[RKNPU][APU] Fix the incorrect inference results from mobilenetv1-int8 on RKNPU and APU (#4368)

lite/core/mir/subgraph/subgraph_detector.cc

@@ -463,6 +463,38 @@ void SubgraphFuser::InsertNewNode(SSAGraph *graph,
                                                      idata_var_names);
   subgraph_op_desc.SetAttr<std::vector<std::string>>("output_data_names",
                                                      odata_var_names);
+
+  // Set input/output scale values of input/output var nodes for
+  // type_precision_cast_pass.
+  std::vector<float> input_data_scales;
+  std::vector<float> output_data_scales;
+  for (auto &var_node : idata_var_nodes) {
+    auto any_op_node = var_node->outlinks.front();
+    CHECK(any_op_node->IsStmt());
+    auto &any_inst = any_op_node->AsStmt();
+    if (any_inst.op_info()->HasAttr("input_scale")) {
+      input_data_scales.push_back(
+          any_inst.op_info()->GetAttr<float>("input_scale"));
+    }
+  }
+  for (auto &var_node : odata_var_nodes) {
+    auto any_op_node = var_node->inlinks.front();
+    CHECK(any_op_node->IsStmt());
+    auto &any_inst = any_op_node->AsStmt();
+    if (any_inst.op_info()->HasAttr("output_scale")) {
+      output_data_scales.push_back(
+          any_inst.op_info()->GetAttr<float>("output_scale"));
+    }
+  }
+  if (input_data_scales.size() > 0) {
+    subgraph_op_desc.SetAttr<std::vector<float>>("input_data_scales",
+                                                 input_data_scales);
+  }
+  if (output_data_scales.size() > 0) {
+    subgraph_op_desc.SetAttr<std::vector<float>>("output_data_scales",
+                                                 output_data_scales);
+  }
+
   // Set all of the inputs and outputs to the target subgraph op
   // To prevent vars are removed in RuntimeProgram::UpdateVarsOfProgram()
   std::vector<std::string> input_var_names;

lite/kernels/apu/bridges/softmax_op.cc

@@ -104,7 +104,7 @@ int SoftmaxConverter(void* ctx, OpLite* op, KernelBase* kernel) {
   // Add out operand
   NeuronOperandType outType;
   outType.type = NEURON_TENSOR_QUANT8_ASYMM;
-  outType.scale = out_scale / 127;
+  outType.scale = out_scale;
   outType.zeroPoint = 128;
   outType.dimensionCount = x_dims.size();
   outType.dimensions = &dims_x[0];

lite/utils/string.h

@@ -60,13 +60,6 @@ static std::string to_string(const T& v) {
   return ss.str();
 }
 
-static std::string to_string(int index) {
-  const int BUFFER_LENGTH = 15;
-  char buffer[BUFFER_LENGTH];
-  snprintf(buffer, sizeof(buffer), "%d", index);
-  return std::string(buffer);
-}
-
 template <typename T = std::string>
 static T parse_string(const std::string& v) {
   return v;