diff --git a/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.cc b/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.cc
new file mode 100644
index 0000000000..d3a06b708c
--- /dev/null
+++ b/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.cc
@@ -0,0 +1,574 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include <vector>
+#include <map>
+#include "tools/converter/legacy_optimizer/graph/switch_pass.h"
+#include "src/common/log_adapter.h"
+#include "include/errorcode.h"
+#include "src/ops/primitive_c.h"
+#include "src/common/utils.h"
+#include "tools/common/graph_util.h"
+
+namespace mindspore::lite {
+
+STATUS SwitchPass::Run(mindspore::schema::MetaGraphT *graph) {
+  MS_ASSERT(graph != nullptr);
+  for (size_t i = 0; i < graph->nodes.size(); i++) {
+    auto &node = graph->nodes.at(i);
+    auto type = node->primitive->value.type;
+    if (type != schema::PrimitiveType_Switch) {
+      continue;
+    }
+
+    SingleSwitchPass pass(graph, i);
+    int ret = pass.Run();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "node: " << node->name << "'s switch pass failed: " << ret;
+      return ret;
+    }
+  }
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::DoubleSwitchOutput() {
+  origin_switch_output_tensor_indices_ = switch_node_->outputIndex;
+  MS_ASSERT(origin_switch_output_tensor_indices_.size() == cond_partial_node_->inputIndex.szie());
+  for (size_t i = 0; i < origin_switch_output_tensor_indices_.size(); i++) {
+    auto &switch_out_tensor = graph_->allTensors.at(origin_switch_output_tensor_indices_[i]);
+    const auto &cond_partial_input_tensor = graph_->allTensors.at(cond_partial_node_->inputIndex[i]);
+    switch_out_tensor->dataType = cond_partial_input_tensor->dataType;
+    auto tensor = NewTensor(switch_out_tensor);
+    graph_->allTensors.push_back(std::move(tensor));
+    switch_node_->outputIndex.push_back(graph_->allTensors.size() - 1);
+    graph_->subGraph.at(this_subgraph_index_)->tensorIndices.push_back(graph_->allTensors.size() - 1);
+  }
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::UpdateSwitchUser() {
+  std::vector<CNodeT *> switch_users;
+  for (auto &node_idx : graph_->subGraph.at(this_subgraph_index_)->nodeIndices) {
+    auto &node = graph_->nodes.at(node_idx);
+    for (auto &idx : node->inputIndex) {
+      auto iter = std::find(switch_node_->outputIndex.begin(), switch_node_->outputIndex.end(), idx);
+      if (iter != switch_node_->outputIndex.end()) {
+        switch_users.push_back(node.get());
+        int pos = iter - switch_node_->outputIndex.begin();
+        idx = switch_node_->outputIndex.at(pos + switch_node_->outputIndex.size() / 2);
+      }
+    }
+  }
+  return RET_OK;
+}
+
+bool SingleSwitchPass::IsLoop() {
+  for (auto &node : body_graph_nodes_) {
+    if (node->primitive->value.type == schema::PrimitiveType_Partial &&
+        node->primitive->value.AsPartial()->subGraphIndex == cond_subgraph_index_) {
+      body_to_cond_partial_node_ = node;
+      return true;
+    }
+  }
+  return false;
+}
+
+std::unique_ptr<schema::TensorT> SingleSwitchPass::NewTensor(const std::unique_ptr<schema::TensorT> &in_tensor) {
+  auto out_tensor = std::make_unique<schema::TensorT>();
+  out_tensor->nodeType = in_tensor->nodeType;
+  out_tensor->dims = in_tensor->dims;
+  out_tensor->dataType = in_tensor->dataType;
+  out_tensor->data = in_tensor->data;
+  out_tensor->format = in_tensor->format;
+  return out_tensor;
+}
+
+STATUS SingleSwitchPass::MoveMaxIterationToCond() {
+  auto &body_subgraph_input = graph_->subGraph.at(body_subgraph_index_)->inputIndices;
+  for (auto it = body_subgraph_input.begin(); it != body_subgraph_input.end();) {
+    if (!body_to_cond_partial_node_->inputIndex.empty() && IsContain(body_to_cond_partial_node_->inputIndex, *it)) {
+      int32_t max_iteration_idx = it - body_subgraph_input.begin();
+      // get maxiteration tensor
+      auto &max_iteration_tensor = graph_->allTensors.at(cond_partial_node_->inputIndex.at(max_iteration_idx));
+      auto all_tensor_idx = std::find(graph_->allTensors.begin(), graph_->allTensors.end(), max_iteration_tensor) -
+                            graph_->allTensors.begin();
+
+      // remove maxiteration from body_to_cond partial node
+      body_to_cond_partial_node_->inputIndex.erase(body_to_cond_partial_node_->inputIndex.begin() + max_iteration_idx);
+
+      // concat body subgraph tensor to max iteration in all tensor
+      auto body_max_iteration_tensor_idx = body_subgraph_input.at(max_iteration_idx);
+      for (auto &node : cond_graph_nodes_) {
+        std::replace_if(
+          node->inputIndex.begin(), node->inputIndex.end(),
+          [&body_max_iteration_tensor_idx](uint32_t idx) { return idx == body_max_iteration_tensor_idx; },
+          all_tensor_idx);
+      }
+
+      // remove maxiteration from body partial input and body func input
+      body_partial_node_->inputIndex.erase(body_partial_node_->inputIndex.begin() + max_iteration_idx);
+      it = body_subgraph_input.erase(it);
+    } else {
+      it++;
+    }
+  }
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::InsertMerge() {
+  int ret = RET_OK;
+  auto merge_node = std::unique_ptr<CNodeT>(new (std::nothrow) CNodeT);
+  MS_ASSERT(merge_node != nullptr);
+  auto primitiveT = std::unique_ptr<PrimitiveT>(new (std::nothrow) PrimitiveT);
+  MS_ASSERT(primitiveT != nullptr);
+  merge_node->primitive = std::move(primitiveT);
+
+  static int id = 0;
+  merge_node->name = "Merge-" + std::to_string(id++);
+  merge_node->primitive->value.type = schema::PrimitiveType_Merge;
+  std::unique_ptr<MergeT> merge_param(new (std::nothrow) MergeT());
+  MS_ASSERT(merge_param != nullptr);
+  merge_node->primitive->value.value = merge_param.release();
+
+  merge_node->inputIndex.assign(cond_partial_node_->inputIndex.begin(), cond_partial_node_->inputIndex.end());
+
+  // merge node output is same as switch
+  for (auto &out_index : origin_switch_output_tensor_indices_) {
+    auto &switch_out_tensor = graph_->allTensors.at(out_index);
+    auto tensor = NewTensor(switch_out_tensor);
+    graph_->allTensors.push_back(std::move(tensor));
+    merge_node->outputIndex.push_back(graph_->allTensors.size() - 1);
+  }
+
+  // double merge inputs to contain the outputs of body node
+  for (auto &out_index : origin_switch_output_tensor_indices_) {
+    auto &switch_out_tensor = graph_->allTensors.at(out_index);
+    auto tensor = NewTensor(switch_out_tensor);
+    graph_->allTensors.push_back(std::move(tensor));
+    merge_node->inputIndex.push_back(graph_->allTensors.size() - 1);
+  }
+
+  // insert merge node before the cond graph
+  std::map<int, int> cond_input_update_map{};
+  for (size_t i = 0; i < cond_partial_node_->inputIndex.size(); i++) {
+    cond_input_update_map.insert(std::make_pair(cond_partial_node_->inputIndex.at(i), merge_node->outputIndex.at(i)));
+  }
+  for (auto &node : cond_graph_nodes_) {
+    for (auto &input_idx : node->inputIndex) {
+      if (cond_input_update_map.find(input_idx) != cond_input_update_map.end()) {
+        input_idx = cond_input_update_map.at(input_idx);
+      }
+    }
+  }
+
+  // update cond node input to be consistent with cond graph input
+  cond_partial_node_->inputIndex.assign(merge_node->outputIndex.begin(), merge_node->outputIndex.end());
+
+  // insert switch after cond node and merge node
+  auto cond_input = switch_node_->inputIndex.front();
+  switch_node_->inputIndex.clear();
+  switch_node_->inputIndex.push_back(cond_input);
+  switch_node_->inputIndex.insert(switch_node_->inputIndex.end(), merge_node->outputIndex.begin(),
+                                  merge_node->outputIndex.end());
+
+  // move body node to switch node output
+  body_partial_node_->inputIndex.clear();
+  body_partial_node_->inputIndex.assign(switch_node_->outputIndex.begin(),
+                                        switch_node_->outputIndex.begin() + switch_node_->outputIndex.size() / 2);
+
+  // concat body output to merge input
+  body_partial_node_->outputIndex.assign(merge_node->inputIndex.begin() + merge_node->inputIndex.size() / 2,
+                                         merge_node->inputIndex.end());
+
+  graph_->nodes.push_back(std::move(merge_node));
+  graph_->subGraph.at(this_subgraph_index_)->nodeIndices.push_back(graph_->nodes.size() - 1);
+
+  // update bodu graph output
+  graph_->subGraph.at(body_subgraph_index_)
+    ->outputIndices.assign(body_to_cond_partial_node_->inputIndex.begin(),
+                           body_to_cond_partial_node_->inputIndex.end());
+
+  // erase body_to_cond_partial_node_
+  RemoveUselessNode(body_to_cond_partial_node_, graph_);
+  return ret;
+}
+
+void SingleSwitchPass::RemoveUselessNode(schema::CNodeT *partial_node, schema::MetaGraphT *graph) {
+  partial_node->inputIndex.clear();
+  partial_node->outputIndex.clear();
+
+  int pos = -1;
+  for (size_t i = 0; i < graph->nodes.size(); ++i) {
+    if (graph->nodes.at(i).get() == partial_node) {
+      pos = i;
+      break;
+    }
+  }
+
+  if (pos == -1) {
+    return;
+  }
+
+  graph->nodes.erase(graph->nodes.begin() + pos);
+
+  for (auto &subgraph : graph->subGraph) {
+    for (auto it = subgraph->nodeIndices.begin(); it != subgraph->nodeIndices.end();) {
+      if (*it == static_cast<uint32_t>(pos)) {
+        it = subgraph->nodeIndices.erase(it);
+      } else {
+        if (*it > static_cast<uint32_t>(pos)) {
+          (*it)--;
+        }
+        it++;
+      }
+    }
+  }
+}
+
+size_t SingleSwitchPass::InitThisGraphIndex() {
+  for (size_t i = 0; i < graph_->subGraph.size(); i++) {
+    if (std::any_of(graph_->subGraph.at(i)->nodeIndices.begin(), graph_->subGraph.at(i)->nodeIndices.end(),
+                    [this](const uint32_t &idx) { return idx == this->switch_node_index_; })) {
+      return i;
+    }
+  }
+  return -1;
+}
+
+STATUS SingleSwitchPass::Init() {
+  if (graph_ == nullptr) {
+    MS_LOG(ERROR) << "graph is nullptr.";
+    return RET_NULL_PTR;
+  }
+
+  this_subgraph_index_ = InitThisGraphIndex();
+  if (this_subgraph_index_ < 0) {
+    MS_LOG(ERROR) << "init this subgraph index failed.";
+    return RET_ERROR;
+  }
+
+  switch_node_ = graph_->nodes.at(switch_node_index_).get();
+  if (switch_node_ == nullptr) {
+    MS_LOG(ERROR) << "switch node is nullptr.";
+    return RET_NULL_PTR;
+  }
+
+  if (switch_node_->inputIndex.size() == kSwitchMinInputSize) {
+    return RET_OK;
+  }
+
+  if (switch_node_->inputIndex.size() < kSwitchMinInputSize) {
+    MS_LOG(ERROR) << "switch node: " << switch_node_->name
+                  << " 's input size is not right, size: " << switch_node_->inputIndex.size();
+    return RET_INPUT_PARAM_INVALID;
+  }
+
+  // get cond_partial_node_ and body_partial_node_
+  bool find_cond_node = false;
+  bool find_body_node = false;
+  for (auto iter = graph_->nodes.begin(); iter < graph_->nodes.end(); iter++) {
+    for (auto &out_index : iter->get()->outputIndex) {
+      if (out_index == switch_node_->inputIndex[kSwitchCondIndex]) {
+        cond_partial_node_ = iter->get();
+        cond_node_index_ = iter - graph_->nodes.begin();
+        find_cond_node = true;
+      }
+      if (out_index == switch_node_->inputIndex[kSwitchBodyIndex]) {
+        body_partial_node_ = iter->get();
+        body_node_index_ = iter - graph_->nodes.begin();
+        find_body_node = true;
+      }
+    }
+    if (find_body_node && find_cond_node) {
+      break;
+    }
+  }
+
+  if (cond_partial_node_->primitive->value.type != PrimitiveType_Partial ||
+      body_partial_node_->primitive->value.type != PrimitiveType_Partial) {
+    return RET_OK;
+  }
+  // get cond_graph_nodes_
+  cond_subgraph_index_ = cond_partial_node_->primitive->value.AsPartial()->subGraphIndex;
+  auto cond_node_indices = graph_->subGraph.at(cond_subgraph_index_)->nodeIndices;
+  for (auto &index : cond_node_indices) {
+    cond_graph_nodes_.push_back(graph_->nodes.at(index).get());
+  }
+
+  // get body_graph_nodes_
+  body_subgraph_index_ = body_partial_node_->primitive->value.AsPartial()->subGraphIndex;
+  auto body_node_indices = graph_->subGraph.at(body_subgraph_index_)->nodeIndices;
+  for (auto &index : body_node_indices) {
+    body_graph_nodes_.push_back(graph_->nodes.at(index).get());
+  }
+
+  // get this_graph_nodes_
+  auto this_node_indices = graph_->subGraph.at(this_subgraph_index_)->nodeIndices;
+  for (auto &index : this_node_indices) {
+    this_graph_nodes_.push_back(graph_->nodes.at(index).get());
+  }
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::UpdateSubgraphInput(const size_t &subgraph_index, schema::CNodeT *partial_node,
+                                             const std::vector<schema::CNodeT *> &subgraph_nodes) {
+  if (partial_node == nullptr || subgraph_nodes.empty()) {
+    MS_LOG(ERROR) << "partial_node is nullptr or subgraph_nodes are empty.";
+    return RET_INPUT_PARAM_INVALID;
+  }
+  auto &partial_inputs = partial_node->inputIndex;
+  auto &subgraph_inputs = graph_->subGraph.at(subgraph_index)->inputIndices;
+
+  std::map<int, int> subgraph_input_map;
+  std::vector<int> new_subgraph_inputs{};
+  for (unsigned int &subgraph_input : subgraph_inputs) {
+    auto &tensor = graph_->allTensors.at(subgraph_input);
+    // get parameter input index k. subgraph name + “_input_" + "k"
+    char k = tensor->name[graph_->subGraph.at(subgraph_index)->name.size() + 7];
+    int partial_idx = k - '0';
+    subgraph_input_map.insert(std::pair<int, int>{subgraph_input, partial_inputs[partial_idx]});
+    new_subgraph_inputs.push_back(partial_inputs[partial_idx]);
+  }
+
+  for (auto &subgraph_node : subgraph_nodes) {
+    for (auto &input : subgraph_node->inputIndex) {
+      if (subgraph_input_map.find(input) != subgraph_input_map.end()) {
+        input = subgraph_input_map.at(input);
+      }
+    }
+  }
+  subgraph_inputs.assign(new_subgraph_inputs.begin(), new_subgraph_inputs.end());
+
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::UpdateSubgraphOutput(const size_t &subgraph_index, schema::CNodeT *partial_node,
+                                              const std::vector<schema::CNodeT *> &subgraph_nodes) {
+  if (partial_node == nullptr || subgraph_nodes.empty()) {
+    MS_LOG(ERROR) << "partial_node is nullptr or subgraph_nodes are empty.";
+    return RET_INPUT_PARAM_INVALID;
+  }
+  auto &partial_outputs = partial_node->outputIndex;
+  auto &subgraph_outputs = graph_->subGraph.at(subgraph_index)->outputIndices;
+
+  std::map<int, int> subgraph_output_map;
+  std::vector<int> new_subgraph_outputs{};
+  for (unsigned int &subgraph_output : subgraph_outputs) {
+    auto &tensor = graph_->allTensors.at(subgraph_output);
+    // get parameter input index k. subgraph name + “_output_" + "k"
+    char k = tensor->name[graph_->subGraph.at(subgraph_index)->name.size() + 8];
+    int partial_idx = k - '0';
+    subgraph_output_map.insert(std::pair<int, int>{subgraph_output, partial_outputs[partial_idx]});
+    new_subgraph_outputs.push_back(partial_outputs[partial_idx]);
+  }
+
+  for (auto &subgraph_node : subgraph_nodes) {
+    for (auto &output : subgraph_node->outputIndex) {
+      if (subgraph_output_map.find(output) != subgraph_output_map.end()) {
+        output = subgraph_output_map.at(output);
+      }
+    }
+  }
+  subgraph_outputs.assign(new_subgraph_outputs.begin(), new_subgraph_outputs.end());
+
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::ConcatCondSubgraphInputAndOutput() {
+  int ret = UpdateSubgraphInput(cond_subgraph_index_, cond_partial_node_, cond_graph_nodes_);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init failed, ret: " << ret;
+    return ret;
+  }
+  ret = UpdateSubgraphOutput(cond_subgraph_index_, cond_partial_node_, cond_graph_nodes_);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init failed, ret: " << ret;
+    return ret;
+  }
+
+  return ret;
+}
+
+STATUS SingleSwitchPass::ConcatBodySubgraphInputAndOutput() {
+  int ret = UpdateSubgraphInput(body_subgraph_index_, body_partial_node_, body_graph_nodes_);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "UpdateSubgraphInput failed, ret: " << ret;
+    return ret;
+  }
+  ret = UpdateSubgraphOutput(body_subgraph_index_, body_partial_node_, body_graph_nodes_);
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "UpdateSubgraphOutput failed, ret: " << ret;
+    return ret;
+  }
+  return ret;
+}
+
+STATUS SingleSwitchPass::ConvertSwitchToSelect() {
+  MS_ASSERT(switch_node_->inputIndex.size() >= 3);
+  MS_ASSERT(switch_node_->inputIndex.size() % 2 != 0);
+  MS_ASSERT(switch_node_->outputIndex.size() * 2 + 1 == switch_node_->inputIndex.size());
+  auto bool_index = switch_node_->inputIndex.front();
+
+  // insert switch node1
+  auto switch_node1 = std::make_unique<CNodeT>();
+  switch_node1->name = switch_node_->name + "-Switch-1";
+  switch_node1->primitive = std::make_unique<PrimitiveT>();
+  switch_node1->primitive->value.type = PrimitiveType_Switch;
+  switch_node1->primitive->value.value = new (std::nothrow) SwitchT();
+  switch_node1->inputIndex = {bool_index};
+  std::vector<int> part_one_input_index(
+    switch_node_->inputIndex.begin() + 1,
+    switch_node_->inputIndex.begin() + 1 + (switch_node_->inputIndex.size() - 1) / 2);
+  switch_node1->inputIndex.insert(switch_node1->inputIndex.end(), part_one_input_index.begin(),
+                                  part_one_input_index.end());
+  std::vector<std::unique_ptr<TensorT>> switch_output_tensors1(part_one_input_index.size() * 2);
+  std::vector<int> switch_output_indexes1(part_one_input_index.size() * 2);
+  int i = 0;
+  for (const auto &input_index : part_one_input_index) {
+    auto &switch_in_tensor = graph_->allTensors.at(input_index);
+    auto tensor1 = NewTensor(switch_in_tensor);
+    auto tensor2 = NewTensor(switch_in_tensor);
+    switch_output_tensors1[i] = std::move(tensor1);
+    switch_output_tensors1[part_one_input_index.size() + i] = std::move(tensor2);
+    switch_output_indexes1[i] = graph_->allTensors.size() - 1 + i;
+    switch_output_indexes1[part_one_input_index.size() + i] =
+      graph_->allTensors.size() - 1 + i + part_one_input_index.size();
+    i++;
+  }
+  for (auto &tensor : switch_output_tensors1) {
+    graph_->allTensors.emplace_back(std::move(tensor));
+  }
+  switch_node1->outputIndex.insert(switch_node1->outputIndex.begin(), switch_output_indexes1.begin(),
+                                   switch_output_indexes1.end());
+
+  // insert switch node2
+  auto switch_node2 = std::make_unique<CNodeT>();
+  switch_node2->name = switch_node_->name + "-Switch-1";
+  switch_node2->primitive = std::make_unique<PrimitiveT>();
+  switch_node2->primitive->value.type = PrimitiveType_Switch;
+  switch_node2->primitive->value.value = new (std::nothrow) SwitchT();
+  switch_node2->inputIndex = {bool_index};
+
+  std::vector<int> part_two_input_index(
+    switch_node_->inputIndex.begin() + 1 + (switch_node_->inputIndex.size() - 1) / 2, switch_node_->inputIndex.end());
+  switch_node2->inputIndex.insert(switch_node2->inputIndex.end(), part_two_input_index.begin(),
+                                  part_two_input_index.end());
+  std::vector<std::unique_ptr<TensorT>> switch_output_tensors2(part_two_input_index.size() * 2);
+  std::vector<int> switch_output_indexes2(part_two_input_index.size() * 2);
+  i = 0;
+  for (const auto &input_index : part_two_input_index) {
+    auto &switch_in_tensor = graph_->allTensors.at(input_index);
+    auto tensor1 = NewTensor(switch_in_tensor);
+    auto tensor2 = NewTensor(switch_in_tensor);
+    switch_output_tensors2[i] = std::move(tensor1);
+    switch_output_tensors2[part_two_input_index.size() + i] = std::move(tensor2);
+    switch_output_indexes2[i] = graph_->allTensors.size() - 1 + i;
+    switch_output_indexes2[part_two_input_index.size() + i] =
+      graph_->allTensors.size() - 1 + i + part_two_input_index.size();
+    i++;
+  }
+  for (auto &tensor : switch_output_tensors2) {
+    graph_->allTensors.emplace_back(std::move(tensor));
+  }
+  switch_node2->outputIndex.insert(switch_node2->outputIndex.begin(), switch_output_indexes2.begin(),
+                                   switch_output_indexes2.end());
+
+  // insert merge
+  auto merge_node = std::make_unique<CNodeT>();
+  merge_node->name = switch_node_->name + "-Merge";
+  merge_node->primitive = std::make_unique<PrimitiveT>();
+  merge_node->primitive->value.type = PrimitiveType_Merge;
+  merge_node->primitive->value.value = new (std::nothrow) MergeT();
+
+  std::vector<int> merge_input_indexes(switch_node_->outputIndex.size() * 2);
+  for (i = 0; i < switch_node_->outputIndex.size(); i++) {
+    merge_input_indexes[i] = switch_output_indexes1[i];
+    merge_input_indexes[i + switch_node_->outputIndex.size()] =
+      switch_output_indexes2[i + switch_node_->outputIndex.size()];
+    merge_node->outputIndex.emplace_back(switch_node_->outputIndex.at(i));
+  }
+  merge_node->inputIndex.insert(merge_node->inputIndex.end(), merge_input_indexes.begin(), merge_input_indexes.end());
+  graph_->nodes.emplace_back(std::move(switch_node1));
+  graph_->subGraph.at(this_subgraph_index_)->nodeIndices.push_back(graph_->nodes.size() - 1);
+  graph_->nodes.emplace_back(std::move(switch_node2));
+  graph_->subGraph.at(this_subgraph_index_)->nodeIndices.push_back(graph_->nodes.size() - 1);
+  graph_->nodes.emplace_back(std::move(merge_node));
+  graph_->subGraph.at(this_subgraph_index_)->nodeIndices.push_back(graph_->nodes.size() - 1);
+
+  RemoveUselessNode(switch_node_, graph_);
+  return RET_OK;
+}
+
+STATUS SingleSwitchPass::Run() {
+  int ret = Init();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "Init failed, ret: " << ret;
+    return ret;
+  }
+
+  if (switch_node_->inputIndex.size() == kSwitchMinInputSize) {
+    return RET_OK;
+  }
+
+  if (cond_partial_node_->primitive->value.type != PrimitiveType_Partial ||
+      body_partial_node_->primitive->value.type != PrimitiveType_Partial) {
+    ret = ConvertSwitchToSelect();
+    return ret;
+  }
+
+  if (IsLoop()) {
+    ret = MoveMaxIterationToCond();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "MoveMaxIterationToCond failed, ret: " << ret;
+      return ret;
+    }
+  }
+
+  ret = DoubleSwitchOutput();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "DoubleSwitchOutput failed, ret: " << ret;
+    return ret;
+  }
+
+  ret = UpdateSwitchUser();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "UpdateOriginSwitchOutput failed, ret: " << ret;
+    return ret;
+  }
+
+  if (IsLoop()) {
+    ret = InsertMerge();
+    if (ret != RET_OK) {
+      MS_LOG(ERROR) << "InsertMerge failed, ret: " << ret;
+      return ret;
+    }
+  }
+
+  ret = ConcatCondSubgraphInputAndOutput();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "ConcatCondSubgraphInputAndOutput failed, ret: " << ret;
+    return ret;
+  }
+
+  ret = ConcatBodySubgraphInputAndOutput();
+  if (ret != RET_OK) {
+    MS_LOG(ERROR) << "ConcatBodySubgraphInputAndOutput failed, ret: " << ret;
+    return ret;
+  }
+
+  return RET_OK;
+}
+}  // namespace mindspore::lite
diff --git a/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.h b/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.h
new file mode 100644
index 0000000000..c349e49809
--- /dev/null
+++ b/mindspore/lite/tools/converter/legacy_optimizer/graph/switch_pass.h
@@ -0,0 +1,85 @@
+/**
+ * Copyright 2020 Huawei Technologies Co., Ltd
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#ifndef MINDSPORE_PREDICT_SWITCH_PASS_H
+#define MINDSPORE_PREDICT_SWITCH_PASS_H
+#include <unordered_map>
+#include <memory>
+#include <string>
+#include <utility>
+#include <vector>
+#include "tools/common/graph_util.h"
+#include "tools/converter/optimizer.h"
+
+using mindspore::schema::TensorT;
+namespace mindspore {
+namespace lite {
+class SwitchPass : public GraphPass {
+ public:
+  SwitchPass() = default;
+  ~SwitchPass() override = default;
+  STATUS Run(schema::MetaGraphT *graph) override;
+};
+
+class SingleSwitchPass {
+ public:
+  SingleSwitchPass(schema::MetaGraphT *graph, const size_t &node_index)
+      : graph_(graph), switch_node_index_(node_index) {}
+  ~SingleSwitchPass() = default;
+  STATUS Run();
+
+ private:
+  STATUS Init();
+  size_t InitThisGraphIndex();
+  STATUS DoubleSwitchOutput();
+  STATUS MoveMaxIterationToCond();
+  STATUS UpdateSwitchUser();
+  STATUS ConcatCondSubgraphInputAndOutput();
+  STATUS ConcatBodySubgraphInputAndOutput();
+  STATUS ConvertSwitchToSelect();
+  bool IsLoop();
+  STATUS InsertMerge();
+  STATUS UpdateSubgraphInput(const size_t &subgraph_index, schema::CNodeT *partial_node,
+                             const std::vector<schema::CNodeT *> &subgraph_nodes);
+  STATUS UpdateSubgraphOutput(const size_t &subgraph_index, schema::CNodeT *partial_node,
+                              const std::vector<schema::CNodeT *> &subgraph_nodes);
+  std::unique_ptr<schema::TensorT> NewTensor(const std::unique_ptr<schema::TensorT> &in_tensor);
+  void RemoveUselessNode(schema::CNodeT *partial_node, schema::MetaGraphT *graph);
+
+  const size_t kSwitchCondIndex = 0;
+  const size_t kSwitchBodyIndex = 1;
+  const size_t kSwitchMinInputSize = 2;
+
+  schema::MetaGraphT *graph_ = nullptr;
+  schema::CNodeT *switch_node_ = nullptr;
+  schema::CNodeT *cond_partial_node_ = nullptr;
+  schema::CNodeT *body_partial_node_ = nullptr;
+  schema::CNodeT *body_to_cond_partial_node_ = nullptr;
+  std::vector<schema::CNodeT *> this_graph_nodes_;
+  std::vector<schema::CNodeT *> body_graph_nodes_;
+  std::vector<schema::CNodeT *> cond_graph_nodes_;
+  std::vector<schema::CNodeT *> switch_users_;
+  size_t switch_node_index_ = -1;
+  size_t cond_node_index_ = -1;
+  size_t body_node_index_ = -1;
+  int32_t this_subgraph_index_ = -1;
+  int32_t cond_subgraph_index_ = -1;
+  int32_t body_subgraph_index_ = -1;
+  std::vector<uint32_t> origin_switch_output_tensor_indices_;
+};
+}  // namespace lite
+}  // namespace mindspore
+#endif