// 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 "paddle/fluid/framework/ir/mkldnn/mkldnn_placement_pass.h"

#include <gtest/gtest.h>
#include <boost/logic/tribool.hpp>

namespace paddle {
namespace framework {
namespace ir {

class PlacementPassTest {
 private:
  void SetOp(ProgramDesc* prog, const std::string& type,
             const std::string& name, const std::vector<std::string>& inputs,
             const std::vector<std::string>& outputs,
             boost::tribool use_mkldnn) {
    auto* op = prog->MutableBlock(0)->AppendOp();

    op->SetType(type);

    if (!boost::indeterminate(use_mkldnn))
      op->SetAttr("use_mkldnn", use_mkldnn);

    if (type == "conv2d") {
      op->SetAttr("name", name);
      op->SetInput("Input", {inputs[0]});
      op->SetInput("Filter", {inputs[1]});
      op->SetInput("Bias", {inputs[2]});
    } else if (type == "relu") {
      op->SetInput("X", inputs);
    } else if (type == "concat") {
      op->SetAttr("axis", 1);
      op->SetInput("X", {inputs[0], inputs[1]});
    } else if (type == "pool2d") {
      op->SetInput("X", {inputs[0]});
    } else {
      FAIL() << "Unexpected operator type.";
    }
    op->SetOutput("Out", {outputs[0]});
  }

  // operator                      use_mkldnn
  // ---------------------------------------
  // (a,b)->concat->c              none
  // (c,weights,bias)->conv->f     none
  // f->relu->g                    false
  // g->pool->h                    false
  // (h,weights2,bias2)->conv->k   true
  // k->relu->l                    true
  ProgramDesc BuildProgramDesc() {
    ProgramDesc prog;

    for (auto& v :
         std::vector<std::string>({"a", "b", "c", "weights", "bias", "f", "g",
                                   "h", "weights2", "bias2", "k", "l"})) {
      auto* var = prog.MutableBlock(0)->Var(v);
      var->SetType(proto::VarType::SELECTED_ROWS);
      if (v == "weights" || v == "bias") {
        var->SetPersistable(true);
      }
    }

    SetOp(&prog, "concat", "concat1", std::vector<std::string>({"a", "b"}),
          std::vector<std::string>({"c"}), boost::indeterminate);
    SetOp(&prog, "conv2d", "conv1",
          std::vector<std::string>({"c", "weights", "bias"}),
          std::vector<std::string>({"f"}), boost::indeterminate);
    SetOp(&prog, "relu", "relu1", std::vector<std::string>({"f"}),
          std::vector<std::string>({"g"}), false);
    SetOp(&prog, "pool2d", "pool1", std::vector<std::string>({"g"}),
          std::vector<std::string>({"h"}), false);
    SetOp(&prog, "conv2d", "conv2",
          std::vector<std::string>({"h", "weights2", "bias2"}),
          std::vector<std::string>({"k"}), true);
    SetOp(&prog, "relu", "relu2", std::vector<std::string>({"k"}),
          std::vector<std::string>({"l"}), true);

    return prog;
  }

 public:
  void MainTest(std::initializer_list<std::string> mkldnn_enabled_op_types,
                unsigned expected_use_mkldnn_true_count) {
    auto prog = BuildProgramDesc();

    std::unique_ptr<ir::Graph> graph(new ir::Graph(prog));

    auto pass = PassRegistry::Instance().Get("mkldnn_placement_pass");

    pass->Set("mkldnn_enabled_op_types",
              new std::unordered_set<std::string>(mkldnn_enabled_op_types));

    graph.reset(pass->Apply(graph.release()));

    unsigned use_mkldnn_true_count = 0;

    for (auto* node : graph->Nodes()) {
      if (node->IsOp()) {
        auto* op = node->Op();
        if (op->HasAttr("use_mkldnn") &&
            BOOST_GET_CONST(bool, op->GetAttr("use_mkldnn"))) {
          ++use_mkldnn_true_count;
        }
      }
    }

    EXPECT_EQ(use_mkldnn_true_count, expected_use_mkldnn_true_count);
  }

  void PlacementNameTest() {
    auto pass = PassRegistry::Instance().Get("mkldnn_placement_pass");
    EXPECT_EQ(static_cast<PlacementPassBase*>(pass.get())->GetPlacementName(),
              "MKLDNN");
  }
};

TEST(MKLDNNPlacementPass, enable_conv_relu) {
  // 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 0 pool
  PlacementPassTest().MainTest({"conv2d", "relu"}, 3);
}

TEST(MKLDNNPlacementPass, enable_relu_pool) {
  // 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
  PlacementPassTest().MainTest({"relu", "pool2d"}, 4);
}

TEST(MKLDNNPlacementPass, enable_all) {
  // 1 conv (1 conv is always true) + 2 relu (1 relu is always true) + 1 pool
  PlacementPassTest().MainTest({}, 4);
}

TEST(MKLDNNPlacementPass, placement_name) {
  PlacementPassTest().PlacementNameTest();
}

}  // namespace ir
}  // namespace framework
}  // namespace paddle

USE_PASS(mkldnn_placement_pass);
