fix bug of int mul and add overflow

mindspore/lite/src/runtime/kernel/arm/fp16/cast_fp16.cc

@@ -125,15 +125,11 @@ int CastFp16CPUKernel::DoCast(int thread_id) {
         return RET_ERROR;
     }
   } else if (input_data_type == kNumberTypeInt32) {
-    switch (output_data_type) {
-      case kNumberTypeFloat32:
-        Int32ToFloat32(static_cast<int32_t *>(input_data) + offset, static_cast<float *>(output_data) + offset,
-                       data_num);
-        break;
-      default:
-        MS_LOG(ERROR) << "Unsupported output data type " << output_data_type;
-        return RET_ERROR;
+    if (output_data_type != kNumberTypeFloat32) {
+      MS_LOG(ERROR) << "Unsupported output data type " << output_data_type;
+      return RET_ERROR;
     }
+    Int32ToFloat32(static_cast<int32_t *>(input_data) + offset, static_cast<float *>(output_data) + offset, data_num);
   } else {
     MS_LOG(ERROR) << "Unsupported input data type " << input_data_type;
     return RET_ERROR;

mindspore/lite/src/runtime/kernel/arm/fp16_grad/strided_slice_fp16_grad.cc

@@ -41,14 +41,11 @@ int StridedSliceGradCPUKernelFp16::Prepare() {
   auto input = in_tensors_.at(0);
   CHECK_NULL_RETURN(input);
   CHECK_NULL_RETURN(out_tensors_.at(0));
-  switch (input->data_type()) {
-    case kNumberTypeFloat16:
-      param_->data_type = kDataTypeFloat16;
-      break;
-    default:
-      MS_LOG(ERROR) << "Not supported data type: " << input->data_type();
-      return RET_ERROR;
+  if (input->data_type() != kNumberTypeFloat16) {
+    MS_LOG(ERROR) << "Not supported data type: " << input->data_type();
+    return RET_ERROR;
   }
+  param_->data_type = kDataTypeFloat16;
   FillEmptyDims();
   FillOutputDim();
   return ReSize();

mindspore/lite/src/runtime/kernel/arm/fp32_grad/strided_slice_grad.cc

@@ -42,14 +42,11 @@ int StridedSliceGradCPUKernel::Prepare() {
   CHECK_NULL_RETURN(out_tensors_.at(0));
   auto input = in_tensors_.at(0);
   CHECK_NULL_RETURN(input);
-  switch (input->data_type()) {
-    case kNumberTypeFloat32:
-      param_->data_type = kDataTypeFloat;
-      break;
-    default:
-      MS_LOG(ERROR) << "Not supported data type: " << input->data_type();
-      return RET_ERROR;
+  if (input->data_type() != kNumberTypeFloat32) {
+    MS_LOG(ERROR) << "Not supported data type: " << input->data_type();
+    return RET_ERROR;
   }
+  param_->data_type = kDataTypeFloat;
   return ReSize();
 }
 

mindspore/lite/src/scheduler.cc

@@ -655,15 +655,10 @@ int Scheduler::CopyPartialShapeToSubGraph(const lite::Model::Node *partial_node)
   for (size_t i = 0; i < partial_node->input_indices_.size(); ++i) {
     auto &subgraph_input = src_tensors_->at(subgraph->input_indices_[i]);
     auto &partial_input = src_tensors_->at(partial_node->input_indices_[i]);
-    switch (partial_input->data_type()) {
-      case kObjectTypeTensorType: {
-        return RET_INFER_INVALID;
-      }
-      default: {
-        CopyCommonTensor(subgraph_input, partial_input);
-        break;
-      }
+    if (partial_input->data_type() == kObjectTypeTensorType) {
+      return RET_INFER_INVALID;
     }
+    CopyCommonTensor(subgraph_input, partial_input);
   }
 
   return RET_OK;

mindspore/lite/src/tensor.cc

@@ -226,11 +226,29 @@ int32_t Tensor::ElementsC4Num() const {
   if (this->category_ == CONST_SCALAR) {
     return 1;
   }
-  int32_t result = 1;
+  int64_t result = 1;
   if (this->shape_.size() == 4) {
-    result = Batch() * Height() * Width() * ((Channel() + 3) / 4 * 4);
+    int64_t tmp_channel = Channel() + 3;
+    if (tmp_channel > static_cast<int64_t>(INT32_MAX) || tmp_channel < 0) {
+      MS_LOG(ERROR) << "extend INT32_MAX: " << tmp_channel << " return INT32_MAX";
+      return INT32_MAX;
+    }
+    result = Batch() * Height() * Width() * (tmp_channel / 4 * 4);
+    if (result > static_cast<int64_t>(INT32_MAX) || result < 0) {
+      MS_LOG(ERROR) << "extend INT32_MAX: " << result << " return INT32_MAX";
+      return INT32_MAX;
+    }
   } else if (this->shape_.size() == 2) {
-    result = this->shape_[0] * ((this->shape_[1] + 3) / 4 * 4);
+    int64_t tmp_shape = this->shape_[1] + 3;
+    if (tmp_shape > static_cast<int64_t>(INT32_MAX) || tmp_shape < 0) {
+      MS_LOG(ERROR) << "extend INT32_MAX: " << tmp_shape << " return INT32_MAX";
+      return INT32_MAX;
+    }
+    result = this->shape_[0] * (tmp_shape / 4 * 4);
+    if (result > static_cast<int64_t>(INT32_MAX) || result < 0) {
+      MS_LOG(ERROR) << "extend INT32_MAX: " << result << " return INT32_MAX";
+      return INT32_MAX;
+    }
   }
   return result;
 }