fix thread problem

mindspore/lite/src/ops/tile.cc

@@ -186,7 +186,8 @@ int Tile::InferShape(std::vector<Tensor *> inputs_, std::vector<Tensor *> output
     out_shape.push_back(input->shape().at(i));
   }
   for (size_t i = 0; i < dims.size(); ++i) {
-    if (multiples.at(i) > std::numeric_limits<int>::max() / input->shape().at(dims.at(i))) {
+    if (input->shape().at(dims.at(i)) != 0 &&
+        multiples.at(i) > std::numeric_limits<int>::max() / input->shape().at(dims.at(i))) {
       MS_LOG(ERROR) << "The value of multiples[" << i << "] is too big";
       return RET_ERROR;
     }

mindspore/lite/src/runtime/kernel/arm/fp32/addn_fp32.cc

@@ -44,7 +44,7 @@ int AddNCPUKernel::ReSize() { return RET_OK; }
 
 int AddNCPUKernel::AddNParallelRun(int thread_id) {
   int count_per_thread = UP_DIV(elements_num_, op_parameter_->thread_num_);
-  int count = MSMIN(count_per_thread, static_cast<int>(elements_num_ - thread_id * count_per_thread));
+  int count = MSMIN(count_per_thread, elements_num_ - thread_id * count_per_thread);
   auto stride = count_per_thread * thread_id;
   auto ret = ElementAdd(in1_addr_ + stride, in2_addr_ + stride, out_addr_ + stride, count);
   if (ret != NNACL_OK) {

mindspore/lite/src/runtime/kernel/arm/fp32/addn_fp32.h

@@ -39,7 +39,7 @@ class AddNCPUKernel : public LiteKernel {
   float *in1_addr_;
   float *in2_addr_;
   float *out_addr_;
-  size_t elements_num_;
+  int elements_num_;
 };
 }  // namespace mindspore::kernel
 

mindspore/lite/src/runtime/kernel/arm/fp32/crop_and_resize_fp32.cc

@@ -121,19 +121,15 @@ int CropAndResizeCPUKernel::RunImpl(int task_id) {
   int unit = UP_DIV(new_height_, context_->thread_num_);
   int h_begin = unit * task_id;
   int h_end = MSMIN(h_begin + unit, new_height_);
+  if (h_end <= h_begin) {
+    return RET_OK;
+  }
   int c = in_tensors_.at(0)->shape().at(3);
   float *line0 = line_buffer_ + new_width_ * c * 2 * task_id;
   float *line1 = line0 + new_width_ * c;
-  int ret = 0;
-  if (is_crop_) {
-    ret = CropAndResizeBilinear(input_data, output_data, input_shape.data(), out_tensors_.at(0)->shape().data(),
-                                y_bottoms_, y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_, line0,
-                                line1, h_begin, h_end);
-  } else {
-    ret =
-      ResizeBilinear(input_data, output_data, input_shape.data(), out_tensors_.at(0)->shape().data(), y_bottoms_,
-                     y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_, line0, line1, h_begin, h_end);
-  }
+  auto ret = CropAndResizeBilinear(input_data, output_data, input_shape.data(), out_tensors_.at(0)->shape().data(),
+                                   y_bottoms_, y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_, line0,
+                                   line1, h_begin, h_end);
   return ret;
 }
 
@@ -146,19 +142,10 @@ int CropAndResizeCPUKernel::Run() {
 
   auto input = in_tensors_.at(0);
   auto input_shape = input->shape();
-  // if boxes tensor data is nullptr, crop_and_resize can be seen as resize with coordinate transformation mode
-  // ALIGN_CORNERS
-  if (in_tensors_.at(1)->ElementsNum() == 0 || in_tensors_.at(1)->data_c() == nullptr) {
-    batch_ = 1;
-    is_crop_ = false;
-    ret = PrepareResizeBilinear(input_shape.data(), out_tensors_.at(0)->shape().data(), CalculateAlignCorners,
-                                y_bottoms_, y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_);
-  } else {
-    auto boxes = reinterpret_cast<float *>(in_tensors_.at(1)->data_c());
-    auto box_idx = reinterpret_cast<int32_t *>(in_tensors_.at(2)->data_c());
-    ret = PrepareCropAndResizeBilinear(input_shape.data(), boxes, box_idx, out_tensors_.at(0)->shape().data(),
-                                       y_bottoms_, y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_);
-  }
+  auto boxes = reinterpret_cast<float *>(in_tensors_.at(1)->data_c());
+  auto box_idx = reinterpret_cast<int32_t *>(in_tensors_.at(2)->data_c());
+  ret = PrepareCropAndResizeBilinear(input_shape.data(), boxes, box_idx, out_tensors_.at(0)->shape().data(), y_bottoms_,
+                                     y_tops_, x_lefts_, x_rights_, y_bottom_weights_, x_left_weights_);
   if (ret != RET_OK) {
     FreeTmpBuffer();
     return ret;

mindspore/lite/src/runtime/kernel/arm/fp32/crop_and_resize_fp32.h

@@ -46,7 +46,6 @@ class CropAndResizeCPUKernel : public LiteKernel {
   int batch_;
   int new_height_;
   int new_width_;
-  bool is_crop_ = true;
   int *y_tops_ = nullptr;
   int *y_bottoms_ = nullptr;
   int *x_lefts_ = nullptr;

mindspore/lite/test/models_with_several_inputs_or_without_outputs.cfg

@@ -37,3 +37,4 @@ ml_video_edit_video_segment_gauss_adaptis_part2.pb;2
 ml_video_edit_video_segment_gauss_adaptis_part2_pb2tflite.tflite;2
 tiny-yolov3-11.onnx;2;1,416,416,3:1,2
 ml_video_edit_person_divison_pic;2
+fasterrcnn_crop.pb;1;236,190,3