Qualify uses of std::string
PiperOrigin-RevId: 317003622 Change-Id: Iae6a9a287ffd3b97dee8b9993c443db322936592
This commit is contained in:
A. Unique TensorFlower
TensorFlower Gardener
parent
adf0573f9d
commit
56db128697
@ -34,8 +34,8 @@ namespace toco {
|
||||
|
||||
namespace {
|
||||
|
||||
string TryGetOperatorName(const Operator& op) {
|
||||
string op_name;
|
||||
std::string TryGetOperatorName(const Operator& op) {
|
||||
std::string op_name;
|
||||
if (!op.tensorflow_node_def.empty()) {
|
||||
// Parse op name from serialized NodeDef.
|
||||
tensorflow::NodeDef node_def;
|
||||
@ -63,8 +63,8 @@ string TryGetOperatorName(const Operator& op) {
|
||||
return op_name;
|
||||
}
|
||||
|
||||
string GetOSVersion() {
|
||||
string os_info;
|
||||
std::string GetOSVersion() {
|
||||
std::string os_info;
|
||||
#ifdef __linux__
|
||||
utsname info;
|
||||
if (uname(&info)) {
|
||||
@ -72,12 +72,13 @@ string GetOSVersion() {
|
||||
LOG(ERROR) << "Cannot get OS info.";
|
||||
return "";
|
||||
}
|
||||
os_info = string(info.sysname) + ";OSVer=" + string(info.release) + ";";
|
||||
os_info =
|
||||
std::string(info.sysname) + ";OSVer=" + std::string(info.release) + ";";
|
||||
#endif
|
||||
return os_info;
|
||||
}
|
||||
|
||||
string ShapeToStringNoSpace(const Shape& shape) {
|
||||
std::string ShapeToStringNoSpace(const Shape& shape) {
|
||||
if (shape.dimensions_count() == 0) {
|
||||
return "[]";
|
||||
}
|
||||
@ -85,13 +86,13 @@ string ShapeToStringNoSpace(const Shape& shape) {
|
||||
return absl::StrCat("[", absl::StrJoin(shape.dims(), ","), "]");
|
||||
}
|
||||
|
||||
string GetOperatorSignature(
|
||||
std::string GetOperatorSignature(
|
||||
const Model& model, const Operator& op,
|
||||
const std::map<OperatorType, std::unique_ptr<tflite::BaseOperator>>&
|
||||
op_types_map) {
|
||||
// The signature of an op has the following schema:
|
||||
// INPUT:SHAPE::TYPE::OUTPUT:SHAPE::TYPE::NAME:VERSION:
|
||||
string op_signature;
|
||||
std::string op_signature;
|
||||
constexpr char delimiter[] = "::";
|
||||
|
||||
// Get input shapes and types.
|
||||
@ -137,8 +138,8 @@ string GetOperatorSignature(
|
||||
|
||||
} // namespace
|
||||
|
||||
std::vector<string> GetOperatorNames(const Model& model) {
|
||||
std::vector<string> op_names;
|
||||
std::vector<std::string> GetOperatorNames(const Model& model) {
|
||||
std::vector<std::string> op_names;
|
||||
for (const auto& op : model.operators) {
|
||||
op_names.push_back(TryGetOperatorName(*op));
|
||||
}
|
||||
@ -146,9 +147,9 @@ std::vector<string> GetOperatorNames(const Model& model) {
|
||||
}
|
||||
|
||||
void CountOperatorsByType(const Model& model,
|
||||
std::map<string, int>* built_in_ops,
|
||||
std::map<string, int>* custom_ops,
|
||||
std::map<string, int>* select_ops) {
|
||||
std::map<std::string, int>* built_in_ops,
|
||||
std::map<std::string, int>* custom_ops,
|
||||
std::map<std::string, int>* select_ops) {
|
||||
for (const auto& op : model.operators) {
|
||||
OperatorSignature op_signature = {op.get(), &model};
|
||||
const auto ops_by_type =
|
||||
@ -156,7 +157,7 @@ void CountOperatorsByType(const Model& model,
|
||||
tflite::details::OperatorKey op_key(op_signature, ops_by_type,
|
||||
true /*enable_select_tf_ops*/);
|
||||
|
||||
const string op_name = TryGetOperatorName(*op);
|
||||
const std::string op_name = TryGetOperatorName(*op);
|
||||
if (op_key.is_custom_op()) {
|
||||
(*custom_ops)[op_name]++;
|
||||
} else if (op_key.is_flex_op()) {
|
||||
@ -168,8 +169,9 @@ void CountOperatorsByType(const Model& model,
|
||||
}
|
||||
|
||||
void GetInputAndOutputTypes(
|
||||
const Model& model, TFLITE_PROTO_NS::RepeatedPtrField<string>* input_types,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string>* output_types) {
|
||||
const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* input_types,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* output_types) {
|
||||
for (const auto& input_array : model.flags.input_arrays()) {
|
||||
const Array& array = model.GetArray(input_array.name());
|
||||
input_types->Add(ArrayDataTypeName(array.data_type));
|
||||
@ -180,15 +182,16 @@ void GetInputAndOutputTypes(
|
||||
}
|
||||
}
|
||||
|
||||
string GetTfLiteVersion() { return TFLITE_VERSION_STRING; }
|
||||
std::string GetTfLiteVersion() { return TFLITE_VERSION_STRING; }
|
||||
|
||||
string GetCachedOSVersion() {
|
||||
static string* version = new string(GetOSVersion());
|
||||
std::string GetCachedOSVersion() {
|
||||
static std::string* version = new std::string(GetOSVersion());
|
||||
return *version;
|
||||
}
|
||||
|
||||
void GetOpSignatures(const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string>* op_signatures) {
|
||||
void GetOpSignatures(
|
||||
const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* op_signatures) {
|
||||
const auto& op_types_map =
|
||||
tflite::BuildOperatorByTypeMap(true /*enable_select_tf_ops*/);
|
||||
for (const auto& op : model.operators) {
|
||||
@ -196,7 +199,7 @@ void GetOpSignatures(const Model& model,
|
||||
}
|
||||
}
|
||||
|
||||
string GetModelHash(const Model& model) {
|
||||
std::string GetModelHash(const Model& model) {
|
||||
// TODO(b/123519920): Implement the hash function for Model.
|
||||
// Need to consider different implementations for public/private models.
|
||||
return "";
|
||||
@ -204,18 +207,18 @@ string GetModelHash(const Model& model) {
|
||||
|
||||
// This function scans through the error message string, extracts the part about
|
||||
// missing ops and prunes away all other information in the error info.
|
||||
string SanitizeErrorMessage(const string& error_message) {
|
||||
const string s1 = "Ops that can be supported by the flex runtime";
|
||||
const string s2 = "Ops that need custom implementation";
|
||||
string pruned_message;
|
||||
std::string SanitizeErrorMessage(const std::string& error_message) {
|
||||
const std::string s1 = "Ops that can be supported by the flex runtime";
|
||||
const std::string s2 = "Ops that need custom implementation";
|
||||
std::string pruned_message;
|
||||
size_t pos = error_message.find(s1);
|
||||
if (pos != string::npos) {
|
||||
if (pos != std::string::npos) {
|
||||
// Find the terminate point for flex op list.
|
||||
auto end = error_message.find(".", pos);
|
||||
pruned_message.append(error_message.substr(pos, end - pos + 1));
|
||||
}
|
||||
pos = error_message.find(s2);
|
||||
if (pos != string::npos) {
|
||||
if (pos != std::string::npos) {
|
||||
// Find the terminate point for custom op list.
|
||||
auto end = error_message.find(".", pos);
|
||||
pruned_message.append(error_message.substr(pos, end - pos + 1));
|
||||
@ -225,18 +228,18 @@ string SanitizeErrorMessage(const string& error_message) {
|
||||
|
||||
void PopulateConversionLog(const Model& model, TocoConversionLog* log) {
|
||||
// Get the list of ops after conversion.
|
||||
const std::vector<string> op_names = GetOperatorNames(model);
|
||||
const std::vector<std::string> op_names = GetOperatorNames(model);
|
||||
for (const auto& op_name : op_names) {
|
||||
log->add_op_list(op_name);
|
||||
}
|
||||
|
||||
// Get op signatures.
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string> op_signatures;
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string> op_signatures;
|
||||
GetOpSignatures(model, &op_signatures);
|
||||
log->mutable_op_signatures()->CopyFrom(op_signatures);
|
||||
|
||||
// Get op counts by category: custom, built-in or select.
|
||||
std::map<string, int> custom_ops, select_ops, built_in_ops;
|
||||
std::map<std::string, int> custom_ops, select_ops, built_in_ops;
|
||||
CountOperatorsByType(model, &built_in_ops, &custom_ops, &select_ops);
|
||||
log->mutable_custom_ops()->insert(custom_ops.cbegin(), custom_ops.cend());
|
||||
log->mutable_built_in_ops()->insert(built_in_ops.cbegin(),
|
||||
@ -244,7 +247,7 @@ void PopulateConversionLog(const Model& model, TocoConversionLog* log) {
|
||||
log->mutable_select_ops()->insert(select_ops.cbegin(), select_ops.cend());
|
||||
|
||||
// Get the model's input and output types.
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string> input_types, output_types;
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string> input_types, output_types;
|
||||
GetInputAndOutputTypes(model, &input_types, &output_types);
|
||||
log->mutable_input_tensor_types()->CopyFrom(input_types);
|
||||
log->mutable_output_tensor_types()->CopyFrom(output_types);
|
||||
|
||||
@ -25,37 +25,39 @@ namespace toco {
|
||||
|
||||
// This function scans through the error message string, extracts the part about
|
||||
// missing ops and prunes away all other information in the error info.
|
||||
string SanitizeErrorMessage(const string& error_message);
|
||||
std::string SanitizeErrorMessage(const std::string& error_message);
|
||||
|
||||
// Populates the TocoConversionLog proto after analyzing the model.
|
||||
void PopulateConversionLog(const Model& model, TocoConversionLog* log);
|
||||
|
||||
// Returns the names of the operators in the model.
|
||||
std::vector<string> GetOperatorNames(const Model& model);
|
||||
std::vector<std::string> GetOperatorNames(const Model& model);
|
||||
|
||||
// Counts the number of different types of operators in the model:
|
||||
// Built-in ops, custom ops and select ops.
|
||||
// Each map is mapping from the name of the operator (such as 'Conv') to its
|
||||
// total number of occurrences in the model.
|
||||
void CountOperatorsByType(const Model& model,
|
||||
std::map<string, int>* built_in_ops,
|
||||
std::map<string, int>* custom_ops,
|
||||
std::map<string, int>* select_ops);
|
||||
std::map<std::string, int>* built_in_ops,
|
||||
std::map<std::string, int>* custom_ops,
|
||||
std::map<std::string, int>* select_ops);
|
||||
|
||||
// Gets the input and output types of the model. The input and output is
|
||||
// specified by model.flags.input_arrays and model.flags.output_arrays.
|
||||
void GetInputAndOutputTypes(
|
||||
const Model& model, TFLITE_PROTO_NS::RepeatedPtrField<string>* input_types,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string>* output_types);
|
||||
const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* input_types,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* output_types);
|
||||
|
||||
// Calculates signatures for all the ops in the model. An op signature is
|
||||
// defined by its input/output shapes and types, op name and its version.
|
||||
void GetOpSignatures(const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string>* op_signatures);
|
||||
void GetOpSignatures(
|
||||
const Model& model,
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string>* op_signatures);
|
||||
|
||||
// TODO(b/123519920): Implement this.
|
||||
// Calculates a unique hash for the model.
|
||||
string GetModelHash(const Model& model);
|
||||
std::string GetModelHash(const Model& model);
|
||||
|
||||
} // namespace toco
|
||||
|
||||
|
||||
@ -58,9 +58,9 @@ TEST(ConversionLogUtilTest, TestCountOperatorsByType) {
|
||||
Model model;
|
||||
// 1st Conv operator.
|
||||
std::unique_ptr<ConvOperator> conv1(new ConvOperator());
|
||||
const string conv1_input_name = "conv_input1";
|
||||
const string conv1_filter_name = "conv_filter1";
|
||||
const string conv1_output_name = "conv_output1";
|
||||
const std::string conv1_input_name = "conv_input1";
|
||||
const std::string conv1_filter_name = "conv_filter1";
|
||||
const std::string conv1_output_name = "conv_output1";
|
||||
conv1->inputs.push_back(conv1_input_name);
|
||||
conv1->inputs.push_back(conv1_filter_name);
|
||||
conv1->outputs.push_back(conv1_output_name);
|
||||
@ -71,9 +71,9 @@ TEST(ConversionLogUtilTest, TestCountOperatorsByType) {
|
||||
|
||||
// 2nd Conv operator.
|
||||
std::unique_ptr<ConvOperator> conv2(new ConvOperator());
|
||||
const string conv2_input_name = "conv_input2";
|
||||
const string conv2_filter_name = "conv_filter2";
|
||||
const string conv2_output_name = "conv_output2";
|
||||
const std::string conv2_input_name = "conv_input2";
|
||||
const std::string conv2_filter_name = "conv_filter2";
|
||||
const std::string conv2_output_name = "conv_output2";
|
||||
conv2->inputs.push_back(conv2_input_name);
|
||||
conv2->inputs.push_back(conv2_filter_name);
|
||||
conv2->outputs.push_back(conv2_output_name);
|
||||
@ -83,7 +83,7 @@ TEST(ConversionLogUtilTest, TestCountOperatorsByType) {
|
||||
|
||||
// Mean operator.
|
||||
std::unique_ptr<MeanOperator> mean(new MeanOperator());
|
||||
const string mean_input_name = "mean_input";
|
||||
const std::string mean_input_name = "mean_input";
|
||||
mean->inputs.push_back(mean_input_name);
|
||||
array_map[mean_input_name] = std::unique_ptr<Array>(new Array);
|
||||
|
||||
@ -111,26 +111,26 @@ TEST(ConversionLogUtilTest, TestCountOperatorsByType) {
|
||||
model.operators.push_back(std::move(elu_grad));
|
||||
model.operators.push_back(std::move(my_custom_op));
|
||||
|
||||
std::map<string, int> built_in_ops, select_ops, custom_ops;
|
||||
std::map<std::string, int> built_in_ops, select_ops, custom_ops;
|
||||
CountOperatorsByType(model, &built_in_ops, &custom_ops, &select_ops);
|
||||
|
||||
EXPECT_THAT(built_in_ops,
|
||||
UnorderedElementsAre(std::pair<string, int>("Conv", 2),
|
||||
std::pair<string, int>("Mean", 1)));
|
||||
UnorderedElementsAre(std::pair<std::string, int>("Conv", 2),
|
||||
std::pair<std::string, int>("Mean", 1)));
|
||||
EXPECT_THAT(select_ops,
|
||||
UnorderedElementsAre(std::pair<string, int>("AvgPool3D", 1),
|
||||
std::pair<string, int>("EluGrad", 1)));
|
||||
EXPECT_THAT(custom_ops, UnorderedElementsAre(
|
||||
std::pair<string, int>("MyAwesomeCustomOp", 1)));
|
||||
UnorderedElementsAre(std::pair<std::string, int>("AvgPool3D", 1),
|
||||
std::pair<std::string, int>("EluGrad", 1)));
|
||||
EXPECT_THAT(custom_ops, UnorderedElementsAre(std::pair<std::string, int>(
|
||||
"MyAwesomeCustomOp", 1)));
|
||||
}
|
||||
|
||||
TEST(ConversionLogUtilTest, TestGetInputAndOutputTypes) {
|
||||
Model model;
|
||||
auto& array_map = model.GetMutableArrayMap();
|
||||
const string input1 = "conv_input";
|
||||
const string input2 = "conv_filter";
|
||||
const string input3 = "feature";
|
||||
const string output = "softmax";
|
||||
const std::string input1 = "conv_input";
|
||||
const std::string input2 = "conv_filter";
|
||||
const std::string input3 = "feature";
|
||||
const std::string output = "softmax";
|
||||
array_map[input1] = std::unique_ptr<Array>(new Array);
|
||||
array_map[input1]->data_type = ArrayDataType::kFloat;
|
||||
array_map[input2] = std::unique_ptr<Array>(new Array);
|
||||
@ -149,7 +149,7 @@ TEST(ConversionLogUtilTest, TestGetInputAndOutputTypes) {
|
||||
*model.flags.add_input_arrays() = input_arrays[2];
|
||||
model.flags.add_output_arrays(output);
|
||||
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string> input_types, output_types;
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string> input_types, output_types;
|
||||
GetInputAndOutputTypes(model, &input_types, &output_types);
|
||||
|
||||
EXPECT_THAT(input_types, ElementsAre("float", "float", "int16"));
|
||||
@ -161,9 +161,9 @@ TEST(ConversionLogUtilTest, TestGetOpSignatures) {
|
||||
auto& array_map = model.GetMutableArrayMap();
|
||||
|
||||
std::unique_ptr<ConvOperator> conv(new ConvOperator());
|
||||
const string conv_input_name = "conv_input";
|
||||
const string conv_filter_name = "conv_filter";
|
||||
const string conv_output_name = "conv_output";
|
||||
const std::string conv_input_name = "conv_input";
|
||||
const std::string conv_filter_name = "conv_filter";
|
||||
const std::string conv_output_name = "conv_output";
|
||||
conv->inputs.push_back(conv_input_name);
|
||||
conv->inputs.push_back(conv_filter_name);
|
||||
conv->outputs.push_back(conv_output_name);
|
||||
@ -177,15 +177,15 @@ TEST(ConversionLogUtilTest, TestGetOpSignatures) {
|
||||
array_map[conv_output_name]->data_type = ArrayDataType::kFloat;
|
||||
array_map[conv_output_name]->copy_shape({4, 4, 2});
|
||||
|
||||
const string mean_input_name = "mean_input";
|
||||
const string mean_output_name = "mean_output";
|
||||
const std::string mean_input_name = "mean_input";
|
||||
const std::string mean_output_name = "mean_output";
|
||||
std::unique_ptr<MeanOperator> mean(new MeanOperator());
|
||||
mean->inputs.push_back(mean_input_name);
|
||||
mean->outputs.push_back(mean_output_name);
|
||||
array_map[mean_input_name] = std::unique_ptr<Array>(new Array);
|
||||
array_map[mean_output_name] = std::unique_ptr<Array>(new Array);
|
||||
|
||||
const string avg_pool_3d_output_name = "avg_pool_output";
|
||||
const std::string avg_pool_3d_output_name = "avg_pool_output";
|
||||
auto avg_pool_3d = absl::make_unique<TensorFlowUnsupportedOperator>();
|
||||
avg_pool_3d->tensorflow_op = "AvgPool3D";
|
||||
tensorflow::NodeDef node_def;
|
||||
@ -197,7 +197,7 @@ TEST(ConversionLogUtilTest, TestGetOpSignatures) {
|
||||
array_map[avg_pool_3d_output_name]->data_type = ArrayDataType::kInt32;
|
||||
array_map[avg_pool_3d_output_name]->copy_shape({2, 2});
|
||||
|
||||
const string custom_op_output_name = "custom_op_output";
|
||||
const std::string custom_op_output_name = "custom_op_output";
|
||||
auto my_custom_op = absl::make_unique<TensorFlowUnsupportedOperator>();
|
||||
my_custom_op->tensorflow_op = "MyAwesomeCustomOp";
|
||||
my_custom_op->inputs.push_back(avg_pool_3d_output_name);
|
||||
@ -211,7 +211,7 @@ TEST(ConversionLogUtilTest, TestGetOpSignatures) {
|
||||
model.operators.push_back(std::move(avg_pool_3d));
|
||||
model.operators.push_back(std::move(my_custom_op));
|
||||
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<string> op_signatures;
|
||||
TFLITE_PROTO_NS::RepeatedPtrField<std::string> op_signatures;
|
||||
GetOpSignatures(model, &op_signatures);
|
||||
EXPECT_THAT(op_signatures,
|
||||
UnorderedElementsAre(
|
||||
@ -225,14 +225,14 @@ TEST(ConversionLogUtilTest, TestGetOpSignatures) {
|
||||
}
|
||||
|
||||
TEST(ConversionLogUtilTest, TestSanitizeErrorMessage) {
|
||||
const string error =
|
||||
const std::string error =
|
||||
"error: failed while converting: 'main': Ops that can be supported by "
|
||||
"the flex runtime (enabled via setting the -emit-select-tf-ops flag): "
|
||||
"ResizeNearestNeighbor,ResizeNearestNeighbor. Ops that need custom "
|
||||
"implementation (enabled via setting the -emit-custom-ops flag): "
|
||||
"CombinedNonMaxSuppression.\nTraceback (most recent call last): File "
|
||||
"/usr/local/bin/toco_from_protos, line 8, in <module>";
|
||||
const string pruned_error =
|
||||
const std::string pruned_error =
|
||||
"Ops that can be supported by "
|
||||
"the flex runtime (enabled via setting the -emit-select-tf-ops flag): "
|
||||
"ResizeNearestNeighbor,ResizeNearestNeighbor.Ops that need custom "
|
||||
@ -242,7 +242,7 @@ TEST(ConversionLogUtilTest, TestSanitizeErrorMessage) {
|
||||
}
|
||||
|
||||
TEST(ConversionLogUtilTest, TestSanitizeErrorMessageNoMatching) {
|
||||
const string error =
|
||||
const std::string error =
|
||||
"error: failed while converting: 'main': Traceback (most recent call "
|
||||
"last): File "
|
||||
"/usr/local/bin/toco_from_protos, line 8, in <module>";
|
||||
|
||||
Loading…
Reference in New Issue
Block a user