experiments/STT-tensorflow
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change and cleanup per review

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This commit is contained in:
Koan-Sin Tan 2020-05-13 15:35:18 +08:00
parent efa921a770
commit a88c46347c
11 changed files with 7 additions and 38 deletions

9
tensorflow/lite/delegates/nnapi/nnapi_delegate.cc
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@ -3151,7 +3151,7 @@ TfLiteStatus NNAPIDelegateKernel::Init(TfLiteContext* context,
"creating NNAPI model", nnapi_errno);
nn_model_.reset(model);
TF_LITE_ENSURE_STATUS(BuildGraph(context, params->delegate,
TF_LITE_ENSURE_STATUS(BuildGraph(context, delegate_options,
params->input_tensors,
params->output_tensors, nnapi_errno));
}
@ -3203,7 +3203,6 @@ TfLiteStatus NNAPIDelegateKernel::Prepare(TfLiteContext* context,
const auto delegate_options =
StatefulNnApiDelegate::GetOptions(node->delegate);
ANeuralNetworksCompilation* compilation = nullptr;
if (!nnapi_devices_.empty()) {
// Compile for the selected accelerator.
@ -3877,7 +3876,8 @@ TfLiteStatus NNAPIDelegateKernel::AddOpsAndTensors(TfLiteContext* context,
}
TfLiteStatus NNAPIDelegateKernel::BuildGraph(
TfLiteContext* context, TfLiteDelegate* delegate,
TfLiteContext* context,
const StatefulNnApiDelegate::Options& delegate_options,
const TfLiteIntArray* input_tensors, const TfLiteIntArray* output_tensors,
int* nnapi_errno) {
// Build the ops and tensors.
@ -3888,7 +3888,6 @@ TfLiteStatus NNAPIDelegateKernel::BuildGraph(
std::vector<uint32_t> outputs;
outputs.reserve(output_tensors->size);
const auto delegate_options = StatefulNnApiDelegate::GetOptions(delegate);
size_t total_input_byte_size = 0;
// Make the TensorFlow Lite inputs and outputs to ann_indices.
for (int i : TfLiteIntArrayView(input_tensors)) {
@ -4025,9 +4024,9 @@ StatefulNnApiDelegate::StatefulNnApiDelegate(const NnApi* nnapi,
delegate_data_.disallow_nnapi_cpu = options.disallow_nnapi_cpu;
delegate_data_.max_number_delegated_partitions =
options.max_number_delegated_partitions;
delegate_data_.allow_fp16 = options.allow_fp16;
TFLITE_LOG_PROD_ONCE(tflite::TFLITE_LOG_INFO,
"Created TensorFlow Lite delegate for NNAPI.");
delegate_data_.allow_fp16 = options.allow_fp16;
Prepare = DoPrepare;
CopyFromBufferHandle = DoCopyFromBufferHandle;
CopyToBufferHandle = DoCopyToBufferHandle;

4
tensorflow/lite/delegates/nnapi/nnapi_delegate_kernel.h
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@ -349,8 +349,8 @@ class NNAPIDelegateKernel {
TfLiteStatus AddOpsAndTensors(TfLiteContext* context, int* nnapi_errno);
TfLiteStatus BuildGraph(TfLiteContext* context,
TfLiteDelegate* delegate,
const TfLiteIntArray* input_tensors,
const StatefulNnApiDelegate::Options& options,
const TfLiteIntArray* input_tensors,
const TfLiteIntArray* output_tensors,
int* nnapi_errno);
};

2
tensorflow/lite/tools/accuracy/ilsvrc/imagenet_model_evaluator.cc
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@ -141,8 +141,6 @@ class CompositeObserver : public ImagenetModelEvaluator::Observer {
tflite::Flag::CreateFlag(kNumRanksFlag, &params.num_ranks,
"Generates the top-1 to top-k accuracy values"
"where k = num_ranks. Default: 10"),
tflite::Flag::CreateFlag("nnapi_allow_fp16", &params.nnapi_allow_fp16,
"allow fp16 in nnapi"),
};
tflite::Flags::Parse(argc, const_cast<const char**>(argv), flag_list);

3
tensorflow/lite/tools/accuracy/ilsvrc/imagenet_model_evaluator.h
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@ -78,9 +78,6 @@ class ImagenetModelEvaluator {
// Number of interpreter threads.
int num_interpreter_threads = 1;
// allow fp16
bool nnapi_allow_fp16 = false;
};
// An evaluation observer.

3
tensorflow/lite/tools/benchmark/benchmark_performance_options.cc
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@ -303,9 +303,6 @@ void BenchmarkPerformanceOptions::CreatePerformanceOptions() {
BenchmarkParam::Create<bool>(false));
params.AddParam("max_delegated_partitions",
BenchmarkParam::Create<int>(0));
params.AddParam("max_delegated_partitions",
params.AddParam("nnapi_allow_fp16",
BenchmarkParam::Create<bool>(false));
all_run_params_.emplace_back(std::move(params));
}
}

4
tensorflow/lite/tools/delegates/default_execution_provider.cc
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@ -30,7 +30,6 @@ class DefaultExecutionProvider : public DelegateProvider {
ToolParam::Create<int32_t>(0));
default_params_.AddParam("min_nodes_per_partition",
ToolParam::Create<int32_t>(0));
default_params_.AddParam("allow_fp16", ToolParam::Create<bool>(false));
}
std::vector<Flag> CreateFlags(ToolParams* params) const final;
@ -45,7 +44,6 @@ std::vector<Flag> DefaultExecutionProvider::CreateFlags(
std::vector<Flag> flags = {
CreateFlag<int32_t>("num_threads", params,
"number of threads used for inference on CPU."),
CreateFlag<bool>("allow_fp16", params, "allow_fp16"),
CreateFlag<int32_t>("max_delegated_partitions", params,
"Max number of partitions to be delegated."),
CreateFlag<int32_t>(
@ -63,8 +61,6 @@ void DefaultExecutionProvider::LogParams(const ToolParams& params) const {
<< params.Get<int32_t>("max_delegated_partitions") << "]";
TFLITE_LOG(INFO) << "Min nodes per partition : ["
<< params.Get<int32_t>("min_nodes_per_partition") << "]";
TFLITE_LOG(INFO) << "allow_fp16: ["
<< params.Get<bool>("allow_fp16") << "]";
}
TfLiteDelegatePtr DefaultExecutionProvider::CreateTfLiteDelegate(

2
tensorflow/lite/tools/delegates/nnapi_delegate_provider.cc
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@ -88,7 +88,7 @@ void NnapiDelegateProvider::LogParams(const ToolParams& params) const {
<< params.Get<bool>("disable_nnapi_cpu") << "]";
}
if (params.Get<bool>("nnapi_allow_fp16")) {
TFLITE_LOG(INFO) << "nnapi_allow_fp16: ["
TFLITE_LOG(INFO) << "Allow fp16 in NNAPI: ["
<< params.Get<bool>("nnapi_allow_fp16") << "]";
}
}

4
tensorflow/lite/tools/evaluation/evaluation_delegate_provider.cc
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@ -132,10 +132,6 @@ tools::ToolParams DelegateProviders::GetAllParams(
tool_params.Set<int32_t>("num_threads", params.num_threads());
}
if (params.has_nnapi_allow_fp16()) {
tool_params.Set<bool>("nnapi_allow_fp16", params.nnapi_allow_fp16());
}
const auto type = params.delegate();
switch (type) {
case TfliteInferenceParams::NNAPI:

5
tensorflow/lite/tools/evaluation/tasks/coco_object_detection/run_eval.cc
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@ -65,7 +65,6 @@ class CocoObjectDetection : public TaskExecutor {
bool debug_mode_;
std::string delegate_;
int num_interpreter_threads_;
bool allow_fp16_;
DelegateProviders delegate_providers_;
};
@ -105,9 +104,6 @@ CocoObjectDetection::CocoObjectDetection(int* argc, char* argv[])
kDelegateFlag, &delegate_,
"Delegate to use for inference, if available. "
"Must be one of {'nnapi', 'gpu', 'xnnpack', 'hexagon'}"),
tflite::Flag::CreateFlag(
"nnapi_allow_fp16", &allow_fp16_,
"nnapi allow fp16"),
};
tflite::Flags::Parse(argc, const_cast<const char**>(argv), flag_list);
DelegateProviders delegate_providers;
@ -136,7 +132,6 @@ absl::optional<EvaluationStageMetrics> CocoObjectDetection::Run() {
inference_params->set_model_file_path(model_file_path_);
inference_params->set_num_threads(num_interpreter_threads_);
inference_params->set_delegate(ParseStringToDelegateType(delegate_));
inference_params->set_nnapi_allow_fp16(allow_fp16_);
// Get ground truth data.
absl::flat_hash_map<std::string, ObjectDetectionResult> ground_truth_map;

5
tensorflow/lite/tools/evaluation/tasks/imagenet_image_classification/run_eval.cc
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@ -67,7 +67,6 @@ class ImagenetClassification : public TaskExecutor {
std::string delegate_;
int num_images_;
int num_interpreter_threads_;
bool allow_fp16_;
DelegateProviders delegate_providers_;
};
@ -107,9 +106,6 @@ ImagenetClassification::ImagenetClassification(int* argc, char* argv[])
kDelegateFlag, &delegate_,
"Delegate to use for inference, if available. "
"Must be one of {'nnapi', 'gpu', 'hexagon', 'xnnpack'}"),
tflite::Flag::CreateFlag(
"nnapi_allow_fp16", &allow_fp16_,
"nnapi allow fp16"),
};
tflite::Flags::Parse(argc, const_cast<const char**>(argv), flag_list);
delegate_providers_.InitFromCmdlineArgs(argc, const_cast<const char**>(argv));
@ -159,7 +155,6 @@ absl::optional<EvaluationStageMetrics> ImagenetClassification::Run() {
inference_params->set_model_file_path(model_file_path_);
inference_params->set_num_threads(num_interpreter_threads_);
inference_params->set_delegate(ParseStringToDelegateType(delegate_));
inference_params->set_nnapi_allow_fp16(allow_fp16_);
classification_params->mutable_topk_accuracy_eval_params()->set_k(10);
ImageClassificationStage eval(eval_config);

4
tensorflow/lite/tools/evaluation/tasks/inference_diff/run_eval.cc
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@ -50,7 +50,6 @@ class InferenceDiff : public TaskExecutor {
std::string delegate_;
int num_runs_;
int num_interpreter_threads_;
bool allow_fp16_;
DelegateProviders delegate_providers_;
};
@ -72,8 +71,6 @@ InferenceDiff::InferenceDiff(int* argc, char* argv[])
kDelegateFlag, &delegate_,
"Delegate to use for test inference, if available. "
"Must be one of {'nnapi', 'gpu', 'hexagon', 'xnnpack'}"),
tflite::Flag::CreateFlag("nnapi_allow_fp16", &allow_fp16_,
"nnapi allow fp16")
};
tflite::Flags::Parse(argc, const_cast<const char**>(argv), flag_list);
delegate_providers_.InitFromCmdlineArgs(argc, const_cast<const char**>(argv));
@ -91,7 +88,6 @@ absl::optional<EvaluationStageMetrics> InferenceDiff::Run() {
// generating random data.
inference_params->set_invocations_per_run(3);
inference_params->set_delegate(ParseStringToDelegateType(delegate_));
inference_params->set_nnapi_allow_fp16(allow_fp16_);
if (!delegate_.empty() &&
inference_params->delegate() == TfliteInferenceParams::NONE) {
TFLITE_LOG(WARN) << "Unsupported TFLite delegate: " << delegate_;