!6055 [MSLITE] Fix bug of several quantized operators inference.

Merge pull request !6055 from wangshaocong/lite_bugfix

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

@@ -79,7 +79,12 @@ int QuantDTypeCastCPUKernel::QuantDTypeCast(int task_id) {
     return RET_OK;
   }
   int thread_offset = task_id * thread_n_stride_;
-  auto quant_arg = in_tensors_.front()->GetQuantParams().front();
+  if (in_tensors_.front()->GetQuantParams().empty() && out_tensors_.front()->GetQuantParams().empty()) {
+    MS_LOG(ERROR) << "QuantDTypeCast need quantization parameters which is not found.";
+    return RET_ERROR;
+  }
+  auto quant_arg = !in_tensors_.front()->GetQuantParams().empty() ? in_tensors_.front()->GetQuantParams().front() :
+                   out_tensors_.front()->GetQuantParams().front();
   int ret;
   if (inverse_) {
     ret = DoDequantizeInt8(int8_ptr_ + thread_offset, float32_ptr_ + thread_offset, quant_arg.scale,

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

@@ -92,17 +92,10 @@ int QuantizedAddCPUKernel::Run() {
     input0_data_ = static_cast<int8_t *>(ctx_->allocator->Malloc(out_tensors_.at(0)->Size()));
     input1_data_ = static_cast<int8_t *>(ctx_->allocator->Malloc(out_tensors_.at(0)->Size()));
 
-    ArithmeticParameter tile_para;
-    tile_para.ndim_ = out_tensors_.at(0)->shape().size();
-    for (size_t i = 0; i < tile_para.ndim_; i++) {
-      tile_para.in_shape0_[i] = in_tensors_.at(0)->DimensionSize(i);
-      tile_para.in_shape1_[i] = in_tensors_.at(1)->DimensionSize(i);
-      tile_para.out_shape_[i] = out_tensors_.at(0)->DimensionSize(i);
-    }
     TileDimensionsUint8(static_cast<uint8_t *>(in_tensors_.at(0)->MutableData()),
                         static_cast<uint8_t *>(in_tensors_.at(1)->MutableData()),
                         reinterpret_cast<uint8_t *>(input0_data_), reinterpret_cast<uint8_t *>(input1_data_),
-                        &tile_para);
+                        arith_para_);
     ret = ParallelLaunch(THREAD_POOL_DEFAULT, AddInt8Run, this, thread_count_);
     ctx_->allocator->Free(input0_data_);
     ctx_->allocator->Free(input1_data_);

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

@@ -19,6 +19,7 @@
 #include <vector>
 #include "src/lite_kernel.h"
 #include "nnacl/int8/add_int8.h"
+#include "nnacl/arithmetic_common.h"
 #include "src/runtime/runtime_api.h"
 
 namespace mindspore::kernel {
@@ -27,7 +28,9 @@ class QuantizedAddCPUKernel : public LiteKernel {
   explicit QuantizedAddCPUKernel(OpParameter *parameter, const std::vector<lite::Tensor *> &inputs,
                                  const std::vector<lite::Tensor *> &outputs, const lite::Context *ctx,
                                  const mindspore::lite::PrimitiveC *primitive)
-      : LiteKernel(parameter, inputs, outputs, ctx, primitive), ctx_(ctx), thread_count_(ctx_->thread_num_) {}
+      : LiteKernel(parameter, inputs, outputs, ctx, primitive), ctx_(ctx), thread_count_(ctx_->thread_num_) {
+    arith_para_ = reinterpret_cast<ArithmeticParameter *>(parameter);
+  }
   ~QuantizedAddCPUKernel() override {}
 
   int Init() override;
@@ -38,6 +41,7 @@ class QuantizedAddCPUKernel : public LiteKernel {
  private:
   const lite::Context *ctx_;
   AddQuantParameter para_;
+  ArithmeticParameter *arith_para_;
   int thread_count_;
   int64_t elements_num_;
   int64_t count_unit_;

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

@@ -91,7 +91,7 @@ ParameterPtr CreateNewParamter(const FuncGraphPtr &func_graph, Tensor *tensor) {
       MS_LOG(ERROR) << "tensor_data is nullptr";
       return nullptr;
     }
-    auto ret = memcpy_s(tensor_data, size * sizeof(float), tensor->MutableData(), size * sizeof(float));
+    auto ret = memcpy_s(tensor_data, tensor->Size(), tensor->MutableData(), tensor->Size());
     if (ret != EOK) {
       delete[] tensor_data;
       MS_LOG(ERROR) << "memcpy error: " << ret;
@@ -234,6 +234,9 @@ const AnfNodePtr ConstFoldPass::Process(const FuncGraphPtr &func_graph, const An
       return nullptr;
     }
     lite::Context context;
+    if (context.allocator == nullptr) {
+      context.allocator = lite::Allocator::Create();
+    }
     auto lite_kernel = GetLiteKernel(input_tensors, output_tensors, parameter, &context, lite_primitive.get());
     if (lite_kernel == nullptr) {
       MS_LOG(ERROR) << "constant_folding schedule node lite kernel nullptr";