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// Copyright 2021 The Chromium Authors
// Use of this source code is governed by a BSD-style license that can be
// found in the LICENSE file.
#include "components/optimization_guide/core/bert_model_executor.h"
#include "base/trace_event/trace_event.h"
#include "base/types/expected.h"
#include "build/build_config.h"
#include "components/optimization_guide/core/model_util.h"
#include "components/optimization_guide/core/optimization_guide_features.h"
#include "components/optimization_guide/core/tflite_op_resolver.h"
#include "third_party/tflite_support/src/tensorflow_lite_support/cc/task/text/bert_nl_classifier.h"
namespace optimization_guide {
BertModelExecutor::BertModelExecutor(
proto::OptimizationTarget optimization_target)
: optimization_target_(optimization_target),
num_threads_(features::OverrideNumThreadsForOptTarget(optimization_target)
.value_or(-1)) {}
BertModelExecutor::~BertModelExecutor() = default;
std::optional<std::vector<tflite::task::core::Category>>
BertModelExecutor::Execute(ModelExecutionTask* execution_task,
ExecutionStatus* out_status,
const std::string& input) {
if (input.empty()) {
*out_status = ExecutionStatus::kErrorEmptyOrInvalidInput;
return std::nullopt;
}
TRACE_EVENT2("browser", "BertModelExecutor::Execute", "optimization_target",
GetStringNameForOptimizationTarget(optimization_target_),
"input_length", input.size());
auto status_or_result =
static_cast<tflite::task::text::BertNLClassifier*>(execution_task)
->ClassifyText(input);
if (absl::IsCancelled(status_or_result.status())) {
*out_status = ExecutionStatus::kErrorCancelled;
return std::nullopt;
}
if (!status_or_result.ok()) {
*out_status = ExecutionStatus::kErrorUnknown;
return std::nullopt;
}
*out_status = ExecutionStatus::kSuccess;
return *status_or_result;
}
base::expected<std::unique_ptr<BertModelExecutor::ModelExecutionTask>,
ExecutionStatus>
BertModelExecutor::BuildModelExecutionTask(base::File& model_file) {
tflite::task::text::BertNLClassifierOptions options;
auto* mutable_file_descriptor_meta = options.mutable_base_options()
->mutable_model_file()
->mutable_file_descriptor_meta();
#if BUILDFLAG(IS_WIN)
mutable_file_descriptor_meta->set_handle(
reinterpret_cast<uint64_t>(model_file.GetPlatformFile()));
#else
mutable_file_descriptor_meta->set_fd(model_file.GetPlatformFile());
#endif
options.mutable_base_options()
->mutable_compute_settings()
->mutable_tflite_settings()
->mutable_cpu_settings()
->set_num_threads(num_threads_);
auto maybe_nl_classifier =
tflite::task::text::BertNLClassifier::CreateFromOptions(
std::move(options), std::make_unique<TFLiteOpResolver>());
if (maybe_nl_classifier.ok())
return std::move(maybe_nl_classifier.value());
DLOG(ERROR) << "Unable to load BERT model: "
<< maybe_nl_classifier.status().ToString();
return base::unexpected(ExecutionStatus::kErrorModelFileNotValid);
}
} // namespace optimization_guide
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