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/*
* Copyright 2021 Google LLC
*
* 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.
*/
// fcp:google3-internal-file
#include "fcp/client/engine/tflite_plan_engine.h"
#include <algorithm>
#include <functional>
#include <memory>
#include <string>
#include <utility>
#include "absl/status/statusor.h"
#include "fcp/client/client_runner.h"
#include "fcp/client/diag_codes.pb.h"
#include "fcp/client/opstats/opstats_example_store.h"
#include "fcp/client/test_helpers.h"
#include "fcp/testing/testing.h"
#include "gmock/gmock.h"
#include "gtest/gtest.h"
#include "tensorflow/core/framework/tensor.pb.h"
#include "tensorflow/core/framework/tensor_shape.pb.h"
#include "tensorflow/core/protobuf/struct.pb.h"
namespace fcp {
namespace client {
namespace engine {
namespace {
using ::fcp::client::opstats::OpStatsSequence;
using ::google::internal::federated::plan::ClientOnlyPlan;
using ::google::internal::federated::plan::Dataset;
using ::google::internal::federated::plan::FederatedComputeEligibilityIORouter;
using ::google::internal::federated::plan::FederatedComputeIORouter;
using ::google::internal::federated::plan::LocalComputeIORouter;
using ::testing::Gt;
using ::testing::InSequence;
using ::testing::Invoke;
using ::testing::IsEmpty;
using ::testing::NiceMock;
using ::testing::Return;
using ::testing::StrictMock;
// We turn formatting off to prevent line breaks, which ensures that these paths
// are more easily code searchable.
// clang-format off
constexpr absl::string_view kArtifactPrefix =
"intelligence/brella/testing/tasks/mnist/simpleagg_mnist_training_tflite_task_artifacts"; // NOLINT
constexpr absl::string_view kEligibilityPlanArtifactPrefix =
"intelligence/brella/testing/tasks/eligibility_eval/eligibility_eval_tflite_task_artifacts"; // NOLINT
constexpr absl::string_view kSecaggArtifactPrefix =
"intelligence/brella/testing/tasks/secagg_only_tflite_task_artifacts";
constexpr absl::string_view kLcArtifactPrefix =
"intelligence/brella/testing/local_computation/mnist_tflite_personalization_artifacts"; // NOLINT
constexpr absl::string_view kLcInitialCheckpoint =
"intelligence/brella/testing/local_computation/initial.ckpt";
constexpr absl::string_view kConstantInputsArtifactPrefix =
"intelligence/brella/testing/tasks/mnist/simpleagg_constant_tflite_inputs_task_artifacts"; // NOLINT
// clang-format on
const char* const kCollectionUri = "app:/test_collection";
const char* const kEligibilityEvalCollectionUri =
"app:/test_eligibility_eval_collection";
const char* const kLcTrainCollectionUri = "app:/p13n_train_collection";
const char* const kLcTestCollectionUri = "app:/p13n_test_collection";
// Parameterized with whether per_phase_logs should be used.
class TfLitePlanEngineTest : public testing::Test {
protected:
void SetUp() override {
EXPECT_CALL(mock_opstats_logger_, IsOpStatsEnabled())
.WillRepeatedly(Return(true));
EXPECT_CALL(mock_opstats_logger_, GetOpStatsDb())
.WillRepeatedly(Return(&mock_opstats_db_));
EXPECT_CALL(mock_opstats_db_, Read())
.WillRepeatedly(Return(OpStatsSequence::default_instance()));
EXPECT_CALL(mock_flags_, ensure_dynamic_tensors_are_released())
.WillRepeatedly(Return(true));
EXPECT_CALL(mock_flags_, large_tensor_threshold_for_dynamic_allocation())
.WillRepeatedly(Return(1000));
EXPECT_CALL(mock_flags_, num_threads_for_tflite())
.WillRepeatedly(Return(4));
EXPECT_CALL(mock_flags_, disable_tflite_delegate_clustering())
.WillRepeatedly(Return(false));
EXPECT_CALL(mock_flags_, support_constant_tf_inputs())
.WillRepeatedly(Return(false));
}
void InitializeFlTask(absl::string_view prefix) {
LoadArtifacts();
example_iterator_factory_ =
std::make_unique<FunctionalExampleIteratorFactory>(
[&dataset = dataset_](
const google::internal::federated::plan::ExampleSelector&
selector) {
return std::make_unique<::fcp::client::SimpleExampleIterator>(
dataset);
});
// Compute dataset stats.
for (const Dataset::ClientDataset& client_dataset :
dataset_.client_data()) {
num_examples_ += client_dataset.example_size();
for (const std::string& example : client_dataset.example()) {
example_bytes_ += example.size();
}
}
// The single session FL plan specifies both input and output filepaths in
// its FederatedComputeIORouter.
FederatedComputeIORouter io_router =
client_only_plan_.phase().federated_compute();
if (!io_router.input_filepath_tensor_name().empty()) {
(*inputs_)[io_router.input_filepath_tensor_name()] = checkpoint_input_fd_;
}
checkpoint_output_filename_ =
files_impl_.CreateTempFile("output", ".ckp").value();
ASSERT_EQ(std::filesystem::file_size(checkpoint_output_filename_), 0);
int fd = open(checkpoint_output_filename_.c_str(), O_WRONLY);
ASSERT_NE(-1, fd);
checkpoint_output_fd_ = absl::StrCat("fd:///", fd);
if (!io_router.output_filepath_tensor_name().empty()) {
(*inputs_)[io_router.output_filepath_tensor_name()] =
checkpoint_output_fd_;
}
for (const auto& tensor_spec :
client_only_plan_.phase().tensorflow_spec().output_tensor_specs()) {
output_names_.push_back(tensor_spec.name());
}
}
void LoadArtifacts() {
absl::StatusOr<::fcp::client::ComputationArtifacts> artifacts =
::fcp::client::LoadFlArtifacts();
EXPECT_TRUE(artifacts.ok());
client_only_plan_ = std::move(artifacts->plan);
dataset_ = std::move(artifacts->dataset);
checkpoint_input_filename_ = artifacts->checkpoint_filepath;
int fd = open(checkpoint_input_filename_.c_str(), O_RDONLY);
ASSERT_NE(-1, fd);
checkpoint_input_fd_ = absl::StrCat("fd:///", fd);
}
void ComputeDatasetStats(const std::string& collection_uri) {
for (const Dataset::ClientDataset& client_dataset :
dataset_.client_data()) {
for (const Dataset::ClientDataset::SelectedExample& selected_example :
client_dataset.selected_example()) {
if (selected_example.selector().collection_uri() != collection_uri) {
continue;
}
num_examples_ += selected_example.example_size();
for (const auto& example : selected_example.example()) {
example_bytes_ += example.size();
}
}
}
}
fcp::client::FilesImpl files_impl_;
StrictMock<MockLogManager> mock_log_manager_;
StrictMock<MockOpStatsLogger> mock_opstats_logger_;
StrictMock<MockOpStatsDb> mock_opstats_db_;
StrictMock<MockFlags> mock_flags_;
std::unique_ptr<ExampleIteratorFactory> example_iterator_factory_;
// Never abort, by default.
std::function<bool()> should_abort_ = []() { return false; };
ClientOnlyPlan client_only_plan_;
Dataset dataset_;
std::string checkpoint_input_filename_;
std::string checkpoint_output_filename_;
std::string checkpoint_input_fd_;
std::string checkpoint_output_fd_;
int num_examples_ = 0;
int example_bytes_ = 0;
std::unique_ptr<absl::flat_hash_map<std::string, std::string>> inputs_ =
std::make_unique<absl::flat_hash_map<std::string, std::string>>();
std::vector<std::string> output_names_;
fcp::client::InterruptibleRunner::TimingConfig timing_config_ = {
// Use 10 ms to make the polling faster, otherwise the Abort test might
// fail because the plan finishes before interruption.
.polling_period = absl::Milliseconds(10),
.graceful_shutdown_period = absl::Milliseconds(1000),
.extended_shutdown_period = absl::Milliseconds(2000),
};
};
TEST_F(TfLitePlanEngineTest, SimpleAggPlanSucceeds) {
InitializeFlTask(kArtifactPrefix);
EXPECT_CALL(mock_log_manager_,
LogDiag(ProdDiagCode::BACKGROUND_TRAINING_TFLITE_ENGINE_USED));
EXPECT_CALL(
mock_opstats_logger_,
UpdateDatasetStats(kCollectionUri, num_examples_, example_bytes_));
TfLitePlanEngine plan_engine({example_iterator_factory_.get()}, should_abort_,
&mock_log_manager_, &mock_opstats_logger_,
&mock_flags_, &timing_config_);
engine::PlanResult result = plan_engine.RunPlan(
client_only_plan_.phase().tensorflow_spec(),
client_only_plan_.tflite_graph(), std::move(inputs_), output_names_);
EXPECT_THAT(result.outcome, PlanOutcome::kSuccess);
EXPECT_THAT(result.output_tensors.size(), 0);
EXPECT_THAT(result.output_names.size(), 0);
EXPECT_EQ(result.example_stats.example_count, num_examples_);
EXPECT_EQ(result.example_stats.example_size_bytes, example_bytes_);
EXPECT_GT(std::filesystem::file_size(checkpoint_output_filename_), 0);
}
} // namespace
} // namespace engine
} // namespace client
} // namespace fcp
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