @@ using mindspore::schema::PrimitiveType_Conv2D;
 namespace mindspore::kernel {
 void WinogradFilterTransform(const float *weight_data, Matrix *trans_weight, int kernel_unit, int input_unit,
                              ConvParameter *conv_param, int oc_block) {
-  // original weight format : ohwi
+  // =============original weight format : ohwi===============//
   auto channel_in = conv_param->input_channel_;
   auto channel_out = conv_param->output_channel_;
   int input_unit_square = input_unit * input_unit;
 
-  // generate matrix_G && matrix_GT
+  // =============generate matrix_G && matrix_GT===============//
   auto matrix_g = TransformMatrixGenerator(input_unit, kernel_unit);
   auto matrix_gt = TransformMatrixGenerator(kernel_unit, input_unit);
   ChooseMatrixG(matrix_g, matrix_gt);
@@ -95,15 +95,20 @@ void WinogradFilterTransform(const float *weight_data, Matrix *trans_weight, int
 }
 
 int ConvolutionWinogradCPUKernel::InitWeightBias() {
-  int output_channel = conv_param_->output_channel_;
-  int oc4 = UP_DIV(output_channel, C4NUM);
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  int in_channel = filter_tensor->Channel();
+  int out_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = in_channel;
+  conv_param_->output_channel_ = out_channel;
+
+  int oc4 = UP_DIV(out_channel, C4NUM);
   int oc_block, oc_block_num;
   // #ifdef ENABLE_ARM32
   //   oc_block = C4NUM;
   //   oc_block_num = UP_DIV(output_channel, C4NUM);
   // #else
   oc_block = C8NUM;
-  oc_block_num = UP_DIV(output_channel, C8NUM);
+  oc_block_num = UP_DIV(out_channel, C8NUM);
   // #endif
 
   // init weight
@@ -112,8 +117,7 @@ int ConvolutionWinogradCPUKernel::InitWeightBias() {
     MS_LOG(ERROR) << "Malloc filter matrix failed.";
     return RET_ERROR;
   }
-  auto weight_tensor = in_tensors_.at(kWeightIndex);
-  auto weight_data = reinterpret_cast<float *>(weight_tensor->Data());
+  auto weight_data = reinterpret_cast<float *>(filter_tensor->Data());
   WinogradFilterTransform(weight_data, trans_weight_, kernel_unit_, input_unit_, conv_param_, oc_block);
 
   // init bias
@@ -122,7 +126,7 @@ int ConvolutionWinogradCPUKernel::InitWeightBias() {
   memset(bias_data_, 0, new_bias_size);
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias_addr = reinterpret_cast<float *>(in_tensors_.at(kBiasIndex)->Data());
-    memcpy(bias_data_, ori_bias_addr, output_channel * sizeof(float));
+    memcpy(bias_data_, ori_bias_addr, out_channel * sizeof(float));
   } else {
     MS_ASSERT(in_tensors_.size() == kInputSize1);
   }
@@ -167,25 +171,15 @@ int ConvolutionWinogradCPUKernel::MallocFilterMatrix(int oc_block, int oc_block_
 }
 
 int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
-  int channel_in = conv_param_->input_channel_;
   int channel_out = conv_param_->output_channel_;
   int output_h = conv_param_->output_h_;
   int output_w = conv_param_->output_w_;
-  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) {
-    MS_LOG(ERROR) << "malloc trans_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(trans_input_, 0, tile_buffer_size);
+  MS_ASSERT(ctx_->allocator != nullptr);
 
   /*=============================gemm_out_============================*/
   gemm_out_ = reinterpret_cast<float *>(
-    malloc(thread_count_ * TILE_NUM * input_unit_ * input_unit_ * oc4 * C4NUM * sizeof(float)));
+    ctx_->allocator->Malloc(thread_count_ * TILE_NUM * input_unit_ * input_unit_ * oc4 * C4NUM * sizeof(float)));
   if (gemm_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc gemm_out_ failed.";
     return RET_ERROR;
@@ -194,35 +188,26 @@ int ConvolutionWinogradCPUKernel::InitTmpBuffer() {
   /*=============================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 *>(malloc(conv_param_->output_batch_ * out_w_block * out_h_block *
-                                                   output_unit_ * output_unit_ * oc4 * C4NUM * sizeof(float)));
+  tmp_out_data_ =
+    reinterpret_cast<float *>(ctx_->allocator->Malloc(conv_param_->output_batch_ * out_w_block * out_h_block *
+                                                      output_unit_ * output_unit_ * oc4 * C4NUM * sizeof(float)));
   if (tmp_out_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_data_ failed.";
     return RET_ERROR;
   }
 
   /*=============================tmp_data_============================*/
-  tmp_data_ = reinterpret_cast<float *>(malloc(thread_count_ * C4NUM * input_unit_ * input_unit_ * sizeof(float)));
+  tmp_data_ = reinterpret_cast<float *>(
+    ctx_->allocator->Malloc(thread_count_ * C4NUM * input_unit_ * input_unit_ * sizeof(float)));
   if (tmp_data_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_data_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_data_, 0, C4NUM * input_unit_ * input_unit_ * sizeof(float));
 
   tmp_buffer_address_list_[0] = trans_input_;
   tmp_buffer_address_list_[1] = gemm_out_;
   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);
-  if (nhwc4_input_ == nullptr) {
-    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
   return RET_OK;
 }
 
@@ -253,37 +238,67 @@ int ConvolutionWinogradCPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  kernel_unit_ = conv_param_->kernel_h_;
+  input_unit_ = output_unit_ + kernel_unit_ - 1;
+  conv_param_->input_unit_ = input_unit_;
+  conv_param_->output_unit_ = output_unit_;
+
+  auto ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
   return ReSize();
 }
 
 int ConvolutionWinogradCPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
+
   FreeTmpBuffer();
   if (nhwc4_input_ != nullptr) {
     free(nhwc4_input_);
     nhwc4_input_ = nullptr;
   }
+  if (trans_input_ != nullptr) {
+    free(trans_input_);
+    trans_input_ = nullptr;
+  }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return RET_ERROR;
   }
+
   kernel_unit_ = conv_param_->kernel_h_;
   input_unit_ = output_unit_ + kernel_unit_ - 1;
   conv_param_->input_unit_ = input_unit_;
   conv_param_->output_unit_ = output_unit_;
 
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
+  /*=============================nhwc4_input_============================*/
+  int ic4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  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);
+  if (nhwc4_input_ == nullptr) {
+    MS_LOG(ERROR) << "malloc nhwc4_input_ failed.";
     return RET_ERROR;
   }
-  // malloc tmp buffer
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  memset(nhwc4_input_, 0, nhwc4_input_size);
+
+  /*=============================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) {
+    MS_LOG(ERROR) << "malloc trans_input_ failed.";
     return RET_ERROR;
   }
+  memset(trans_input_, 0, tile_buffer_size);
+
   ret = ConfigInputOutput();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConfigInputOutput failed.";
@@ -319,17 +334,21 @@ int ConvolutionWinogradCPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare fail!ret: " << prepare_ret;
     return prepare_ret;
   }
+  // malloc tmp buffer
+  auto ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
   auto input_tensor = in_tensors_.at(kInputIndex);
   auto ori_input_data = input_tensor->Data();
-  int in_batch = conv_param_->input_batch_;
-  int in_h = conv_param_->input_h_;
-  int in_w = conv_param_->input_w_;
-  int in_channel = conv_param_->input_channel_;
-  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, in_batch, in_h * in_w, in_channel);
+  PackNHWCToNHWC4Fp32(ori_input_data, nhwc4_input_, conv_param_->input_batch_,
+                      conv_param_->input_h_ * conv_param_->input_w_, conv_param_->input_channel_);
 
   int error_code = LiteBackendParallelLaunch(ConvolutionWinogradImpl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv winograd error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
 
@@ -346,6 +365,7 @@ int ConvolutionWinogradCPUKernel::Run() {
     UnPackWinogradOutput(tmp_out_data_, out_data, conv_param_->output_batch_, conv_param_->output_h_,
                          conv_param_->output_w_, conv_param_->output_channel_, output_unit_);
   }
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

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

@@ -30,10 +30,18 @@ class ConvolutionWinogradCPUKernel : public ConvolutionBaseCPUKernel {
   ConvolutionWinogradCPUKernel(OpParameter *parameter, const std::vector<lite::tensor::Tensor *> &inputs,
                                const std::vector<lite::tensor::Tensor *> &outputs, const lite::Context *ctx,
                                const mindspore::lite::PrimitiveC *primitive, int output_unit)
-      : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive), output_unit_(output_unit),
+      : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive),
+        output_unit_(output_unit),
         trans_weight_(nullptr) {}
   ~ConvolutionWinogradCPUKernel() override {
-    FreeTmpBuffer();
+    if (trans_weight_ != nullptr) {
+      delete trans_weight_;
+      trans_weight_ = nullptr;
+    }
+    if (trans_input_ != nullptr) {
+      free(trans_input_);
+      trans_input_ = nullptr;
+    }
   };
   int Init() override;
   int ReSize() override;
@@ -47,25 +55,17 @@ class ConvolutionWinogradCPUKernel : public ConvolutionBaseCPUKernel {
  private:
   void FreeTmpBuffer() {
     if (tmp_data_ != nullptr) {
-      free(tmp_data_);
+      ctx_->allocator->Free(tmp_data_);
       tmp_data_ = nullptr;
     }
-    if (trans_input_ != nullptr) {
-      free(trans_input_);
-      trans_input_ = nullptr;
-    }
     if (gemm_out_ != nullptr) {
-      free(gemm_out_);
+      ctx_->allocator->Free(gemm_out_);
       gemm_out_ = nullptr;
     }
     if (tmp_out_data_ != nullptr) {
-      free(tmp_out_data_);
+      ctx_->allocator->Free(tmp_out_data_);
       tmp_out_data_ = nullptr;
     }
-    if (trans_weight_ != nullptr) {
-      delete trans_weight_;
-      trans_weight_ = nullptr;
-    }
   }
   int kernel_unit_;
   int input_unit_;

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

@@ -44,6 +44,21 @@ void ProcessFilterUint8(int8_t *origin_weight, int16_t *dst_weight, ConvParamete
 }
 
 void Convolution3x3Int8CPUKernel::FreeTmpBuffer() {
+  if (block_unit_buffer_ != nullptr) {
+    ctx_->allocator->Free(block_unit_buffer_);
+    block_unit_buffer_ = nullptr;
+  }
+  if (tmp_dst_buffer_ != nullptr) {
+    ctx_->allocator->Free(tmp_dst_buffer_);
+    tmp_dst_buffer_ = nullptr;
+  }
+  if (tmp_out_ != nullptr) {
+    ctx_->allocator->Free(tmp_out_);
+    tmp_out_ = nullptr;
+  }
+}
+
+Convolution3x3Int8CPUKernel::~Convolution3x3Int8CPUKernel() {
   if (transformed_filter_addr_ != nullptr) {
     free(transformed_filter_addr_);
     transformed_filter_addr_ = nullptr;
@@ -56,26 +71,15 @@ void Convolution3x3Int8CPUKernel::FreeTmpBuffer() {
     free(tile_buffer_);
     tile_buffer_ = nullptr;
   }
-  if (block_unit_buffer_ != nullptr) {
-    free(block_unit_buffer_);
-    block_unit_buffer_ = nullptr;
-  }
-  if (tmp_dst_buffer_ != nullptr) {
-    free(tmp_dst_buffer_);
-    tmp_dst_buffer_ = nullptr;
-  }
-  if (tmp_out_ != nullptr) {
-    free(tmp_out_);
-    tmp_out_ = nullptr;
-  }
   FreeQuantParam();
 }
 
-Convolution3x3Int8CPUKernel::~Convolution3x3Int8CPUKernel() { FreeTmpBuffer(); }
-
 int Convolution3x3Int8CPUKernel::InitWeightBias() {
-  auto input_channel = conv_param_->input_channel_;
-  auto output_channel = conv_param_->output_channel_;
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
   int iC8 = UP_DIV(input_channel, C8NUM);
   int oC4 = UP_DIV(output_channel, C4NUM);
   // init weight
@@ -107,59 +111,35 @@ int Convolution3x3Int8CPUKernel::InitWeightBias() {
 }
 
 int Convolution3x3Int8CPUKernel::InitTmpBuffer() {
-  int ic8 = UP_DIV(conv_param_->input_channel_, C8NUM);
   int oc4 = UP_DIV(conv_param_->output_channel_, C4NUM);
-  int in_batch = conv_param_->input_batch_;
-  int input_w = conv_param_->input_w_;
-  int input_h = conv_param_->input_h_;
   int output_batch = conv_param_->output_batch_;
   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) {
-    MS_LOG(ERROR) << "malloc tile_buffer_ failed.";
-    return RET_ERROR;
-  }
-  memset(tile_buffer_, 0, tile_buffer_size);
+  MS_ASSERT(ctx_->allocator != nullptr);
 
   /*=============================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));
+  block_unit_buffer_ = reinterpret_cast<int16_t *>(ctx_->allocator->Malloc(block_unit_buffer_size));
   if (block_unit_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc block_unit_buffer_ failed.";
     return RET_ERROR;
   }
-  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));
+  tmp_dst_buffer_ = reinterpret_cast<int32_t *>(ctx_->allocator->Malloc(tmp_dst_buffer_size));
   if (tmp_dst_buffer_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_dst_buffer_ failed.";
     return RET_ERROR;
   }
-  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));
+  tmp_out_ = reinterpret_cast<int8_t *>(ctx_->allocator->Malloc(tmp_out_size));
   if (tmp_out_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_out_ failed.";
     return RET_ERROR;
   }
-  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) {
-    MS_LOG(ERROR) << "malloc input_data_ failed.";
-    return RET_ERROR;
-  }
-  memset(input_data_, 0, c8_input_size);
   return RET_OK;
 }
 
@@ -172,35 +152,63 @@ int Convolution3x3Int8CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
+  auto ret = SetQuantParam();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Set quant param failed.";
+    return ret;
+  }
+  ret = InitWeightBias();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init weight bias failed.";
+    return RET_ERROR;
+  }
+  // config input output
+  ConfigInputOutput();
   return ReSize();
 }
 
 int Convolution3x3Int8CPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
+  }
+
   FreeTmpBuffer();
+  if (input_data_ != nullptr) {
+    free(input_data_);
+    input_data_ = nullptr;
+  }
+  if (tile_buffer_ != nullptr) {
+    free(tile_buffer_);
+    tile_buffer_ = nullptr;
+  }
 
-  auto ret = ConvolutionBaseCPUKernel::Init();
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "ConvolutionBase init failed.";
     return RET_ERROR;
   }
-  ret = SetQuantParam();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Set quant param failed.";
-    return ret;
-  }
-  ret = InitWeightBias();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
+
+  /*=============================input_data_============================*/
+  int ic8 = UP_DIV(conv_param_->input_channel_, C8NUM);
+  size_t c8_input_size =
+    conv_param_->input_batch_ * conv_param_->input_h_ * conv_param_->input_w_ * ic8 * C8NUM * sizeof(int16_t);
+  input_data_ = reinterpret_cast<int16_t *>(malloc(c8_input_size));
+  if (input_data_ == nullptr) {
+    MS_LOG(ERROR) << "malloc input_data_ failed.";
     return RET_ERROR;
   }
-  // init tmp input, output
-  ret = InitTmpBuffer();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+  memset(input_data_, 0, c8_input_size);
+
+  /*=============================tile_buffer_============================*/
+  size_t tile_buffer_size = thread_count_ * TILE_NUM * C16NUM * ic8 * C8NUM * sizeof(int16_t);
+  tile_buffer_ = reinterpret_cast<int16_t *>(malloc(tile_buffer_size));
+  if (tile_buffer_ == nullptr) {
+    MS_LOG(ERROR) << "malloc tile_buffer_ failed.";
     return RET_ERROR;
   }
-  // config input output
-  ConfigInputOutput();
+  memset(tile_buffer_, 0, tile_buffer_size);
   return RET_OK;
 }
 
@@ -227,12 +235,19 @@ int Convolution3x3Int8CPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare failed.";
     return RET_ERROR;
   }
+  // malloc tmp buffer
+  ret = InitTmpBuffer();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    return RET_ERROR;
+  }
   auto input_addr = reinterpret_cast<int8_t *>(in_tensors_.at(kInputIndex)->Data());
   PackInputToC8Int8(input_addr, input_data_, conv_param_);
 
   int error_code = LiteBackendParallelLaunch(Convolution3x3Int8Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv3x3 int8 error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
   // get real output
@@ -240,6 +255,7 @@ int Convolution3x3Int8CPUKernel::Run() {
   auto out_data = reinterpret_cast<int8_t *>(out_tensor->Data());
   PackNC4HW4ToNHWCInt8(tmp_out_, out_data, conv_param_->output_batch_, conv_param_->output_h_ * conv_param_->output_w_,
                        conv_param_->output_channel_);
+  FreeTmpBuffer();
   return RET_OK;
 }
 }  // namespace mindspore::kernel

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

@@ -60,12 +60,15 @@ void ConvolutionInt8CPUKernel::CheckSupportOptimize() {
 }
 
 int ConvolutionInt8CPUKernel::InitWeightBias() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
-  int out_channel = conv_param_->output_channel_;
-  int oc4 = UP_DIV(out_channel, C4NUM);
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  int kernel_h = filter_tensor->Height();
+  int kernel_w = filter_tensor->Width();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
+  int ic4 = UP_DIV(input_channel, C4NUM);
+  int oc4 = UP_DIV(output_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
   int plane_c4 = UP_DIV(kernel_plane, C4NUM);
   int pack_weight_size = oc4 * ic4 * C4NUM * C4NUM * plane_c4 * C4NUM;
@@ -80,8 +83,8 @@ int ConvolutionInt8CPUKernel::InitWeightBias() {
     return RET_ERROR;
   }
   memset(packed_weight_, 0, pack_weight_size);
-  auto *weight_sum = reinterpret_cast<int32_t *>(malloc(sizeof(int32_t) * out_channel));
-  for (int i = 0; i < out_channel; i++) weight_sum[i] = 0;
+  auto *weight_sum = reinterpret_cast<int32_t *>(malloc(sizeof(int32_t) * output_channel));
+  for (int i = 0; i < output_channel; i++) weight_sum[i] = 0;
   PackWeightInt8(origin_weight, conv_param_, packed_weight_, weight_sum);
 
   // init bias
@@ -93,42 +96,22 @@ int ConvolutionInt8CPUKernel::InitWeightBias() {
   memset(bias_data_, 0, oc4 * C4NUM * sizeof(int32_t));
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias = reinterpret_cast<int32_t *>(in_tensors_.at(kBiasIndex)->Data());
-    memcpy(bias_data_, ori_bias, out_channel * sizeof(int32_t));
+    memcpy(bias_data_, ori_bias, output_channel * sizeof(int32_t));
   } else {
     MS_ASSERT(in_tensors_.size() == kInputSize1);
   }
   auto *bias_data = reinterpret_cast<int32_t *>(bias_data_);
   int c4_kernel_plane_size = kernel_plane * ic4 * C4NUM;
   if (conv_quant_arg_->per_channel_ & FILTER_PER_CHANNEL) {
-    for (int i = 0; i < out_channel; i++) {
+    for (int i = 0; i < output_channel; i++) {
       bias_data[i] += filter_arg[i].zp_ * input_zp * c4_kernel_plane_size - weight_sum[i] * input_zp;
     }
   } else {
-    for (int i = 0; i < out_channel; i++) {
+    for (int i = 0; i < output_channel; i++) {
       bias_data[i] += filter_arg[0].zp_ * input_zp * c4_kernel_plane_size - weight_sum[i] * input_zp;
     }
   }
   free(weight_sum);
-  return RET_OK;
-}
-
-int ConvolutionInt8CPUKernel::InitTmpBuffer() {
-  int output_count = conv_param_->output_h_ * conv_param_->output_w_;
-  int output_tile_count = UP_DIV(output_count, tile_num_);
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
-  int kernel_plane = conv_param_->kernel_h_ * conv_param_->kernel_w_;
-  int plane_c4 = UP_DIV(kernel_plane, C4NUM);
-  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.";
-    return RET_ERROR;
-  }
-  memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size);
 
   /*=============================input_sum_============================*/
   size_t input_sum_size;
@@ -137,47 +120,45 @@ int ConvolutionInt8CPUKernel::InitTmpBuffer() {
   } else {
     input_sum_size = tile_num_ * thread_count_ * sizeof(int32_t);
   }
-  input_sum_ = reinterpret_cast<int32_t *>(malloc(input_sum_size));
+  input_sum_ = reinterpret_cast<int32_t *>(ctx_->allocator->Malloc(input_sum_size));
   if (input_sum_ == nullptr) {
     MS_LOG(ERROR) << "malloc input_sum_ failed.";
     return RET_ERROR;
   }
   memset(input_sum_, 0, tile_num_ * thread_count_ * sizeof(int32_t));
+  return RET_OK;
+}
 
+int ConvolutionInt8CPUKernel::InitTmpBuffer() {
+  MS_ASSERT(ctx_->allocator != nullptr);
   /*=============================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));
+  tmp_dst_ = reinterpret_cast<int32_t *>(ctx_->allocator->Malloc(tmp_dst_size));
   if (tmp_dst_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_dst_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_dst_, 0, tmp_dst_size);
 
   /*=============================tmp_out_============================*/
-  tmp_out_ = reinterpret_cast<int8_t *>(malloc(thread_count_ * tile_num_ * conv_param_->output_channel_));
+  tmp_out_ =
+    reinterpret_cast<int8_t *>(ctx_->allocator->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) {
-    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
   return RET_OK;
 }
 
 int ConvolutionInt8CPUKernel::InitWeightBiasOpt() {
-  int kernel_h = conv_param_->kernel_h_;
-  int kernel_w = conv_param_->kernel_w_;
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
-  int out_channel = conv_param_->output_channel_;
-  int oc4 = UP_DIV(out_channel, C4NUM);
+  auto filter_tensor = in_tensors_.at(kWeightIndex);
+  auto input_channel = filter_tensor->Channel();
+  auto output_channel = filter_tensor->Batch();
+  int kernel_h = filter_tensor->Height();
+  int kernel_w = filter_tensor->Width();
+  conv_param_->input_channel_ = input_channel;
+  conv_param_->output_channel_ = output_channel;
+  int ic4 = UP_DIV(input_channel, C4NUM);
+  int oc4 = UP_DIV(output_channel, C4NUM);
   int kernel_plane = kernel_h * kernel_w;
   int pack_weight_size = oc4 * ic4 * C4NUM * C4NUM * kernel_plane;
   auto filter_arg = conv_param_->conv_quant_arg_.filter_quant_args_;
@@ -191,8 +172,8 @@ int ConvolutionInt8CPUKernel::InitWeightBiasOpt() {
     return RET_ERROR;
   }
   memset(packed_weight_, 0, pack_weight_size);
-  auto *weight_sum = reinterpret_cast<int32_t *>(malloc(sizeof(int32_t) * out_channel));
-  for (int i = 0; i < out_channel; i++) weight_sum[i] = 0;
+  auto *weight_sum = reinterpret_cast<int32_t *>(malloc(sizeof(int32_t) * output_channel));
+  for (int i = 0; i < output_channel; i++) weight_sum[i] = 0;
   PackWeightInt8Opt(origin_weight, conv_param_, packed_weight_, weight_sum);
 
   // init bias
@@ -204,41 +185,22 @@ int ConvolutionInt8CPUKernel::InitWeightBiasOpt() {
   memset(bias_data_, 0, oc4 * C4NUM * sizeof(int32_t));
   if (in_tensors_.size() == kInputSize2) {
     auto ori_bias = reinterpret_cast<int32_t *>(in_tensors_.at(kBiasIndex)->Data());
-    memcpy(bias_data_, ori_bias, out_channel * sizeof(int32_t));
+    memcpy(bias_data_, ori_bias, output_channel * sizeof(int32_t));
   } else {
     MS_ASSERT(in_tensors_.size() == kInputSize1);
   }
   auto *bias_data = reinterpret_cast<int32_t *>(bias_data_);
   int c4_kernel_plane_size = kernel_plane * ic4 * C4NUM;
   if (conv_quant_arg_->per_channel_ & FILTER_PER_CHANNEL) {
-    for (int i = 0; i < out_channel; i++) {
+    for (int i = 0; i < output_channel; i++) {
       bias_data[i] += filter_arg[i].zp_ * input_zp * c4_kernel_plane_size - weight_sum[i] * input_zp;
     }
   } else {
-    for (int i = 0; i < out_channel; i++) {
+    for (int i = 0; i < output_channel; i++) {
       bias_data[i] += filter_arg[0].zp_ * input_zp * c4_kernel_plane_size - weight_sum[i] * input_zp;
     }
   }
   free(weight_sum);
-  return RET_OK;
-}
-
-int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
-  int output_count = conv_param_->output_h_ * conv_param_->output_w_;
-  int output_tile_count = UP_DIV(output_count, tile_num_);
-  int in_channel = conv_param_->input_channel_;
-  int ic4 = UP_DIV(in_channel, C4NUM);
-  int kernel_plane = conv_param_->kernel_h_ * conv_param_->kernel_w_;
-  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.";
-    return RET_ERROR;
-  }
-  memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size);
 
   /*=============================input_sum_============================*/
   size_t input_sum_size;
@@ -253,31 +215,26 @@ int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
     return RET_ERROR;
   }
   memset(input_sum_, 0, tile_num_ * thread_count_ * sizeof(int32_t));
+  return RET_OK;
+}
 
+int ConvolutionInt8CPUKernel::InitTmpBufferOpt() {
+  MS_ASSERT(ctx_->allocator != nullptr);
   /*=============================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));
+  tmp_dst_ = reinterpret_cast<int32_t *>(ctx_->allocator->Malloc(tmp_dst_size));
   if (tmp_dst_ == nullptr) {
     MS_LOG(ERROR) << "malloc tmp_dst_ failed.";
     return RET_ERROR;
   }
-  memset(tmp_dst_, 0, tmp_dst_size);
 
   /*=============================tmp_out_============================*/
-  tmp_out_ = reinterpret_cast<int8_t *>(malloc(thread_count_ * tile_num_ * conv_param_->output_channel_));
+  tmp_out_ =
+    reinterpret_cast<int8_t *>(ctx_->allocator->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) {
-    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
-    return RET_ERROR;
-  }
-  memset(nhwc4_input_, 0, nhwc4_input_size);
   return RET_OK;
 }
 
@@ -296,62 +253,79 @@ int ConvolutionInt8CPUKernel::Init() {
   if (!InferShapeDone()) {
     return RET_OK;
   }
-  return ReSize();
-}
-
-int ConvolutionInt8CPUKernel::InitOpt() {
-  auto ret = InitWeightBiasOpt();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
-    return RET_ERROR;
-  }
-  // init tmp input, output
-  ret = InitTmpBufferOpt();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
-    return RET_ERROR;
-  }
-  return RET_OK;
-}
-
-int ConvolutionInt8CPUKernel::ReSize() {
-  FreeTmpBuffer();
-
-  auto ret = ConvolutionBaseCPUKernel::Init();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "ConvolutionBase init failed.";
-    return RET_ERROR;
-  }
   // config input output
   ConfigInputOutput();
   CheckSupportOptimize();
-  ret = SetQuantParam();
+  auto ret = SetQuantParam();
   if (ret != RET_OK) {
     MS_LOG(ERROR) << "Set quant param failed.";
     return ret;
   }
   // init for opt
   if (support_optimize_) {
-    ret = InitOpt();
+    ret = InitWeightBiasOpt();
     if (ret != RET_OK) {
       MS_LOG(ERROR) << "Initialization for optimized int8 conv failed.";
       return RET_ERROR;
     }
-    return RET_OK;
+  } else {
+    // init for situation that not support sdot
+    ret = InitWeightBias();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "Init weight bias failed.";
+      return RET_ERROR;
+    }
   }
 
-  // init for situation that not support sdot
-  ret = InitWeightBias();
+  return ReSize();
+}
+
+int ConvolutionInt8CPUKernel::ReSize() {
+  auto ret = ConvolutionBaseCPUKernel::CheckResizeValid();
   if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init weight bias failed.";
-    return RET_ERROR;
+    MS_LOG(ERROR) << "Resize is invalid.";
+    return ret;
   }
-  // init tmp input, output
-  ret = InitTmpBuffer();
+
+  FreeTmpBuffer();
+  if (nhwc4_input_ != nullptr) {
+    free(nhwc4_input_);
+    nhwc4_input_ = nullptr;
+  }
+  if (packed_input_ != nullptr) {
+    free(packed_input_);
+    packed_input_ = nullptr;
+  }
+
+  ret = ConvolutionBaseCPUKernel::Init();
   if (ret != RET_OK) {
-    MS_LOG(ERROR) << "Init tmp buffer failed.";
+    MS_LOG(ERROR) << "ConvolutionBase init failed.";
+    return RET_ERROR;
+  }
+  /*=============================nhwc4_input_============================*/
+  int ic4 = UP_DIV(conv_param_->input_channel_, C4NUM);
+  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) {
+    MS_LOG(ERROR) << "malloc nhwc4 input failed.";
+    return RET_ERROR;
+  }
+  memset(nhwc4_input_, 0, nhwc4_input_size);
+
+  /*=============================packed_input_============================*/
+  int output_count = conv_param_->output_h_ * conv_param_->output_w_;
+  int output_tile_count = UP_DIV(output_count, tile_num_);
+  int kernel_plane = conv_param_->kernel_h_ * conv_param_->kernel_w_;
+  int plane_c4 = UP_DIV(kernel_plane, C4NUM);
+  int unit_size = plane_c4 * C4NUM * ic4 * C4NUM;
+  int packed_input_size = output_tile_count * tile_num_ * unit_size;
+  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.";
     return RET_ERROR;
   }
+  memset(packed_input_, 0, conv_param_->input_batch_ * packed_input_size);
+
   return RET_OK;
 }
 
@@ -369,7 +343,7 @@ int ConvolutionInt8CPUKernel::RunImpl(int task_id) {
   return RET_OK;
 }
 
-int ConvolutionInt8Impl(int task_id, LiteParallelGroupEnv *penv, void *cdata) {
+int ConvolutionInt8Impl(int task_id, LiteParallelGroupEnv *mpenv, void *cdata) {
   auto conv = reinterpret_cast<ConvolutionInt8CPUKernel *>(cdata);
   auto error_code = conv->RunImpl(task_id);
   if (error_code != RET_OK) {
@@ -385,19 +359,33 @@ int ConvolutionInt8CPUKernel::Run() {
     MS_LOG(ERROR) << "Prepare failed.";
     return RET_ERROR;
   }
+  if (support_optimize_) {
+    ret = InitTmpBufferOpt();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "Init tmp buffer failed.";
+      return RET_ERROR;
+    }
+  } else {
+    // init tmp input, output
+    ret = InitTmpBuffer();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "Init tmp buffer failed.";
+      return RET_ERROR;
+    }
+  }
+
   auto input_tensor = in_tensors_.at(kInputIndex);
   auto ori_input_data = input_tensor->Data();
-  int in_batch = conv_param_->input_batch_;
-  int in_h = conv_param_->input_h_;
-  int in_w = conv_param_->input_w_;
-  int in_channel = conv_param_->input_channel_;
-  convert_func_(ori_input_data, nhwc4_input_, in_batch, in_h * in_w, in_channel);
+  convert_func_(ori_input_data, nhwc4_input_, conv_param_->input_batch_, conv_param_->input_h_ * conv_param_->input_w_,
+                conv_param_->input_channel_);
 
   int error_code = LiteBackendParallelLaunch(ConvolutionInt8Impl, this, thread_count_);
   if (error_code != RET_OK) {
     MS_LOG(ERROR) << "conv int8 error error_code[" << error_code << "]";
+    FreeTmpBuffer();
     return RET_ERROR;
   }
+  FreeTmpBuffer();
   return RET_OK;
 }
 

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

@@ -30,14 +30,27 @@ class ConvolutionInt8CPUKernel : public ConvolutionBaseCPUKernel {
                            const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
                            const mindspore::lite::PrimitiveC *primitive)
       : ConvolutionBaseCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~ConvolutionInt8CPUKernel() override { FreeTmpBuffer(); }
+  ~ConvolutionInt8CPUKernel() override {
+    FreeQuantParam();
+    if (packed_weight_ != nullptr) {
+      free(packed_weight_);
+      packed_weight_ = nullptr;
+    }
+    if (packed_input_ != nullptr) {
+      free(packed_input_);
+      packed_input_ = nullptr;
+    }
+    if (input_sum_ != nullptr) {
+      free(input_sum_);
+      input_sum_ = nullptr;
+    }
+  }
 
   int Init() override;
   int ReSize() override;
   int Run() override;
   int RunImpl(int task_id);
   void CheckSupportOptimize();
-  int InitOpt();
   int InitWeightBiasOpt();
   int InitTmpBufferOpt();
   int InitWeightBias();
@@ -46,27 +59,14 @@ class ConvolutionInt8CPUKernel : public ConvolutionBaseCPUKernel {
 
  private:
   void FreeTmpBuffer() {
-    if (packed_weight_ != nullptr) {
-      free(packed_weight_);
-      packed_weight_ = nullptr;
-    }
-    if (packed_input_ != nullptr) {
-      free(packed_input_);
-      packed_input_ = nullptr;
-    }
-    if (input_sum_ != nullptr) {
-      free(input_sum_);
-      input_sum_ = nullptr;
-    }
     if (tmp_dst_ != nullptr) {
-      free(tmp_dst_);
+      ctx_->allocator->Free(tmp_dst_);
       tmp_dst_ = nullptr;
     }
     if (tmp_out_ != nullptr) {
-      free(tmp_out_);
+      ctx_->allocator->Free(tmp_out_);
       tmp_out_ = nullptr;
     }
-    FreeQuantParam();
   }
   bool support_optimize_ = true;
   int8_t *packed_weight_ = nullptr;

mindspore/lite/src/runtime/kernel/arm/nnacl/pack.c

@@ -228,10 +228,9 @@ void Im2ColPackUnitFp32(const float *input_data, ConvParameter *conv_param, floa
 #ifdef ENABLE_NEON
           vst1q_f32(packed_input + channel_block_offset, vld1q_f32(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];
+          for (int k = 0; k < C4NUM; ++k) {
+            (packed_input + channel_block_offset)[k] = (input_data + channel_block_stride)[k];
+          }
 #endif
         }  // channel_block loop
       }    // kernel_w loop
@@ -349,10 +348,9 @@ void Im2ColPackUnitInt8Opt(const int8_t *input_data, int8_t *packed_input, int r
         for (int m = 0; m < ic4; m++) {
           int channel_block_stride = input_x_stride + m * C4NUM;
           int channel_block_offset = input_plane_offset + m * tile_num * C4NUM;
-          (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];
+          for (int k = 0; k < C4NUM; k++) {
+            (packed_input + channel_block_offset)[k] = (input_data + channel_block_stride)[k];
+          }
         }  // channel_block loop
       }    // kernel_w loop
     }      // kernel_h loop