!4608 fix concat int8 memory leak

Merge pull request !4608 from zhaozhenlong/lite/issue/concat_int8_mem_leak_fix

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

@@ -46,7 +46,7 @@ class ConcatBaseCPUKernel : public LiteKernel {
   int thread_count_;
   int axis_;
   const Context *ctx_;
-  ConcatParameter *concat_param_;
+  ConcatParameter *concat_param_ = nullptr;
 };
 }  // namespace mindspore::kernel
 

mindspore/lite/src/runtime/kernel/arm/int8/concat_int8.cc

@@ -28,9 +28,15 @@ namespace mindspore::kernel {
 
 int ConcatInt8CPUKernel::Init() {
   ConcatBaseCPUKernel::Init();
+  concat_param_->input_shapes_ = nullptr;
   auto input_num = in_tensors_.size();
+  input_data_ = reinterpret_cast<int8_t **>(malloc(sizeof(int8_t *) * input_num));
+  if (input_data_ == nullptr) {
+    MS_LOG(ERROR) << "Null pointer reference: inputs_array.";
+    return RET_ERROR;
+  }
   concat_param_->quant_arg_.in_args_ =
-    reinterpret_cast<QuantArg *>(ctx_->allocator->Malloc(sizeof(QuantArg) * input_num));
+    reinterpret_cast<QuantArg *>(malloc(sizeof(QuantArg) * input_num));
   if (concat_param_->quant_arg_.in_args_ == nullptr) {
     MS_LOG(ERROR) << "Null pointer reference: quant_concat_parm_->in_quant_args_.";
     return RET_ERROR;
@@ -61,11 +67,11 @@ int ConcatInt8CPUKernel::ReSize() {
     return ret;
   }
   if (concat_param_->input_shapes_ != nullptr) {
-    ctx_->allocator->Free(concat_param_->input_shapes_);
+//    free(concat_param_->input_shapes_);
   }
   auto input_num = in_tensors_.size();
   concat_param_->input_num_ = input_num;
-  concat_param_->input_shapes_ = reinterpret_cast<const int **>(ctx_->allocator->Malloc(sizeof(int *) * input_num));
+  concat_param_->input_shapes_ = reinterpret_cast<const int **>(malloc(sizeof(int *) * input_num));
   for (size_t i = 0; i < input_num; i++) {
     concat_param_->input_shapes_[i] = reinterpret_cast<const int *>(in_tensors_.at(i)->shape().data());
   }
@@ -96,11 +102,7 @@ int ConcatInt8CPUKernel::Run() {
   auto input_num = concat_param_->input_num_;
   count_unit_ = thread_count_ > 1 ? UP_DIV(before_axis_size, thread_count_) : before_axis_size;
   concat_param_->count_unit_ = count_unit_;
-  input_data_ = reinterpret_cast<int8_t **>(ctx_->allocator->Malloc(sizeof(int8_t *) * input_num));
-  if (input_data_ == nullptr) {
-    MS_LOG(ERROR) << "Null pointer reference: inputs_array.";
-    return RET_ERROR;
-  }
+
   for (size_t i = 0; i < input_num; i++) {
     input_data_[i] = static_cast<int8_t *>(in_tensors_.at(i)->Data());
   }
@@ -108,10 +110,6 @@ int ConcatInt8CPUKernel::Run() {
 
   ret = LiteBackendParallelLaunch(ConcatInt8Run, this, thread_count_);
 
-  ctx_->allocator->Free(input_data_);
-  ctx_->allocator->Free(concat_param_->input_shapes_);
-  ctx_->allocator->Free(concat_param_->quant_arg_.in_args_);
-
   return ret;
 }
 

mindspore/lite/src/runtime/kernel/arm/int8/concat_int8.h

@@ -32,7 +32,17 @@ class ConcatInt8CPUKernel : public ConcatBaseCPUKernel {
                       const std::vector<lite::tensor::Tensor *> &outputs, const Context *ctx,
                       const lite::Primitive *primitive)
       : ConcatBaseCPUKernel(parameter, inputs, outputs, ctx, primitive) {}
-  ~ConcatInt8CPUKernel() override {}
+  ~ConcatInt8CPUKernel() override {
+    if (input_data_ != nullptr) {
+      free(input_data_);
+    }
+    if (concat_param_->input_shapes_ != nullptr) {
+      free(concat_param_->input_shapes_);
+    }
+    if (concat_param_->quant_arg_.in_args_ != nullptr) {
+      free(concat_param_->quant_arg_.in_args_);
+    }
+  }
 
   int Init() override;
   int ReSize() override;

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/arithmetic_self_int8.c

@@ -35,7 +35,7 @@ int Int8ElementFloor(int8_t *input, int8_t *output, int element_size, ArithSelfQ
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -54,7 +54,7 @@ int Int8ElementRound(int8_t *input, int8_t *output, int element_size, ArithSelfQ
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -73,7 +73,7 @@ int Int8ElementCeil(int8_t *input, int8_t *output, int element_size, ArithSelfQu
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -92,7 +92,7 @@ int Int8ElementAbs(int8_t *input, int8_t *output, int element_size, ArithSelfQua
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -111,7 +111,7 @@ int Int8ElementSin(int8_t *input, int8_t *output, int element_size, ArithSelfQua
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -130,7 +130,7 @@ int Int8ElementCos(int8_t *input, int8_t *output, int element_size, ArithSelfQua
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -149,7 +149,7 @@ int Int8ElementLog(int8_t *input, int8_t *output, int element_size, ArithSelfQua
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -172,7 +172,7 @@ int Int8ElementSqrt(int8_t *input, int8_t *output, int element_size, ArithSelfQu
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -195,7 +195,7 @@ int Int8ElementRsqrt(int8_t *input, int8_t *output, int element_size, ArithSelfQ
     } else if (output_tmp < para.output_activation_min_) {
       output[i] = para.output_activation_min_;
     } else {
-      output[i] = (output_tmp);
+      output[i] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;
@@ -230,6 +230,7 @@ void SquareInt8NEON(int8_t *input_data, int8_t *output_data, int64_t element_siz
     int16x8_t res_s16 = vcombine_s16(sum_low, sum_high);
     int8x8_t res_u8_n0 = vqmovn_s16(res_s16);
     vst1_s8(output_data, res_u8_n0);
+    output_data += 8;
   }
 }
 #endif
@@ -253,7 +254,7 @@ int Int8ElementSquare(int8_t *input, int8_t *output, int element_size, ArithSelf
     } else if (output_tmp < para.output_activation_min_) {
       output[index] = para.output_activation_min_;
     } else {
-      output[index] = (output_tmp);
+      output[index] = (int8_t)output_tmp;
     }
   }
   return NNACL_OK;

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/concat_int8.c

@@ -22,36 +22,36 @@ void Int8Concat(int8_t **inputs, int8_t *output, ConcatParameter *para, int axis
   float output_scale = para->quant_arg_.out_args_.scale_;
   const float output_inverse_scale = 1.f / output_scale;
   int input_num = para->input_num_;
-  int count_unit_ = para->count_unit_;
-  int after_axis_size = para->after_axis_size;
+  int64_t count_unit_ = para->count_unit_;
+  int64_t after_axis_size = para->after_axis_size;
   const int *output_shape = para->output_shapes_;
   int out_copy_size = output_shape[axis] * after_axis_size;
   QuantArg *input_quant = para->quant_arg_.in_args_;
   int output_zp = para->quant_arg_.out_args_.zp_;
-  int max_int8 = para->quant_arg_.output_activation_max_;
-  int min_int8 = para->quant_arg_.output_activation_min_;
+  int8_t max_int8 = para->quant_arg_.output_activation_max_;
+  int8_t min_int8 = para->quant_arg_.output_activation_min_;
   int64_t start = task_id * count_unit_;
   int64_t end = start + real_dst_count;
+  output += start * out_copy_size;
 
   for (int k = start; k < end; k++) {
     for (int i = 0; i < input_num; i++) {
       const int *input_shape = para->input_shapes_[i];
-      int in_copy_size = input_shape[axis] * after_axis_size;
+      int64_t in_copy_size = input_shape[axis] * after_axis_size;
       int8_t *input_ptr = inputs[i] + k * in_copy_size;
-      int8_t *output_ptr = output + k * out_copy_size;
       if (input_quant[i].scale_ == output_scale && input_quant[i].zp_ == output_zp) {
-        memcpy(output_ptr, input_ptr, in_copy_size);
+        memcpy(output, input_ptr, in_copy_size);
       } else {
         float scale = input_quant[i].scale_ * output_inverse_scale;
         float bias = -input_quant[i].zp_ * scale;
         for (int j = 0; j < in_copy_size; j++) {
           int32_t output_tmp = round(input_ptr[j] * scale + bias) + output_zp;
           if (output_tmp > max_int8) {
-            output_ptr[j] = max_int8;
+            output[j] = max_int8;
           } else if (output_tmp < min_int8) {
-            output_ptr[j] = min_int8;
+            output[j] = min_int8;
           } else {
-            output_ptr[j] = (output_tmp);
+            output[j] = (int8_t)output_tmp;
           }
         }
       }

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/crop_int8.c

@@ -68,7 +68,7 @@ void Crop1D(const int8_t *input, int8_t *output, int task_id, CropParameter *par
       } else if (output_tmp < para->quant_arg.output_activation_min_) {
         out_ptr[i] = para->quant_arg.output_activation_min_;
       } else {
-        out_ptr[i] = output_tmp;
+        out_ptr[i] = (int8_t)output_tmp;
       }
     }
   }
@@ -110,7 +110,7 @@ void Crop2D(const int8_t *input, int8_t *output, int task_id, CropParameter *par
         } else if (output_tmp < para->quant_arg.output_activation_min_) {
           out_ptr[i] = para->quant_arg.output_activation_min_;
         } else {
-          out_ptr[i] = (output_tmp);
+          out_ptr[i] = (int8_t)output_tmp;
         }
       }
     }
@@ -164,7 +164,7 @@ void Crop3D(const int8_t *input, int8_t *output, int task_id, CropParameter *par
           } else if (output_tmp < para->quant_arg.output_activation_min_) {
             out_ptr[i] = para->quant_arg.output_activation_min_;
           } else {
-            out_ptr[i] = (output_tmp);
+            out_ptr[i] = (int8_t)output_tmp;
           }
         }
       }
@@ -225,7 +225,7 @@ void Int8Crop4D(const int8_t *input, int8_t *output, int task_id, CropParameter
             } else if (output_tmp < para->quant_arg.output_activation_min_) {
               out_ptr[i] = para->quant_arg.output_activation_min_;
             } else {
-              out_ptr[i] = (output_tmp);
+              out_ptr[i] = (int8_t)output_tmp;
             }
           }
         }

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/mul_int8.c

@@ -80,7 +80,7 @@ void Mul(int8_t *input0_data, int8_t *input1_data, int8_t *output_data, int64_t
     } else if (mul_result < para.output_activation_min_) {
       output_data[index] = para.output_activation_min_;
     } else {
-      output_data[index] = (mul_result);
+      output_data[index] = (int8_t)mul_result;
     }
   }
   return;

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/reshape_int8.c

@@ -33,7 +33,7 @@ void Int8Reshape(int8_t *input_ptr, int8_t *output_ptr, int64_t real_dst_count,
       } else if (output_tmp < para.output_activation_min_) {
         output_ptr[i] = para.output_activation_min_;
       } else {
-        output_ptr[i] = output_tmp;
+        output_ptr[i] = (int8_t)output_tmp;
       }
     }
   }

mindspore/lite/src/runtime/kernel/arm/nnacl/int8/split_int8.c

@@ -62,7 +62,7 @@ int Int8DoSplit(int8_t *in_data, int8_t **out_data, const int *input_shape, int
         } else if (output_tmp < param->quant_arg_.output_activation_min_) {
           dst[j] = param->quant_arg_.output_activation_min_;
         } else {
-          dst[j] = output_tmp;
+          dst[j] = (int8_t)output_tmp;
         }
       }
     }

mindspore/lite/src/runtime/kernel/arm/nnacl/quantization/quantize.h

@@ -53,8 +53,8 @@ typedef struct ConvQuantArg {
 typedef struct ConcatQuantArg {
   QuantArg *in_args_;
   QuantArg out_args_;
-  int output_activation_min_;
-  int output_activation_max_;
+  int8_t output_activation_min_;
+  int8_t output_activation_max_;
 } ConcatQuantArg;
 
 typedef struct SqueezeQuantArg {