/**
 * Copyright 2021 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 "infer_base_pass.h"
#include "common/ge/ge_util.h"
#include "common/util/error_manager/error_manager.h"
#include "framework/common/debug/ge_log.h"
#include "framework/common/util.h"
#include "graph/debug/ge_attr_define.h"
#include "graph/debug/ge_util.h"
#include "graph/utils/graph_utils.h"
#include "graph/utils/node_utils.h"
#include "graph/utils/tensor_utils.h"
#include "graph/utils/type_utils.h"

namespace ge {
namespace {
string Serial(const vector<int64_t> &dims) {
  string serial_string;
  serial_string += "[";
  for (int64_t dim : dims) {
    serial_string += std::to_string(dim) + " ";
  }
  serial_string += "]";
  return serial_string;
}
void SerialShapeRange(const GeTensorDescPtr &desc, std::string &desc_str) {
  desc_str += "[";
  std::vector<std::pair<int64_t, int64_t>> shape_range;
  (void)desc->GetShapeRange(shape_range);
  for (const auto &pair : shape_range) {
    desc_str += "{";
    desc_str += std::to_string(pair.first) + "," + std::to_string(pair.second);
    desc_str += "},";
  }
  desc_str += "]";
  shape_range.clear();
  (void)desc->GetOriginShapeRange(shape_range);
  for (const auto &pair : shape_range) {
    desc_str += ",{";
    desc_str += std::to_string(pair.first) + "," + std::to_string(pair.second);
    desc_str += "},";
  }
}
void SerialValueRange(const GeTensorDescPtr &desc, std::string &desc_str) {
  desc_str += "[";
  std::vector<std::pair<int64_t, int64_t>> value_range;
  (void)desc->GetValueRange(value_range);
  for (const auto &pair : value_range) {
    desc_str += "{";
    desc_str += std::to_string(pair.first) + "," + std::to_string(pair.second);
    desc_str += "},";
  }
  desc_str += "]";
}
graphStatus FindSubgraphDataAndNetoutput(const ComputeGraphPtr &sub_graph, NodePtr &netoutput, const ConstNodePtr &node,
                                         std::vector<std::vector<GeTensorDesc>> &ref_data_tensors) {
  auto sub_nodes = sub_graph->GetDirectNode();
  for (size_t i = sub_nodes.size(); i > 0; --i) {
    auto sub_node = sub_nodes.at(i - 1);
    if (sub_node->GetType() == NETOUTPUT) {
      netoutput = sub_node;
    }
    if (sub_node->GetType() == DATA) {
      if (sub_node->GetOpDesc() == nullptr) {
        return GRAPH_FAILED;
      }

      int ref_i;
      if (!AttrUtils::GetInt(sub_node->GetOpDesc(), ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
        REPORT_INNER_ERROR("E19999", "subgraph data node[%s] has no parent node!", sub_node->GetName().c_str());
        GELOGE(GRAPH_FAILED, "[Get][Int] subgraph data node[%s] has no parent node!", sub_node->GetName().c_str());
        return GRAPH_FAILED;
      }
      if (ref_i < 0 || static_cast<uint32_t>(ref_i) >= node->GetAllInDataAnchorsSize()) {
        REPORT_INNER_ERROR("E19999", "data node[%s]'s ref index[%d] is not in range [0, %u)!",
                           sub_node->GetName().c_str(), ref_i, node->GetAllInDataAnchorsSize());
        GELOGE(GRAPH_FAILED, "[Check][Param] data node[%s]'s ref index[%d] is not in range [0, %u)!",
               sub_node->GetName().c_str(), ref_i, node->GetAllInDataAnchorsSize());
        return GRAPH_FAILED;
      }
      ref_data_tensors[ref_i].emplace_back(sub_node->GetOpDesc()->GetOutputDesc(0));
    }
  }
  return GRAPH_SUCCESS;
}
}  // namespace

Status InferBasePass::Run(NodePtr &node) {
  GE_CHECK_NOTNULL(node);
  GE_CHECK_NOTNULL(node->GetOpDesc());

  bool need_infer = NeedInfer(node);
  if (!need_infer) {
    GELOGD("Node %s does not need to infer.", node->GetName().c_str());
    return SUCCESS;
  }

  std::set<NodePtr> changed_nodes;
  auto ret = InferAndUpdate(node, !OptionExists(kOptimizeAfterSubGraph), changed_nodes);
  if (ret != GRAPH_SUCCESS) {
    (void)AnalyzeFailedInfo(node);
    return GE_GRAPH_INFERSHAPE_FAILED;
  }

  /*
   * we will use changed nodes to do repass for control_ops.
   * AddChangedNodesImmediateRepass(changed_nodes);
   */
  auto status = DoRepassForLoopNode(node);
  if (status != SUCCESS) {
    GELOGE(GE_GRAPH_INFERSHAPE_FAILED, "repass failed. node: %s", node->GetName().c_str());
    return GE_GRAPH_INFERSHAPE_FAILED;
  }
  return SUCCESS;
}

bool InferBasePass::NeedInfer(const NodePtr &node) { return true; }
void InferBasePass::AnalyzeFailedInfo(const NodePtr &node) { /* Analyze and select failed info*/ }
Status InferBasePass::DoRepassForLoopNode(NodePtr &node) { return SUCCESS; }
graphStatus InferBasePass::UpdatePeerInputs(NodePtr &node) { return GRAPH_SUCCESS; }
void InferBasePass::AddChangedNodesImmediateRepass(std::set<NodePtr> &changed_nodes) {
  for (const auto &node_ele : changed_nodes) {
    AddImmediateRePassNode(node_ele);
  }
}

graphStatus InferBasePass::InferAndUpdate(NodePtr &node, bool before_subgraph, std::set<NodePtr> &changed_nodes) {
  auto ret = GRAPH_SUCCESS;
  bool is_unknown_graph = node->GetOwnerComputeGraph()->GetGraphUnknownFlag();
  auto opdesc = node->GetOpDesc();
  // some op can not infershape twice such as aipp
  bool need_update_input = !is_unknown_graph && !opdesc->HasAttr("has_infered_verified");
  if (need_update_input) {
    ret = UpdateCurOpInputDesc(node);
    if (ret != GRAPH_SUCCESS) {
      REPORT_CALL_ERROR("E19999", "update op input_desc failed! ret:%d, node:%s", ret, node->GetName().c_str());
      GELOGE(GRAPH_FAILED, "[Update][OpInputDesc] failed! ret:%d", ret);
      return ret;
    }
  }

  bool contain_subgraph = ContainsSubgraph(node);
  if (contain_subgraph && before_subgraph) {
    ret = UpdateTensorDescToSubgraphData(node, changed_nodes);
    if (ret != GRAPH_SUCCESS) {
      return ret;
    }
  }
  ret = Infer(node);
  if (ret != GRAPH_SUCCESS) {
    return ret;
  }
  if (contain_subgraph && !before_subgraph) {
    ret = UpdateTensorDescToParentNode(node, changed_nodes);
    if (ret != GRAPH_SUCCESS) {
      return ret;
    }
  }

  ret = UpdatePeerInputs(node);
  return ret;
}

graphStatus InferBasePass::UpdateCurOpInputDesc(const NodePtr &node_ptr) {
  for (const auto &in_anchor : node_ptr->GetAllInDataAnchors()) {
    auto in_idx = in_anchor->GetIdx();
    auto peer_out_data_anchor = in_anchor->GetPeerOutAnchor();
    if (peer_out_data_anchor == nullptr) {
      continue;
    }
    auto peer_out_data_node = peer_out_data_anchor->GetOwnerNode();
    if (peer_out_data_node == nullptr || peer_out_data_node->GetOpDesc() == nullptr) {
      continue;
    }
    int peer_out_idx = peer_out_data_anchor->GetIdx();
    auto peer_out_desc = peer_out_data_node->GetOpDesc()->MutableOutputDesc(static_cast<uint32_t>(peer_out_idx));

    // check shape and dtype continuity. do not stop process
    auto in_desc = node_ptr->GetOpDesc()->MutableInputDesc(static_cast<uint32_t>(in_idx));
    if (in_desc == nullptr) {
      continue;
    }
    auto in_shape = in_desc->MutableShape().GetDims();
    auto in_dtype = in_desc->GetDataType();
    auto peer_out_shape = peer_out_desc->MutableShape().GetDims();
    auto peer_out_dtype = peer_out_desc->GetDataType();
    if (peer_out_dtype != in_dtype) {
      GELOGW(
        "current node [%s] [%d]\'th in_dtype is [%s].peer output node [%s] [%d]\'th "
        "output_dtype is [%s].The two dtype should be same! Please check graph and fix it",
        node_ptr->GetName().c_str(), in_idx, TypeUtils::DataTypeToSerialString(in_dtype).c_str(),
        peer_out_data_node->GetName().c_str(), peer_out_idx, TypeUtils::DataTypeToSerialString(peer_out_dtype).c_str());
    } else if ((!in_shape.empty()) && (in_shape != peer_out_shape)) {
      string in_shape_str = Serial(in_shape);
      string peer_out_shape_str = Serial(peer_out_shape);
      GELOGW(
        "current node [%s] [%d]\'th in_shape is [%s].peer output node [%s] [%d]\'th "
        "output_shape is [%s].The two shape should be same! Please check graph and fix it",
        node_ptr->GetName().c_str(), in_idx, in_shape_str.c_str(), peer_out_data_node->GetName().c_str(), peer_out_idx,
        peer_out_shape_str.c_str());
    }
    // refresh current node input desc
    bool output_changed = false;
    (void)UpdateInputDescAttr(peer_out_desc, in_desc, output_changed);
  }
  return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateInputDescAttr(const GeTensorDescPtr &src, GeTensorDescPtr &dst, bool &changed) {
  changed = false;
  return GRAPH_SUCCESS;
}

bool InferBasePass::ContainsSubgraph(const NodePtr &node) {
  auto op_desc = node->GetOpDesc();
  auto sub_graph_names = op_desc->GetSubgraphInstanceNames();
  if (sub_graph_names.empty()) {
    return false;
  }

  auto root_graph = GraphUtils::FindRootGraph(node->GetOwnerComputeGraph());
  if (root_graph == nullptr) {
    return false;
  }
  for (const auto &name : sub_graph_names) {
    if (name.empty()) {
      continue;
    }
    auto sub_graph = root_graph->GetSubgraph(name);
    if (sub_graph != nullptr) {
      return true;
    }
  }
  return false;
}

std::vector<ComputeGraphPtr> InferBasePass::GetCurNodeSubgraphs(const NodePtr &node) {
  std::vector<ComputeGraphPtr> cur_node_subgraph;
  auto op_desc = node->GetOpDesc();
  auto sub_graph_names = op_desc->GetSubgraphInstanceNames();
  if (sub_graph_names.empty()) {
    return cur_node_subgraph;
  }

  auto root_graph = GraphUtils::FindRootGraph(node->GetOwnerComputeGraph());
  for (const auto &name : sub_graph_names) {
    if (name.empty()) {
      GELOGW("The node %s contains empty subgraph instance name", node->GetName().c_str());
      continue;
    }
    auto sub_graph = root_graph->GetSubgraph(name);
    if (sub_graph == nullptr) {
      REPORT_INNER_ERROR("E19999", "Can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
      GE_LOGE("[Get][Graph] can not find the subgrpah %s for node %s", name.c_str(), node->GetName().c_str());
      continue;
    }
    cur_node_subgraph.emplace_back(sub_graph);
  }
  return cur_node_subgraph;
}

graphStatus InferBasePass::UpdateTensorDescToSubgraphData(NodePtr &node, std::set<NodePtr> &changed_nodes) {
  // if infer again, update output of while into subgraph data node
  auto op_desc = node->GetOpDesc();
  for (const auto &sub_graph : GetCurNodeSubgraphs(node)) {
    for (const auto &node_sub : sub_graph->GetDirectNode()) {
      if (node_sub->GetType() != DATA) {
        continue;
      }
      auto name = sub_graph->GetName();
      int ref_i;
      auto data_opdesc = node_sub->GetOpDesc();
      if (data_opdesc == nullptr) {
        REPORT_INNER_ERROR("E19999", "Invalid data node on the sub graph %s parent node %s, no OpDesc", name.c_str(),
                           node->GetName().c_str());
        GE_LOGE("[Get][OpDesc] Invalid data node on the sub graph %s parent node %s, no OpDesc", name.c_str(),
                node->GetName().c_str());
        return GRAPH_FAILED;
      }
      if (!AttrUtils::GetInt(data_opdesc, ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
        REPORT_INNER_ERROR("E19999", "Invalid data node on the sub graph %s parent node %s, no ref-index attribute",
                           name.c_str(), node->GetName().c_str());
        GE_LOGE("[Get][Int] Invalid data node on the sub graph %s parent node %s, no ref-index attribute", name.c_str(),
                node->GetName().c_str());
        return GRAPH_FAILED;
      }
      if (data_opdesc->HasAttr(ATTR_MBATCH_ORIGIN_INPUT_DIMS)) {
        continue;
      }
      auto input_desc = op_desc->MutableInputDesc(ref_i);
      if (input_desc == nullptr) {
        REPORT_INNER_ERROR("E19999",
                           "The ref index(%d) on the data %s on the sub graph %s "
                           "parent node %s are incompatible, inputs num %u",
                           ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
                           node->GetAllInDataAnchorsSize());
        GE_LOGE(
          "[Call][MutableInputDesc] The ref index(%d) on the data %s on the sub graph %s "
          "parent node %s are incompatible, inputs num %u",
          ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(), node->GetAllInDataAnchorsSize());
        return GRAPH_FAILED;
      }
      GELOGI("Ref index is %d, input_desc dtype is %d, node name is %s", ref_i, input_desc->GetDataType(),
             node->GetName().c_str());

      // if need infer again, refresh subgraph input with output
      bool is_infer_again = false;
      AttrUtils::GetBool(node->GetOpDesc(), ATTR_NAME_NEED_INFER_AGAIN, is_infer_again);
      if (is_infer_again) {
        input_desc = op_desc->MutableOutputDesc(ref_i);
        if (input_desc == nullptr) {
          REPORT_INNER_ERROR("E19999",
                             "The ref index(%d) on the data %s on the subgraph %s "
                             "parent node %s are incompatible, outputs num %u.",
                             ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
                             node->GetAllOutDataAnchorsSize());
          GELOGE(PARAM_INVALID,
                 "[Call][MutableOutputDesc] The ref index(%d) on the data %s on the subgraph %s "
                 "parent node %s are incompatible, outputs num %u.",
                 ref_i, node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(),
                 node->GetAllOutDataAnchorsSize());
        }
        GELOGD("Update input desc of data %s on the sub graph %s of node %s,output idx: %d from [%s] to [%s]",
               node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str(), ref_i,
               data_opdesc->GetInputDescPtr(0)->GetShape().ToString().c_str(),
               input_desc->GetShape().ToString().c_str());
      }

      auto data_input_desc = data_opdesc->MutableInputDesc(0);
      auto ret = data_opdesc->UpdateInputDesc(0, *input_desc);
      if (ret != GRAPH_SUCCESS) {
        REPORT_CALL_ERROR("E19999", "Failed to update input desc of data %s on the sub graph %s parent node %s",
                          node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
        GE_LOGE("[Update][InputDesc] of data %s on the sub graph %s parent node %s failed", node_sub->GetName().c_str(),
                name.c_str(), node->GetName().c_str());
        return ret;
      }
      bool input_changed = TensorDescChanged(input_desc, data_input_desc);

      auto data_output_desc = data_opdesc->MutableOutputDesc(0);
      ret = data_opdesc->UpdateOutputDesc(0, *input_desc);
      if (ret != GRAPH_SUCCESS) {
        REPORT_CALL_ERROR("E19999", "Failed to update output desc of data %s on the sub graph %s parent node %s",
                          node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
        GE_LOGE("[Update][OutputDesc] of data %s on the sub graph %s parent node %s failed",
                node_sub->GetName().c_str(), name.c_str(), node->GetName().c_str());
        return ret;
      }
      bool output_changed = TensorDescChanged(input_desc, data_output_desc);

      if (input_changed || output_changed) {
        changed_nodes.insert(node_sub);
      }
    }
  }
  return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateTensorDescToParentNode(NodePtr &node, std::set<NodePtr> &changed_nodes) {
  std::vector<std::vector<GeTensorDesc>> ref_data_tensors(node->GetAllInDataAnchorsSize());
  std::vector<std::vector<GeTensorDesc>> ref_out_tensors(node->GetAllOutDataAnchorsSize());

  for (const auto &sub_graph : GetCurNodeSubgraphs(node)) {
    auto name = sub_graph->GetName();
    NodePtr netoutput = nullptr;
    auto ret = FindSubgraphDataAndNetoutput(sub_graph, netoutput, node, ref_data_tensors);
    if (ret != GRAPH_SUCCESS) {
      return ret;
    }
    if (netoutput == nullptr) {
      REPORT_INNER_ERROR("E19999", "No NetOutput node on sub graph %s, parent node %s", name.c_str(),
                         node->GetName().c_str());
      GE_LOGE("[Check][Param] No NetOutput node on sub graph %s, parent node %s", name.c_str(),
              node->GetName().c_str());
      return GRAPH_FAILED;
    }
    auto netoutput_opdesc = netoutput->GetOpDesc();
    if (netoutput_opdesc == nullptr) {
      REPORT_INNER_ERROR("E19999", "Invalid NetOutput node on sub graph %s, parent node %s, no OpDesc on it",
                         name.c_str(), node->GetName().c_str());
      GE_LOGE("[Get][OpDesc] Invalid NetOutput node on sub graph %s, parent node %s, no OpDesc on it", name.c_str(),
              node->GetName().c_str());
      return GRAPH_FAILED;
    }
    for (auto &edge_anchor : netoutput->GetAllInDataAnchors()) {
      auto edge_desc = netoutput_opdesc->MutableInputDesc(edge_anchor->GetIdx());
      if (edge_desc == nullptr) {
        REPORT_INNER_ERROR("E19999",
                           "Invalid NetOutput node on sub graph %s, parent node %s, "
                           "can not find input tensor %d",
                           name.c_str(), node->GetName().c_str(), edge_anchor->GetIdx());
        GE_LOGE("[Get][Tensor] Invalid NetOutput node on sub graph %s, parent node %s, can not find input tensor %d",
                name.c_str(), node->GetName().c_str(), edge_anchor->GetIdx());
        return GRAPH_FAILED;
      }
      GELOGI("Netoutput in anchor index is %d, input tensor dim is %zu", edge_anchor->GetIdx(),
             edge_desc->GetShape().GetDimNum());
      int ref_i;
      if (!AttrUtils::GetInt(edge_desc, ATTR_NAME_PARENT_NODE_INDEX, ref_i)) {
        // if there is no ref index on the TensorDesc, it means the output data will be ignored outer.
        continue;
      }
      GELOGI("Parent node index of edge desc is %d", ref_i);
      if (ref_i < 0 || static_cast<uint32_t>(ref_i) >= node->GetAllOutDataAnchorsSize()) {
        return GRAPH_FAILED;
      }
      ref_out_tensors[ref_i].emplace_back(*edge_desc);
    }
  }

  if (node->GetType() == WHILE) {
    return UpdateParentNodeForWhile(node, ref_data_tensors, ref_out_tensors, changed_nodes);
  }
  return UpdateParentNodeForBranch(node, ref_out_tensors, changed_nodes);
}

graphStatus InferBasePass::UpdateParentNodeForWhile(NodePtr &node,
                                                    std::vector<std::vector<GeTensorDesc>> &ref_data_tensors,
                                                    std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
                                                    std::set<NodePtr> &changed_nodes) {
  GELOGD("Enter update parent node shape for class while op process");
  if (ref_data_tensors.size() != ref_out_tensors.size()) {
    REPORT_INNER_ERROR("E19999", "op:%s(%s) input number[%zu] and output number[%zu] is not same!",
                       node->GetName().c_str(), node->GetType().c_str(), ref_data_tensors.size(),
                       ref_out_tensors.size());
    GELOGE(GRAPH_FAILED, "[Check][Param] while op [%s] input number[%zu] and output number[%zu] is not same!",
           node->GetName().c_str(), ref_data_tensors.size(), ref_out_tensors.size());
    return GRAPH_FAILED;
  }
  for (size_t i = 0; i < ref_data_tensors.size(); i++) {
    if (ref_out_tensors[i].size() != 1) {
      REPORT_INNER_ERROR("E19999", "while op, every output should only find one output tensor in all graph!");
      GELOGE(GRAPH_FAILED, "[Check][Param] while op, every output should only find one output tensor in all graph!");
      return GRAPH_FAILED;
    }
  }
  bool need_infer_again = false;
  // check input and output
  for (size_t i = 0; i < ref_out_tensors.size(); i++) {
    if (ref_out_tensors[i].empty()) {
      continue;
    }
    auto ref_out_tensor = ref_out_tensors[i].at(0);
    auto out_shape = ref_out_tensor.MutableShape();
    vector<std::pair<int64_t, int64_t>> data_shape_range;
    // ref_i's data and output tensor shape should be same
    for (auto &tensor : ref_data_tensors[i]) {
      if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
        REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype or format among all ref output",
                           node->GetName().c_str());
        GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype or format output.",
               node->GetName().c_str());
        return GRAPH_FAILED;
      }
      auto data_shape = tensor.MutableShape();
      // input is dynamic, here use dim_num
      if (data_shape.GetDims() != out_shape.GetDims()) {
        GELOGI("After infer, While %s %zu output shape [%s] is not match with input shape [%s].Need infer again.",
               node->GetName().c_str(), i, out_shape.ToString().c_str(), data_shape.ToString().c_str());
        if (data_shape.GetDimNum() != out_shape.GetDimNum()) {
          ref_out_tensor.SetUnknownDimNumShape();
        } else {
          for (size_t j = 0; j < data_shape.GetDimNum(); ++j) {
            if (data_shape.GetDim(j) != out_shape.GetDim(j)) {
              if (data_shape.GetDim(j) != UNKNOWN_DIM) {
                // if input data is fix shape, output is different, need_infer_again
                need_infer_again = true;
              }
              data_shape.SetDim(j, UNKNOWN_DIM);
            }
            // set shape rang of while, if dim is unknown ,set shape range as {1,-1}
            if (data_shape.GetDim(j) == UNKNOWN_DIM) {
              data_shape_range.emplace_back(std::make_pair(1, UNKNOWN_DIM));
            } else {
              data_shape_range.emplace_back(std::make_pair(data_shape.GetDim(j), data_shape.GetDim(j)));
            }
          }
          ref_out_tensor.SetShape(data_shape);
          ref_out_tensor.SetShapeRange(data_shape_range);
        }
      }
    }

    auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
    (void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensor);
    bool output_changed = TensorDescChanged(ComGraphMakeShared<GeTensorDesc>(ref_out_tensor), output_desc);
    if (output_changed) {
      changed_nodes.insert(node);
    }
  }
  AttrUtils::SetBool(node->GetOpDesc(), ATTR_NAME_NEED_INFER_AGAIN, need_infer_again);
  return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateOutputForMultiBatch(NodePtr &node,
                                                     std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
                                                     std::set<NodePtr> &changed_nodes) {
  // check sub_graph shape. Get max for update.
  for (size_t i = 0; i < ref_out_tensors.size(); ++i) {
    if (ref_out_tensors[i].empty()) {
      continue;
    }

    int64_t max_size = 0;
    size_t max_shape_index = 0;
    auto &ref_out_tensor = ref_out_tensors[i].at(0);
    for (size_t j = 0; j < ref_out_tensors[i].size(); ++j) {
      auto &tensor = ref_out_tensors[i].at(j);
      if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
        REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype among all ref output",
                           node->GetName().c_str());
        GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype among all ref output",
               node->GetName().c_str());
        return GRAPH_FAILED;
      }

      auto shape = tensor.MutableShape();
      int64_t size = 1;
      for (auto dim : shape.GetDims()) {
        if (dim != 0 && INT64_MAX / dim < size) {
          REPORT_INNER_ERROR("E19999", "The shape:%s size overflow, node:%s", shape.ToString().c_str(),
                             node->GetName().c_str());
          GELOGE(PARAM_INVALID, "[Check][Overflow] The shape size overflow");
          return PARAM_INVALID;
        }
        size *= dim;
      }

      if (size > max_size) {
        max_size = size;
        max_shape_index = j;
      }
    }

    auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
    (void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensors[i].at(max_shape_index));
    bool output_changed =
      TensorDescChanged(ComGraphMakeShared<GeTensorDesc>(ref_out_tensors[i].at(max_shape_index)), output_desc);
    if (output_changed) {
      changed_nodes.insert(node);
    }
  }

  return GRAPH_SUCCESS;
}

graphStatus InferBasePass::UpdateParentNodeForBranch(NodePtr &node,
                                                     std::vector<std::vector<GeTensorDesc>> &ref_out_tensors,
                                                     std::set<NodePtr> &changed_nodes) {
  GELOGD("Enter update parent node shape for class branch op process");
  if (node->GetOpDesc()->HasAttr(ATTR_NAME_BATCH_NUM)) {
    return UpdateOutputForMultiBatch(node, ref_out_tensors, changed_nodes);
  }

  // check sub_graph shape.If not same ,do unknown shape process
  for (size_t i = 0; i < ref_out_tensors.size(); i++) {
    if (ref_out_tensors[i].empty()) {
      continue;
    }
    auto ref_out_tensor = ref_out_tensors[i].at(0);
    ge::GeShape &ref_out_tensor_shape = ref_out_tensor.MutableShape();
    for (auto &tensor : ref_out_tensors[i]) {
      if (ref_out_tensor.GetDataType() != tensor.GetDataType()) {
        REPORT_INNER_ERROR("E19999", "node[%s] does not support diff dtype among all ref output, shape:%s",
                           node->GetName().c_str(), ref_out_tensor_shape.ToString().c_str());
        GELOGE(GRAPH_FAILED, "[Check][Param] node[%s] does not support diff dtype output", node->GetName().c_str());
        return GRAPH_FAILED;
      }
      auto shape = tensor.MutableShape();
      if (shape.GetDims().size() != ref_out_tensor_shape.GetDims().size()) {
        GELOGD("node is %s, i : %zu, shape size: %lu, ref_out_tensor_shape size: %lu", node->GetName().c_str(), i,
               shape.GetShapeSize(), ref_out_tensor_shape.GetShapeSize());
        ref_out_tensor_shape = GeShape(UNKNOWN_RANK);
        break;
      }
      for (size_t j = 0; j < ref_out_tensor_shape.GetDims().size(); j++) {
        if (ref_out_tensor_shape.GetDim(j) == shape.GetDim(j)) {
          continue;
        }
        GELOGD("node is %s, i : %zu, j: %zu ,shape size: %lu, ref_out_tensor_shape size: %lu", node->GetName().c_str(),
               i, j, shape.GetShapeSize(), ref_out_tensor_shape.GetShapeSize());
        (void)ref_out_tensor_shape.SetDim(j, UNKNOWN_DIM);
      }
    }

    auto output_desc = node->GetOpDesc()->MutableOutputDesc(i);
    (void)node->GetOpDesc()->UpdateOutputDesc(i, ref_out_tensor);
    bool output_changed =
      TensorDescChanged(ComGraphMakeShared<GeTensorDesc>(ref_out_tensor), output_desc);
    if (output_changed) {
      changed_nodes.insert(node);
    }
  }
  return GRAPH_SUCCESS;
}

void InferBasePass::PrintInOutTensorShape(const NodePtr &node, const std::string &phase) {
  if (!IsLogEnable(GE, DLOG_DEBUG)) {
    return;
  }
  if (node == nullptr) {
    REPORT_INNER_ERROR("E19999", "param node is nullprt, check invalid");
    GELOGE(GRAPH_FAILED, "[Check][Param] node is null");
    return;
  }
  ge::OpDescPtr op_desc = node->GetOpDesc();
  GE_IF_BOOL_EXEC(op_desc == nullptr, REPORT_INNER_ERROR("E19999", "node has no opdesc, check invalid");
                  GELOGE(GRAPH_FAILED, "[Get][OpDesc] op_desc is null."); return );
  std::stringstream ss;
  ss << "{";
  int32_t in_idx = 0;
  int32_t out_idx = 0;
  for (const auto &input_desc : op_desc->GetAllInputsDescPtr()) {
    if (input_desc == nullptr) {
      in_idx++;
      continue;
    }
    if (in_idx > 0) {
      ss << "    ";
    }
    ss << "input_" << in_idx << " "
       << "tensor: [";
    ss << "(shape:[" << input_desc->MutableShape().ToString() << "]),";
    ss << "(format:" << TypeUtils::FormatToSerialString(input_desc->GetFormat()) << "),";
    ss << "(dtype:" << TypeUtils::DataTypeToSerialString(input_desc->GetDataType()) << "),";
    ss << "(origin_shape:" << input_desc->GetOriginShape().ToString() << "),";
    ss << "(origin_format:" << TypeUtils::FormatToSerialString(input_desc->GetOriginFormat()) << "),";
    ss << "(origin_dtype:" << TypeUtils::DataTypeToSerialString(input_desc->GetOriginDataType()) << "),";
    string range_str;
    SerialShapeRange(input_desc, range_str);
    ss << "(shape_range:" << range_str << "),";
    string value_range_str;
    SerialValueRange(input_desc, value_range_str);
    ss << "(value_range:" << value_range_str << ")]";
    in_idx++;
  }
  for (const auto &output_desc : op_desc->GetAllOutputsDescPtr()) {
    if (output_desc == nullptr) {
      out_idx++;
      continue;
    }
    ss << "    ";
    ss << "output_" << out_idx << " "
       << "tensor: [";
    ss << "(shape:[" << output_desc->MutableShape().ToString() << "]),";
    ss << "(format:" << TypeUtils::FormatToSerialString(output_desc->GetFormat()) << "),";
    ss << "(dtype:" << TypeUtils::DataTypeToSerialString(output_desc->GetDataType()) << "),";
    ss << "(origin_shape:" << output_desc->GetOriginShape().ToString() << "),";
    ss << "(origin_format:" << TypeUtils::FormatToSerialString(output_desc->GetOriginFormat()) << "),";
    ss << "(origin_dtype:" << TypeUtils::DataTypeToSerialString(output_desc->GetOriginDataType()) << "),";
    string range_str;
    SerialShapeRange(output_desc, range_str);
    ss << "(shape_range:" << range_str << "),";
    string value_range_str;
    SerialValueRange(output_desc, value_range_str);
    ss << "(value_range:" << value_range_str << ")]";
    out_idx++;
  }
  ss << "}";
  GELOGD("Shape dump [%s], Node name: [%s]. %s", phase.c_str(), node->GetName().c_str(), ss.str().c_str());
}
}  // namespace ge