/* Copyright 2018 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/compiler/jit/create_xla_launch_op.h"

#include "absl/memory/memory.h"
#include "tensorflow/core/common_runtime/device_factory.h"
#include "tensorflow/core/common_runtime/function.h"
#include "tensorflow/core/framework/function_testlib.h"
#include "tensorflow/core/framework/node_def_builder.h"
#include "tensorflow/core/framework/tensor_testutil.h"
#include "tensorflow/core/lib/core/status.h"
#include "tensorflow/core/platform/test.h"
#include "tensorflow/core/public/session_options.h"
#include "tensorflow/core/public/version.h"
#include "tensorflow/core/util/ptr_util.h"

namespace tensorflow {

NodeDef ToNodeDef(const string& text) {
  NodeDef node_def;
  EXPECT_TRUE(protobuf::TextFormat::MergeFromString(text, &node_def));
  return node_def;
}

// Create a FunctionDef that takes one resource and one regular param
FunctionDef XTimesY() {
  return FunctionDefHelper::Define(
      // Name
      "XTimesY",
      // Args
      {"x: float", "y: resource"},
      // Return values
      {"z: float"},
      // Attr def
      {},
      // Nodes
      {
          {{"y0"}, "ReadVariableOp", {"y"}, {{"dtype", DT_FLOAT}}},
          {{"z"}, "Mul", {"x", "y0"}, {{"T", DT_FLOAT}}},
      });
}

class CreateXlaLaunchOpTest : public ::testing::Test {
 protected:
  void Init(const std::vector<FunctionDef>& flib) {
    SessionOptions options;
    auto* device_count = options.config.mutable_device_count();
    device_count->insert({"CPU", 1});
    TF_CHECK_OK(DeviceFactory::AddDevices(
        options, "/job:localhost/replica:0/task:0", &devices_));

    FunctionDefLibrary proto;
    for (const auto& fdef : flib) {
      *(proto.add_function()) = fdef;
    }
    lib_def_ = absl::make_unique<FunctionLibraryDefinition>(
        OpRegistry::Global(), proto);
    OptimizerOptions opts;
    device_mgr_ = absl::make_unique<DeviceMgr>(devices_);
    pflr_ = absl::make_unique<ProcessFunctionLibraryRuntime>(
        device_mgr_.get(), Env::Default(), TF_GRAPH_DEF_VERSION, lib_def_.get(),
        opts, /*default_thread_pool=*/nullptr, /*cluster_flr=*/nullptr);
    flr_ = pflr_->GetFLR("/job:localhost/replica:0/task:0/cpu:0");
  }

  FunctionLibraryRuntime* flr_;
  std::vector<Device*> devices_;
  std::unique_ptr<DeviceMgr> device_mgr_;
  std::unique_ptr<FunctionLibraryDefinition> lib_def_;
  std::unique_ptr<ProcessFunctionLibraryRuntime> pflr_;

  std::unique_ptr<OpKernel> kernel_;
};

AttrValue BoolAttr(bool b) {
  AttrValue v;
  v.set_b(b);
  return v;
}

TEST_F(CreateXlaLaunchOpTest, OneFloatOneResourceArgument) {
  FunctionDef fdef = XTimesY();
  (*fdef.mutable_attr())["_XlaCompile"] = BoolAttr(true);
  Init({fdef});

  Status status = CreateXlaLaunchOp(
      flr_, ToNodeDef(R"pb(
        name: 'XTimesY' op: 'XTimesY' input: 'a' input: 'b'
      )pb"), &kernel_);
  ASSERT_TRUE(status.ok()) << status.ToString();

  EXPECT_EQ("XTimesY", kernel_->name());
  EXPECT_EQ("XTimesY", kernel_->type_string());

  EXPECT_EQ(2, kernel_->num_inputs());
  EXPECT_EQ(DT_FLOAT, kernel_->input_type(0));
  EXPECT_EQ(DT_RESOURCE, kernel_->input_type(1));
  EXPECT_EQ(DEVICE_MEMORY, kernel_->input_memory_types()[0]);
  EXPECT_EQ(HOST_MEMORY, kernel_->input_memory_types()[1]);

  EXPECT_EQ(1, kernel_->num_outputs());
  EXPECT_EQ(DT_FLOAT, kernel_->output_type(0));
  EXPECT_EQ(DEVICE_MEMORY, kernel_->output_memory_types()[0]);
}

TEST_F(CreateXlaLaunchOpTest, FailsIfXlaCompileAttrNotSet) {
  FunctionDef fdef = XTimesY();
  Init({fdef});

  Status status = CreateXlaLaunchOp(flr_, ToNodeDef(R"proto(
                                      name: 'XTimesY'
                                      op: 'XTimesY'
                                      input: 'a'
                                      input: 'b'
                                    )proto"), &kernel_);
  EXPECT_TRUE(errors::IsInvalidArgument(status)) << status.ToString();
}

TEST_F(CreateXlaLaunchOpTest, FailsIfXlaCompileAttrIsSetToFalse) {
  FunctionDef fdef = XTimesY();
  (*fdef.mutable_attr())["_XlaCompile"] = BoolAttr(false);
  Init({fdef});

  Status status = CreateXlaLaunchOp(flr_, ToNodeDef(R"proto(
                                      name: 'XTimesY'
                                      op: 'XTimesY'
                                      input: 'a'
                                      input: 'b'
                                    )proto"), &kernel_);
  EXPECT_TRUE(errors::IsInvalidArgument(status)) << status.ToString();
}

}  // namespace tensorflow
