/* Copyright 2019 The TensorFlow 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 "tensorflow/core/grappler/optimizers/data/slack.h"

#include "absl/status/status.h"
#include "tensorflow/core/framework/attr_value_util.h"
#include "tensorflow/core/grappler/grappler_item.h"
#include "tensorflow/core/grappler/optimizers/data/function_utils.h"
#include "tensorflow/core/grappler/optimizers/data/graph_utils.h"
#include "tensorflow/core/grappler/utils/functions.h"
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace grappler {
namespace {

void SetupGrapplerItem(GrapplerItem *item) {
  MutableGraphView graph(&item->graph);

  std::vector<std::pair<string, AttrValue>> common_attrs(2);
  AttrValue shapes_attr;
  SetAttrValue(std::vector<TensorShape>({{}}), &shapes_attr);
  common_attrs[0] = std::make_pair("output_shapes", shapes_attr);
  AttrValue types_attr;
  SetAttrValue(std::vector<DataType>({DT_INT64}), &types_attr);
  common_attrs[1] = std::make_pair("output_types", types_attr);

  NodeDef *start_node = graph_utils::AddScalarConstNode<int64_t>(0, &graph);
  NodeDef *stop_node = graph_utils::AddScalarConstNode<int64_t>(10, &graph);
  NodeDef *step_node = graph_utils::AddScalarConstNode<int64_t>(1, &graph);

  std::vector<string> range_inputs(3);
  range_inputs[0] = start_node->name();
  range_inputs[1] = stop_node->name();
  range_inputs[2] = step_node->name();
  NodeDef *range_node = graph_utils::AddNode(
      "RangeDataset", "RangeDataset", range_inputs, common_attrs, &graph);

  NodeDef *buffer_size_node =
      graph_utils::AddScalarConstNode<int64_t>(1, &graph);
  NodeDef *prefetch_node = graph_utils::AddNode(
      "PrefetchDataset", "PrefetchDataset",
      {range_node->name(), buffer_size_node->name()}, common_attrs, &graph);
  item->fetch.push_back(prefetch_node->name());
}

struct ParameterizedSlackTest
    : ::testing::TestWithParam<std::tuple<string, int>> {};

TEST_P(ParameterizedSlackTest, BasicTest) {
  GrapplerItem item;
  SetupGrapplerItem(&item);

  Slack optimizer;
  tensorflow::RewriterConfig_CustomGraphOptimizer config;
  (*config.mutable_parameter_map())["slack_period"].set_s(
      std::get<0>(GetParam()));
  TF_ASSERT_OK(optimizer.Init(&config));

  GraphDef output;
  TF_ASSERT_OK(optimizer.Optimize(nullptr, item, &output));
  ASSERT_TRUE(graph_utils::ContainsNodeWithOp("PrefetchDataset", output));
  NodeDef optimized_prefetch_node =
      output.node(graph_utils::FindGraphNodeWithOp("PrefetchDataset", output));
  EXPECT_EQ(optimized_prefetch_node.attr().at("slack_period").i(),
            std::get<1>(GetParam()));
}

INSTANTIATE_TEST_SUITE_P(DifferentSlackEveryValues, ParameterizedSlackTest,
                         ::testing::Values(std::make_tuple("1", 1),
                                           std::make_tuple("8", 8)));

TEST(SlackTest, TestFailWithoutInit) {
  GrapplerItem item;
  Slack optimizer;
  GraphDef output;
  absl::Status result = optimizer.Optimize(nullptr, item, &output);

  EXPECT_FALSE(result.ok());
  EXPECT_TRUE(absl::IsInvalidArgument(result));
}

TEST(SlackTest, TestFailWithInvalidSlackEveryParam) {
  GrapplerItem item;
  SetupGrapplerItem(&item);

  Slack optimizer;
  tensorflow::RewriterConfig_CustomGraphOptimizer config;
  (*config.mutable_parameter_map())["slack_period"].set_s("0");
  TF_ASSERT_OK(optimizer.Init(&config));

  GraphDef output;
  absl::Status result = optimizer.Optimize(nullptr, item, &output);

  EXPECT_FALSE(result.ok());
  EXPECT_TRUE(absl::IsInvalidArgument(result));
}

TEST(SlackTest, TestFunctionNotOptimized) {
  GrapplerFunctionItem item;
  FunctionDefLibrary lib_def;
  FunctionDef *fdef = lib_def.add_function();
  fdef->mutable_signature()->set_name("nested_function");
  auto *input_arg = fdef->mutable_signature()->add_input_arg();
  input_arg->set_name("args_0");
  input_arg->set_type(DT_INT64);
  auto *output_arg = fdef->mutable_signature()->add_output_arg();
  output_arg->set_name("identity");
  output_arg->set_type(DT_VARIANT);
  fdef->mutable_signature()->set_is_stateful(true);

  AttrValue shapes_attr;
  SetAttrValue(std::vector<TensorShape>({{}}), &shapes_attr);
  AttrValue types_attr;
  SetAttrValue(std::vector<DataType>({DT_INT64}), &types_attr);
  NodeDef *tensor_dataset_node =
      function_utils::AddNode("TensorDataset", "TensorDataset", {"args_0"},
                              {std::make_pair("output_shapes", shapes_attr),
                               std::make_pair("Toutput_types", types_attr)},
                              fdef);
  NodeDef *prefetch_node = function_utils::AddNode(
      "PrefetchDataset", "PrefetchDataset",
      {strings::StrCat(tensor_dataset_node->name(), ":handle:0"), "args_0"},
      {std::make_pair("output_shapes", shapes_attr),
       std::make_pair("output_types", types_attr)},
      fdef);

  AttrValue variant_type_attr;
  SetAttrValue(DT_VARIANT, &variant_type_attr);
  NodeDef *identity_node = function_utils::AddNode(
      "Identity", "Identity",
      {strings::StrCat(prefetch_node->name(), ":handle:0"),
       strings::StrCat("^", tensor_dataset_node->name())},
      {std::make_pair("T", variant_type_attr)}, fdef);

  (*fdef->mutable_ret())["identity"] =
      strings::StrCat(identity_node->name(), ":output:0");
  (*fdef->mutable_control_ret())[tensor_dataset_node->name()] =
      tensor_dataset_node->name();
  fdef->mutable_signature()->add_control_output(tensor_dataset_node->name());

  FunctionLibraryDefinition flib(OpRegistry::Global(), lib_def);

  TF_ASSERT_OK(
      MakeGrapplerFunctionItem(*fdef, flib, /*graph_def_version=*/27, &item));

  GraphDef output;
  Slack optimizer;
  tensorflow::RewriterConfig_CustomGraphOptimizer config;
  (*config.mutable_parameter_map())["slack_period"].set_s("8");
  TF_ASSERT_OK(optimizer.Init(&config));

  TF_ASSERT_OK(optimizer.Optimize(nullptr, item, &output));
  ASSERT_TRUE(graph_utils::ContainsNodeWithOp("PrefetchDataset", output));
  NodeDef optimized_prefetch_node =
      output.node(graph_utils::FindGraphNodeWithOp("PrefetchDataset", output));
  // Should not set slack for function items.
  EXPECT_EQ(optimized_prefetch_node.attr().at("slack_period").i(), 0);
}

}  // namespace
}  // namespace grappler
}  // namespace tensorflow
