diff --git a/mindspore/lite/src/lite_mindrt.cc b/mindspore/lite/src/lite_mindrt.cc
index eb03a680c41..c8c3450430c 100644
--- a/mindspore/lite/src/lite_mindrt.cc
+++ b/mindspore/lite/src/lite_mindrt.cc
@@ -83,6 +83,16 @@ void LiteOpActor::IsolateInputData(std::vector<std::shared_ptr<LiteOpActor>> *ac
     Tensor *old_tensor = kernel_->in_tensors()[i];
 
     if (OfflineIsolated(kernels, *kernel_, *old_tensor)) {
+      if (old_tensor->data_type() == kNumberTypeFloat16 || old_tensor->data_type() == kNumberTypeFloat32) {
+        old_tensor->set_data_type(kernel_->desc().data_type);
+      }
+      if (old_tensor->data_type() == kObjectTypeTensorType) {
+        auto old_tensorlist = reinterpret_cast<TensorList *>(old_tensor);
+        if (old_tensorlist->tensors_data_type() == kNumberTypeFloat16 ||
+            old_tensorlist->tensors_data_type() == kNumberTypeFloat32) {
+          old_tensorlist->set_tensors_data_type(kernel_->desc().data_type);
+        }
+      }
       continue;
     }
 
@@ -310,7 +320,31 @@ void LiteOpActor::SetInputData(Tensor *dst_tensor, Tensor *src_tensor) {
 }
 
 int LiteOpActor::CastInputData(Tensor *dst, Tensor *src) {
+  int ret = RET_OK;
   dst->ResetRefCount();
+  if (src->data_type() != kObjectTypeTensorType) {
+    ret = CastTensorInputData(dst, src);
+  } else {
+    ret = CastTensorListInputData(reinterpret_cast<TensorList *>(dst), reinterpret_cast<TensorList *>(src));
+  }
+  src->DecRefCount();
+  return ret;
+}
+
+bool LiteOpActor::NeedCastData(Tensor *dst_tensor, Tensor *src_tensor) {
+  if (dst_tensor->data_type() != kObjectTypeTensorType && src_tensor->data_type() != kObjectTypeTensorType &&
+      dst_tensor->data_type() != src_tensor->data_type()) {
+    return true;
+  }
+  if (dst_tensor->data_type() == kObjectTypeTensorType && src_tensor->data_type() == kObjectTypeTensorType &&
+      reinterpret_cast<TensorList *>(dst_tensor)->tensors_data_type() !=
+        reinterpret_cast<TensorList *>(src_tensor)->tensors_data_type()) {
+    return true;
+  }
+  return false;
+}
+
+int LiteOpActor::CastTensorInputData(Tensor *dst, Tensor *src) {
   dst->MallocData();
 #if defined(ENABLE_ARM) && defined(ENABLE_FP16)
   if (dst->shape() != src->shape()) {
@@ -332,13 +366,37 @@ int LiteOpActor::CastInputData(Tensor *dst, Tensor *src) {
     MS_LOG(ERROR) << "not support dst_data_type: " << dst_data_type << " src_data_type: " << src_data_type;
     return RET_NOT_SUPPORT;
   }
-  src->DecRefCount();
   return RET_OK;
 #endif
-  src->DecRefCount();
   return RET_ERROR;
 }
 
+int LiteOpActor::CastTensorListInputData(TensorList *dst_tensorlist, TensorList *src_tensorlist) {
+  MS_ASSERT(src_tensorlist != nullptr);
+  MS_ASSERT(dst_tensorlist != nullptr);
+  dst_tensorlist->set_shape(src_tensorlist->shape());
+  std::vector<std::vector<int>> tensors_shapes{};
+  tensors_shapes.resize(src_tensorlist->tensors().size());
+  for (size_t i = 0; i < tensors_shapes.size(); ++i) {
+    tensors_shapes[i] = src_tensorlist->tensors()[i]->shape();
+  }
+  if (src_tensorlist->tensors_data_type() == kNumberTypeFloat16) {
+    dst_tensorlist->MallocTensorListData(kNumberTypeFloat32, tensors_shapes);
+  }
+  if (src_tensorlist->tensors_data_type() == kNumberTypeFloat32) {
+    dst_tensorlist->MallocTensorListData(kNumberTypeFloat16, tensors_shapes);
+  }
+  dst_tensorlist->ResetRefCount();
+  dst_tensorlist->set_allocator(src_tensorlist->allocator());
+
+  for (size_t i = 0; i < src_tensorlist->tensors().size(); ++i) {
+    auto &src_tensor = src_tensorlist->tensors()[i];
+    auto &dst_tensor = dst_tensorlist->tensors()[i];
+    CastTensorInputData(dst_tensor, src_tensor);
+  }
+  return RET_OK;
+}
+
 void LiteOpActor::SetInputShape() {
   for (size_t i = 0; i < inputs_data_.size(); ++i) {
     auto &input_tensor = kernel_->in_tensors()[i];
@@ -377,8 +435,7 @@ int LiteOpActor::InitInputData() {
       continue;
     }
 
-    if (src_tensor->data_type() != dst_tensor->data_type()) {
-      /* fp16 & fp32 transfer */
+    if (NeedCastData(dst_tensor, src_tensor)) {
       CastInputData(dst_tensor, src_tensor);
       continue;
     }
diff --git a/mindspore/lite/src/lite_mindrt.h b/mindspore/lite/src/lite_mindrt.h
index 5a23febfde6..cb362ab4955 100644
--- a/mindspore/lite/src/lite_mindrt.h
+++ b/mindspore/lite/src/lite_mindrt.h
@@ -99,6 +99,9 @@ class LiteOpActor : public OpActor<lite::Tensor> {
   void MoveInputData(Tensor *dst_tensor, Tensor *src_tensor);
   void SetInputData(Tensor *dst_tensor, Tensor *src_tensor);
   int CastInputData(Tensor *dst_tensor, Tensor *src_tensor);
+  bool NeedCastData(Tensor *dst_tensor, Tensor *src_tensor);
+  int CastTensorInputData(Tensor *dst_tensor, Tensor *src_tensor);
+  int CastTensorListInputData(TensorList *dst_tensor, TensorList *src_tensor);
 
  private:
   kernel::LiteKernel *partial_node_ = nullptr;
diff --git a/mindspore/lite/src/sub_graph_kernel.cc b/mindspore/lite/src/sub_graph_kernel.cc
index c3465e56035..c75b955fea9 100644
--- a/mindspore/lite/src/sub_graph_kernel.cc
+++ b/mindspore/lite/src/sub_graph_kernel.cc
@@ -240,228 +240,4 @@ int CpuSubGraph::Execute(const KernelCallBack &before, const KernelCallBack &aft
   }
   return RET_OK;
 }
-#if defined(ENABLE_ARM) && defined(ENABLE_FP16)
-void CpuFp16SubGraph::FreeOriginInputData() {
-  for (auto &iter : this->origin_input_data_) {
-    auto *data_store = iter.second;
-    if (data_store == nullptr) {
-      continue;
-    }
-    // free data in data_store
-    if (data_store->data_ != nullptr) {
-      if (data_store->allocator_ == nullptr) {
-        free(data_store->data_);
-      } else {
-        data_store->allocator_->Free(data_store->data_);
-      }
-    }
-    // free data_store
-    if (this->Context()->allocator != nullptr) {
-      this->Context()->allocator->Free(data_store);
-    } else {
-      free(data_store);
-    }
-    data_store = nullptr;
-  }
-  this->origin_input_data_.clear();
-}
-
-int CpuFp16SubGraph::Float32TensorToFloat16Tensor(lite::Tensor *tensor) {
-  MS_ASSERT(tensor != nullptr);
-  auto float32_data = tensor->data_c();
-  auto own_data = tensor->own_data();
-  tensor->set_data_type(TypeId::kNumberTypeFloat16);
-  if (float32_data == nullptr) {
-    // the input data may be nullptr of merge.
-    MS_LOG(INFO) << "tensor data is null.";
-    return lite::RET_OK;
-  }
-  tensor->set_data(nullptr);
-  auto ret = tensor->MallocData();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "malloc data failed";
-    return RET_ERROR;
-  }
-  MS_ASSERT(tensor->data_c() != nullptr);
-  Float32ToFloat16_fp16_handler(float32_data, tensor->data_c(), tensor->ElementsNum(), support_fp16_);
-  if (tensor->allocator() != nullptr) {
-    tensor->allocator()->SetRefCount(tensor->data_c(), tensor->allocator()->RefCount(float32_data));
-  }
-  auto *data_store =
-    DataStore::CreateDataStore(float32_data, own_data, tensor->allocator().get(), this->Context()->allocator.get());
-  if (data_store == nullptr) {
-    MS_LOG(ERROR) << "Create DataStore failed";
-    return RET_ERROR;
-  }
-  origin_input_data_[tensor] = data_store;
-  return RET_OK;
-}
-
-int CpuFp16SubGraph::Float16TensorToFloat32Tensor(lite::Tensor *tensor) {
-  auto float16_data = tensor->data_c();
-  if (float16_data == nullptr) {
-    MS_LOG(ERROR) << "tensor data is null.";
-    return lite::RET_NULL_PTR;
-  }
-  tensor->set_data(nullptr);
-  tensor->set_data_type(TypeId::kNumberTypeFloat32);
-  auto ret = tensor->MallocData();
-  if (ret != RET_OK) {
-    MS_LOG(ERROR) << "malloc data failed";
-    if (this->Context() != nullptr && this->Context()->allocator != nullptr) {
-      this->Context()->allocator->Free(float16_data);
-    } else {
-      free(float16_data);
-    }
-    return RET_ERROR;
-  }
-  MS_ASSERT(tensor->data_c() != nullptr);
-  Float16ToFloat32_fp16_handler(float16_data, tensor->data_c(), tensor->ElementsNum(), support_fp16_);
-  if (tensor->allocator() != nullptr) {
-    tensor->allocator()->SetRefCount(tensor->data_c(), tensor->allocator()->RefCount(float16_data));
-    tensor->allocator()->Free(float16_data);
-  } else {
-    free(float16_data);
-  }
-  return RET_OK;
-}
-
-int CpuFp16SubGraph::PreProcess() {
-#ifdef ENABLE_FP16
-  int ret;
-  for (auto tensor : this->in_tensors()) {
-    MS_ASSERT(tensor != nullptr);
-    auto real_tensor = tensor;
-    if (tensor->root_tensor() != nullptr) {
-      real_tensor = tensor->root_tensor();
-      if (tensor->data_type() == kNumberTypeFloat32) {
-        tensor->set_data_type(kNumberTypeFloat16);
-      } else if (tensor->data_type() == kObjectTypeTensorType) {
-        auto tensorlist = reinterpret_cast<lite::TensorList *>(tensor);
-        if (tensorlist->tensors_data_type() == kNumberTypeFloat32) {
-          tensorlist->set_tensors_data_type(kNumberTypeFloat16);
-        }
-      }
-    }
-    if (real_tensor->data_type() == kNumberTypeFloat32) {
-      ret = Float32TensorToFloat16Tensor(real_tensor);
-      if (ret != RET_OK) {
-        MS_LOG(ERROR) << "Float32TensorToFloat16Tensor failed.";
-        this->FreeOriginInputData();
-        return ret;
-      }
-    } else if (real_tensor->data_type() == kObjectTypeTensorType) {
-      auto tensorlist = reinterpret_cast<lite::TensorList *>(real_tensor);
-      if (tensorlist->tensors_data_type() == kNumberTypeFloat32) {
-        tensorlist->set_tensors_data_type(kNumberTypeFloat16);
-        for (auto inner_tensor : tensorlist->tensors()) {
-          ret = Float32TensorToFloat16Tensor(inner_tensor);
-          if (ret != RET_OK) {
-            MS_LOG(ERROR) << "Float32TensorToFloat16Tensor failed.";
-            this->FreeOriginInputData();
-            return ret;
-          }
-        }
-      }
-    }
-  }
-  for (auto kernel : this->nodes_) {
-    for (auto tensor : kernel->out_tensors()) {
-      if (kernel->type() == schema::PrimitiveType_Cast) {
-        continue;
-      }
-      if (tensor->data_type() == kNumberTypeFloat32) {
-        tensor->set_data_type(kNumberTypeFloat16);
-      } else if (tensor->data_type() == kObjectTypeTensorType) {
-        auto tensorlist = reinterpret_cast<lite::TensorList *>(tensor);
-        if (tensorlist->tensors_data_type() == kNumberTypeFloat32) {
-          tensorlist->set_tensors_data_type(kNumberTypeFloat16);
-        }
-      }
-    }
-  }
-  return RET_OK;
-#else
-  return RET_OK;
-#endif
-}
-
-int CpuFp16SubGraph::PostProcess() {
-#ifdef ENABLE_FP16
-  int ret;
-  for (auto tensor : this->out_tensors()) {
-    MS_ASSERT(tensor != nullptr);
-    if (tensor->data_type() == kNumberTypeFloat16) {
-      ret = Float16TensorToFloat32Tensor(tensor);
-      if (ret != RET_OK) {
-        MS_LOG(ERROR) << "Float16TensorToFloat32Tensor failed.";
-        return ret;
-      }
-    } else if (tensor->data_type() == kObjectTypeTensorType) {
-      auto tensorlist = reinterpret_cast<lite::TensorList *>(tensor);
-      if (tensorlist->tensors_data_type() == kNumberTypeFloat16) {
-        tensorlist->set_tensors_data_type(kNumberTypeFloat32);
-        for (auto inner_tensor : tensorlist->tensors()) {
-          ret = Float16TensorToFloat32Tensor(inner_tensor);
-          if (ret != RET_OK) {
-            MS_LOG(ERROR) << "Float32TensorToFloat16Tensor failed.";
-            return ret;
-          }
-        }
-      }
-    }
-  }
-
-  int tensor_count = 0;
-  auto in_tensors = this->in_tensors();
-  for (size_t i = 0; i < in_tensors.size(); i++) {
-    auto tensor = in_tensors.at(i);
-    MS_ASSERT(tensor != nullptr);
-    auto real_tensor = tensor;
-    if (tensor->root_tensor() != nullptr) {
-      real_tensor = tensor->root_tensor();
-      if (tensor->data_type() == kNumberTypeFloat16) {
-        tensor->set_data_type(kNumberTypeFloat32);
-      } else if (tensor->data_type() == kObjectTypeTensorType) {
-        auto tensorlist = reinterpret_cast<lite::TensorList *>(tensor);
-        if (tensorlist->tensors_data_type() == kNumberTypeFloat16) {
-          tensorlist->set_tensors_data_type(kNumberTypeFloat32);
-        }
-      }
-    }
-    if (real_tensor->data_type() == kNumberTypeFloat16 &&
-        origin_input_data_.find(real_tensor) != origin_input_data_.end()) {
-      auto origin_tensor_data = origin_input_data_.at(real_tensor);
-      real_tensor->FreeData();
-      MS_ASSERT(origin_tensor_data->data_ != nullptr);
-      real_tensor->set_data(origin_tensor_data->data_);
-      real_tensor->set_own_data(origin_tensor_data->own_data_);
-      real_tensor->set_data_type(kNumberTypeFloat32);
-      origin_tensor_data->data_ = nullptr;
-      tensor_count++;
-    } else if (real_tensor->data_type() == kObjectTypeTensorType) {
-      auto tensorlist = reinterpret_cast<lite::TensorList *>(real_tensor);
-      if (tensorlist->tensors_data_type() == kNumberTypeFloat16) {
-        tensorlist->set_tensors_data_type(kNumberTypeFloat32);
-        for (auto inner_tensor : tensorlist->tensors()) {
-          MS_ASSERT(inner_tensor != nullptr);
-          auto origin_tensor_data = origin_input_data_.at(inner_tensor);
-          inner_tensor->FreeData();
-          MS_ASSERT(origin_tensor_data->data_ != nullptr);
-          inner_tensor->set_data(origin_tensor_data->data_);
-          inner_tensor->set_own_data(origin_tensor_data->own_data_);
-          inner_tensor->set_data_type(kNumberTypeFloat32);
-          origin_tensor_data->data_ = nullptr;
-          tensor_count++;
-        }
-      }
-    }
-  }
-  this->FreeOriginInputData();
-  return RET_OK;
-#else
-  return RET_OK;
-#endif
-}
-#endif
 }  // namespace mindspore::kernel
diff --git a/mindspore/lite/src/sub_graph_kernel.h b/mindspore/lite/src/sub_graph_kernel.h
index 997c07fd477..22d1e3874ac 100644
--- a/mindspore/lite/src/sub_graph_kernel.h
+++ b/mindspore/lite/src/sub_graph_kernel.h
@@ -175,67 +175,7 @@ class CpuFp16SubGraph : public CpuSubGraph {
     return CpuSubGraph::Init();
   }
 
-  int PreProcess();
-  int Execute() override {
-    auto ret = PreProcess();
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel PreProcess failed, name: " << this->name();
-      return ret;
-    }
-    ret = CpuSubGraph::Execute();
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel failed, name: " << this->name();
-      return ret;
-    }
-
-    ret = PostProcess();
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel PreProcess failed, name: " << this->name();
-      return ret;
-    }
-    return lite::RET_OK;
-  }
-  int Execute(const KernelCallBack &before, const KernelCallBack &after) override {
-    auto ret = PreProcess();
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel PreProcess failed, name: " << this->name();
-      return ret;
-    }
-#ifdef Debug
-    for (const auto *node : nodes_) {
-      if (node->type() == schema::PrimitiveType_PartialFusion) {
-        continue;
-      }
-      for (const auto *in_tensor : node->in_tensors()) {
-        if (in_tensor->data_type() == kNumberTypeFloat32) {
-          MS_LOG(ERROR) << "FP16 kernel can not accept float32 input";
-          return lite::RET_ERROR;
-        }
-      }
-    }
-#endif
-    ret = CpuSubGraph::Execute(before, after);
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel failed, name: " << this->name();
-      return ret;
-    }
-
-    ret = PostProcess();
-    if (lite::RET_OK != ret) {
-      MS_LOG(ERROR) << "run kernel PreProcess failed, name: " << this->name();
-      return ret;
-    }
-    return lite::RET_OK;
-  };
-  int PostProcess();
-
  private:
-  void FreeOriginInputData();
-  int Float32TensorToFloat16Tensor(lite::Tensor *tensor);
-  int Float16TensorToFloat32Tensor(lite::Tensor *tensor);
-
- private:
-  std::map<lite::Tensor *, DataStore *> origin_input_data_;
   bool support_fp16_ = false;
 };
 #endif
diff --git a/mindspore/lite/test/config/models_onnx_fp16.cfg b/mindspore/lite/test/config/models_onnx_fp16.cfg
index 8e61999bd95..4c23284359c 100644
--- a/mindspore/lite/test/config/models_onnx_fp16.cfg
+++ b/mindspore/lite/test/config/models_onnx_fp16.cfg
@@ -84,7 +84,7 @@ Q_face_recognition.onnx 3.2
 ml_video_edit_enhance_update_tmp.onnx 0.5
 Q888_face_recognition.onnx 3.5
 Q888_iris_detect.onnx 0.5
-#ssd_mobilenet_v1_10.onnx;1;1,383,640,3 0.5 to open
+ssd_mobilenet_v1_10.onnx;1;1,383,640,3 0.5
 # The output from a conv in the later part contains many minus values, the following leakyRelu makes them become very
 # close to 0 (-e^-4). The fp16 precision lost a lot in this case and it affects the following computation.
 Harmony_Voiceprint.onnx;1;1,200,40,1 21.5 # small output causes big bias
diff --git a/mindspore/lite/test/config/models_tf_fp16.cfg b/mindspore/lite/test/config/models_tf_fp16.cfg
index 9ea326c57e7..cc9fd6c97d2 100644
--- a/mindspore/lite/test/config/models_tf_fp16.cfg
+++ b/mindspore/lite/test/config/models_tf_fp16.cfg
@@ -65,7 +65,7 @@ siteAI_trans_nonlinear134g.pb;1;1,137 0.5
 siteAI_trans_nonlinear134g_nrz.pb;1;1,182 0.6
 ml_vision_guide_detection2.pb;1;1,320,320,1 1
 # ml_tts_encoder.pb has a round op, which will cause round-off error when the decimal of input value is near 0.5
-#ml_tts_encoder.pb;4;1:1,44:1:1 9 to open
+ml_tts_encoder.pb;4;1:1,44:1:1 9
 # encoder_0111_control_flow.pb is same as ml_tts_encoder_control_flow.pb
 #encoder_0111_control_flow.pb;4;1:1,44:1:1 10
 ml_video_edit_video_segment_gauss_adaptis_part2.pb;2 11
@@ -81,8 +81,8 @@ ml_video_edit_oneclick_adaptis.pb;3 6
 ml_female_model_step6_noiseout.pb;66 2
 ml_male_model_step6_noiseout.pb;66 2.5
 ml_tts_encoder_control_flow.pb;4;1:1,22:1:1 1.5
-#ml_tts_decoder_control_flow.pb;5 1 to open
-#ml_tts_decoder.pb;5 2.5 to open
+ml_tts_decoder_control_flow.pb;5 1
+ml_tts_decoder.pb;5 2.5
 ml_tts_vocoder.pb;66 53
 hiai_transformer_encoder.pb;15 4
 decoder_step_nocumsum_v5.pb;13;1:1,512:1,1429,2:1,127:1,127:1,127:1,127,320:1,80:1,512:1,512:1,512:1,512:1,512 1.2