fix LSTM quant bug and fix ToD: check input param

mindspore/lite/src/train/transfer_session.cc

@@ -159,6 +159,18 @@ session::TrainSession *session::TrainSession::CreateTransferSession(const char *
                                                                     size_t size_backbone, const char *model_buf_head,
                                                                     size_t size_head, lite::Context *context,
                                                                     bool train_mode) {
+  auto ValidModelSize = [](size_t size) -> bool {
+    constexpr size_t MaxModelSize = 1024 * 1024 * 1024ULL;  // 1G B
+    return size < MaxModelSize && size > 0;
+  };
+  if (!ValidModelSize(size_backbone)) {
+    MS_LOG(ERROR) << "size_backbone too large: " << size_backbone;
+    return nullptr;
+  }
+  if (!ValidModelSize(size_head)) {
+    MS_LOG(ERROR) << "size_head too large: " << size_head;
+    return nullptr;
+  }
   auto session = new (std::nothrow) lite::TransferSession(model_buf_backbone, size_backbone, context);
   if (session == nullptr) {
     MS_LOG(ERROR) << "create transfer session failed";

mindspore/lite/tools/converter/quantizer/weight_quantizer.cc

@@ -275,8 +275,8 @@ STATUS WeightQuantizer::ProcessLstmWeightByIndex(const CNodePtr &cnode, const Pr
   ParamValueLitePtr param_value;
   GetLiteParameter(weight_i, &param_node, &param_value);
   if (param_node == nullptr || param_value == nullptr) {
-    MS_LOG(ERROR) << "GetLiteParameter error";
-    return RET_ERROR;
+    MS_LOG(INFO) << "LSTM input index " << index << " is not weight";
+    return RET_OK;
   }
   if (param_value->tensor_type() != TypeId::kNumberTypeFloat32) {
     MS_LOG(WARNING) << "param_value tensor type is: " << param_value->tensor_type() << " not quant";