// Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
//
// 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 "lite/core/mir/memory_optimize_pass.h"
#include <memory>
#include <utility>
#include <vector>
#include "lite/core/mir/graph_visualize_pass.h"
#include "lite/core/mir/pass_registry.h"
#include "lite/core/type_system.h"

namespace paddle {
namespace lite {
namespace mir {

typedef struct {
  std::string name;
  int cluster;
  std::pair<int, int> lifetime;
  std::unordered_set<std::string> adj;
} MemNode;

void MemoryOptimizePass::CollectLifeCycleByDevice(
    std::unordered_map<std::string, lifecycle_map_t>* lifecycles,
    SSAGraph* graph) {
  max_lifecycle_ = 0;

  auto is_host = [](TargetType x) -> bool {
    return x == TARGET(kHost) || x == TARGET(kX86) || x == TARGET(kARM);
  };
  // The vars which inputs or outputs are invalid op will not be reused.
  auto valid_var = [&](Node* node) -> bool {
    std::set<std::string> invalid_op = {"while",
                                        "conditional_block",
                                        "conditional_block_infer",
                                        "merge_lod_tensor_infer",
                                        "merge_lod_tensor",
                                        "equal",
                                        "lod_reset",
                                        "concat",
                                        "yolo_box",
                                        "subgraph",
                                        "feed",
                                        "fetch"};
    for (auto* tmp : node->inlinks) {
      CHECK(tmp->IsStmt());
      std::string op_type = tmp->AsStmt().op_info()->Type();
      if (std::find(invalid_op.begin(), invalid_op.end(), op_type) !=
          invalid_op.end()) {
        return false;
      }
    }
    for (auto* tmp : node->outlinks) {
      CHECK(tmp->IsStmt());
      std::string op_type = tmp->AsStmt().op_info()->Type();
      if (std::find(invalid_op.begin(), invalid_op.end(), op_type) !=
          invalid_op.end()) {
        return false;
      }
    }
    return true;
  };

  for (auto& op_node : graph->StmtTopologicalOrder()) {
    if (op_node->IsStmt()) {
      auto inputs = op_node->inlinks;
      auto outputs = op_node->outlinks;
      std::vector<Node*> requires(inputs.begin(), inputs.end());
      requires.insert(requires.end(), outputs.begin(), outputs.end());
      for (Node* node : requires) {
        CHECK(node->IsArg());
        auto& arg = node->AsArg();
        if (arg.is_weight || arg.is_persist) continue;
        if (!valid_var(node)) continue;
        std::string var_name = arg.name;
        TargetType target_type = node->AsArg().type->target();
        if (is_host(target_type)) target_type = TARGET(kHost);

        if (!(*lifecycles)[TargetToStr(target_type)].count(var_name)) {
          (*lifecycles)[TargetToStr(target_type)].emplace(
              var_name, std::make_pair(max_lifecycle_, max_lifecycle_));
        } else {
          int cur_life =
              (*lifecycles)[TargetToStr(target_type)][var_name].second;
          (*lifecycles)[TargetToStr(target_type)][var_name].second =
              std::max(max_lifecycle_, cur_life);
        }
      }
      ++max_lifecycle_;
    }
  }
  LOG(INFO) << "There are " << (*lifecycles).size() << " types device var.";
}

void MemoryOptimizePass::MakeReusePlan(
    const lifecycle_map_t& lifecycles,
    std::unordered_map<std::string, std::string>* node2cluster) {
  std::vector<MemNode> mem_nodes;
  std::vector<std::string> cluster;
  for (auto& data : lifecycles) {
    MemNode temp_node;
    temp_node.name = data.first;
    temp_node.cluster = -1;
    temp_node.lifetime = data.second;
    mem_nodes.push_back(temp_node);
  }
  auto overlap = [](std::pair<int, int> a, std::pair<int, int> b) -> bool {
    return b.second >= a.first && a.second >= b.first;
  };
  // If the lifetime of two nodes is overwritten, we set them as adjacent nodes.
  for (size_t i = 0; i < mem_nodes.size(); i++) {
    for (size_t j = i + 1; j < mem_nodes.size(); j++) {
      if (overlap(mem_nodes[i].lifetime, mem_nodes[j].lifetime)) {
        mem_nodes[i].adj.insert(mem_nodes[j].name);
        mem_nodes[j].adj.insert(mem_nodes[i].name);
      }
    }
  }

  // Generating Memory Reuse Strategy Based on Greedy Way
  // The vars can be reused if there is no overlap between them.
  for (size_t i = 0; i < mem_nodes.size(); i++) {
    if (mem_nodes[i].cluster >= 0) continue;
    int cluster_index = cluster.size();
    mem_nodes[i].cluster = cluster_index;
    (*node2cluster)[mem_nodes[i].name] = mem_nodes[i].name;
    cluster.push_back(mem_nodes[i].name);
    std::unordered_set<std::string> cluster_adj = mem_nodes[i].adj;
    for (size_t j = i + 1; j < mem_nodes.size(); j++) {
      if (mem_nodes[j].cluster < 0 &&
          (cluster_adj.find(mem_nodes[j].name) == cluster_adj.end())) {
        (*node2cluster)[mem_nodes[j].name] = mem_nodes[i].name;
        mem_nodes[j].cluster = cluster_index;
        for (auto& n : mem_nodes[j].adj) {
          cluster_adj.insert(n);
        }
      }
    }
  }
  for (auto& name : cluster) {
    LOG(INFO) << "cluster: " << name;
  }
}

void MemoryOptimizePass::PerformReusePlan(
    SSAGraph* graph,
    const std::unordered_map<std::string, std::string>& reuse_table) {
  int node_append_idx = 0;
  for (auto& op_node : graph->StmtTopologicalOrder()) {
    if (!op_node->IsStmt()) continue;
    auto& stmt = op_node->AsStmt();
    auto* op_info = stmt.mutable_op_info();
    std::unordered_map<std::string, std::vector<std::string>> in_args, out_args;
    // replace the op's input according the reuse table.
    for (auto argument : op_info->inputs()) {
      for (const auto& x : argument.second) {
        auto name = x;
        if (reuse_table.count(x) && reuse_table.at(x) != x) {
          name = reuse_table.at(x);
        }
        in_args[argument.first].push_back(name);
        VLOG(4) << op_info->Type() << " input " << x << " -> " << name;
      }
    }

    // modify the graph
    for (Node* input_node : op_node->inlinks) {
      CHECK(input_node->IsArg()) << "The op node's inputs should be var node.";
      std::string name = input_node->AsArg().name;
      if (reuse_table.count(name) && reuse_table.at(name) != name) {
        auto replace_name = reuse_table.at(name);
        input_node->AsArg().name =
            replace_name + "(" + std::to_string(node_append_idx) + ")";
        node_append_idx++;
      }
    }

    // replace the op's output according the reuse table.
    for (auto argument : op_info->outputs()) {
      for (const auto& x : argument.second) {
        auto name = x;
        if (reuse_table.count(x) && reuse_table.at(x) != x) {
          name = reuse_table.at(x);
        }
        out_args[argument.first].push_back(name);
        VLOG(4) << op_info->Type() << " output " << x << " -> " << name;
      }
    }

    // modify the graph
    for (Node* out_node : op_node->outlinks) {
      CHECK(out_node->IsArg()) << "The op node's outputs should be var node.";
      std::string name = out_node->AsArg().name;
      if (reuse_table.count(name) && reuse_table.at(name) != name) {
        auto replace_name = reuse_table.at(name);
        out_node->AsArg().name =
            replace_name + "(" + std::to_string(node_append_idx) + ")";
        node_append_idx++;
      }
    }

    for (auto& arg : in_args) {
      op_info->SetInput(arg.first, arg.second);
    }
    for (auto& arg : out_args) {
      op_info->SetOutput(arg.first, arg.second);
    }

    auto original_selected_kernel = std::move(stmt.kernels().front());
    auto updated_op_info = *stmt.mutable_op_info();
    stmt.ResetOp(updated_op_info, graph->valid_places());
    stmt.kernels().clear();
    stmt.kernels().emplace_back(std::move(original_selected_kernel));
    for (auto& kernel : stmt.kernels()) {
      VLOG(4) << "kernel info: " << kernel->name();
      stmt.op()->AttachKernel(kernel.get());
    }
    graph->CheckValid();
  }
}

void MemoryOptimizePass::Apply(const std::unique_ptr<SSAGraph>& graph) {
  // Memory optimization.
  // We will perform the following operation:
  // 1. Collect all var's lifetime, then classify them according to the device.
  // Only the vars on the same device can be reused.
  // 2. Make reuse plan: the vars can be reused if there is no overlap between
  // them.
  // The final plan is a mapping table in which the key represents the original
  // name of var and the value in the table represents the current name of var.
  // 3. Perform reuse plan: Replace all var's name in the model according to the
  // mapping table.
  std::unordered_map<std::string, lifecycle_map_t> lifecycles;
  CollectLifeCycleByDevice(&lifecycles, graph.get());
  for (auto& ele : lifecycles) {
    std::unordered_map<std::string, std::string> node2cluster;
    MakeReusePlan(ele.second, &node2cluster);
    PerformReusePlan(graph.get(), node2cluster);
  }
}

}  // namespace mir
}  // namespace lite
}  // namespace paddle

REGISTER_MIR_PASS(memory_optimize_pass, paddle::lite::mir::MemoryOptimizePass)
    .BindTargets({TARGET(kARM)})
    .ExcludeTargets({TARGET(kOpenCL), TARGET(kNPU), TARGET(kXPU), TARGET(kBM)});
