experiments/STT-tensorflow
1
0
Fork 0
Code Issues Pull Requests Projects Releases Wiki Activity

Fix ~63 ClangTidy - Performance findings in TensorFlow.

Browse Source 
Change: 131891101
This commit is contained in:
Vincent Vanhoucke 2016-08-31 16:01:52 -08:00 committed by TensorFlower Gardener
parent 62c159ffe8
commit 7a1210bdbd
28 changed files with 57 additions and 49 deletions

2
tensorflow/c/c_api_test.cc
View File

@ -87,7 +87,7 @@ TEST(CApi, AllocateTensor) {
static void TestEncodeDecode(int line,
const std::vector<tensorflow::string>& data) {
const tensorflow::int64 n = data.size();
for (std::vector<tensorflow::int64> dims :
for (const std::vector<tensorflow::int64>& dims :
std::vector<std::vector<tensorflow::int64>>{
{n}, {1, n}, {n, 1}, {n / 2, 2}}) {
// Create C++ Tensor

2
tensorflow/core/common_runtime/bfc_allocator.cc
View File

@ -157,7 +157,7 @@ bool BFCAllocator::Extend(size_t rounded_bytes) {
InsertFreeChunkIntoBin(h);
// Invoke visitors on newly allocated region.
for (auto visitor : region_visitors_) {
for (const auto& visitor : region_visitors_) {
visitor(mem_addr, bytes);
}
return true;

2
tensorflow/core/common_runtime/constant_folding.cc
View File

@ -279,7 +279,7 @@ bool ReplaceTensorWithConstant(Graph* graph, Device* partition_device,
edges_to_remove.push_back(out_edge);
}
}
string node_name = n->name();
const string& node_name = n->name();
Node* constant_node;
auto builder = NodeDefBuilder(strings::StrCat(graph->NewName(node_name),
"__cf__", UniqueConstantId()),

5
tensorflow/core/common_runtime/copy_tensor.cc
View File

@ -16,6 +16,7 @@ limitations under the License.
#include "tensorflow/core/common_runtime/copy_tensor.h"
#include <atomic>
#include <utility>
#include <vector>
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/platform/logging.h"
@ -26,7 +27,9 @@ namespace {
struct RegistrationInfo {
RegistrationInfo(DeviceType s, DeviceType r, CopyTensor::CopyFunction cf)
: sender_device_type(s), receiver_device_type(r), copy_function(cf) {}
: sender_device_type(std::move(s)),
receiver_device_type(r),
copy_function(cf) {}
DeviceType sender_device_type;
DeviceType receiver_device_type;
CopyTensor::CopyFunction copy_function;

4
tensorflow/core/common_runtime/device_set.cc
View File

@ -71,9 +71,9 @@ std::vector<DeviceType> DeviceSet::PrioritizedDeviceTypeList() const {
std::vector<DeviceType> result;
std::set<string> seen;
for (Device* d : devices_) {
auto t = d->device_type();
const auto& t = d->device_type();
if (seen.insert(t).second) {
result.emplace_back(DeviceType(t));
result.emplace_back(t);
}
}
std::sort(result.begin(), result.end(), DeviceTypeComparator);

2
tensorflow/core/common_runtime/function_test.cc
View File

@ -144,7 +144,7 @@ class FunctionLibraryRuntimeTest : public ::testing::Test {
void Init(const std::vector<FunctionDef>& flib) {
FunctionDefLibrary proto;
for (auto fdef : flib) *(proto.add_function()) = fdef;
for (const auto& fdef : flib) *(proto.add_function()) = fdef;
delete lib_def_;
lib_def_ = new FunctionLibraryDefinition(OpRegistry::Global(), proto);
delete lib_;

2
tensorflow/core/common_runtime/gpu/gpu_event_mgr.cc
View File

@ -95,7 +95,7 @@ void EventMgr::ThenDeleteTensors(perftools::gputools::Stream* stream,
FlushAccumulatedTensors();
}
accumulated_stream_ = stream;
for (auto t : tensors) {
for (const auto& t : tensors) {
// accumulated_tensors_ takes over ownership of the reference to "t"
accumulated_tensors_->push_back(t);
accumulated_tensor_bytes_ += t.TotalBytes();

2
tensorflow/core/common_runtime/gpu/gpu_stream_util_test.cc
View File

@ -129,7 +129,7 @@ TEST_F(GpuStreamUtilTest, StreamOverrides) {
// Nodes should be assigned to streams by op type.
for (const auto& it : node_to_stream_id) {
Node* n = g.FindNodeId(it.first);
const string op = n->type_string();
const string& op = n->type_string();
const int stream = it.second;
if (op == "Const") {
EXPECT_EQ(stream, 90);

11
tensorflow/core/common_runtime/gpu/pool_allocator.cc
View File

@ -20,6 +20,7 @@ limitations under the License.
#include <sys/mman.h> // for munmap
#include <map>
#include <utility>
#include "tensorflow/core/lib/strings/numbers.h"
#include "tensorflow/core/platform/logging.h"
@ -31,7 +32,7 @@ namespace tensorflow {
PoolAllocator::PoolAllocator(size_t pool_size_limit, bool auto_resize,
SubAllocator* allocator,
RoundUpInterface* size_rounder, string name)
: name_(name),
: name_(std::move(name)),
has_size_limit_(pool_size_limit > 0),
auto_resize_(auto_resize),
pool_size_limit_(pool_size_limit),
@ -125,7 +126,7 @@ void* PoolAllocator::AllocateRaw(size_t alignment, size_t num_bytes) {
return PrepareChunk(r, alignment, num_bytes);
} else {
void* ptr = allocator_->Alloc(kPoolAlignment, num_bytes);
for (auto v : alloc_visitors_) {
for (const auto& v : alloc_visitors_) {
v(ptr, num_bytes);
}
return PrepareChunk(ptr, alignment, num_bytes);
@ -137,7 +138,7 @@ void PoolAllocator::DeallocateRaw(void* ptr) {
ChunkPrefix* cp = FindPrefix(ptr);
CHECK_LE((void*)cp, (void*)ptr);
if (!has_size_limit_ && !auto_resize_) {
for (auto v : free_visitors_) {
for (const auto& v : free_visitors_) {
v(cp, cp->num_bytes);
}
allocator_->Free(cp, cp->num_bytes);
@ -160,7 +161,7 @@ void PoolAllocator::Clear() {
mutex_lock lock(mutex_);
for (auto iter : pool_) {
PtrRecord* pr = iter.second;
for (auto v : free_visitors_) {
for (const auto& v : free_visitors_) {
v(pr->ptr, pr->num_bytes);
}
allocator_->Free(pr->ptr, pr->num_bytes);
@ -217,7 +218,7 @@ void PoolAllocator::EvictOne() {
DCHECK(iter != pool_.end());
}
pool_.erase(iter);
for (auto v : free_visitors_) {
for (const auto& v : free_visitors_) {
v(prec->ptr, prec->num_bytes);
}
allocator_->Free(prec->ptr, prec->num_bytes);

8
tensorflow/core/common_runtime/simple_placer.cc
View File

@ -42,7 +42,7 @@ std::vector<Device*> FilterSupportedDevices(
const std::vector<Device*>& devices,
const DeviceTypeVector& supported_device_types) {
std::vector<Device*> filtered_devices;
for (DeviceType d : supported_device_types) {
for (const DeviceType& d : supported_device_types) {
for (Device* device : devices) {
if (DeviceType(device->attributes().device_type()) == d) {
filtered_devices.emplace_back(device);
@ -495,7 +495,7 @@ class ColocationGraph {
"' does not match any device");
}
for (DeviceType d : member->supported_device_types) {
for (const DeviceType& d : member->supported_device_types) {
if (DeviceType(assigned_device->attributes().device_type()) == d) {
return Status::OK();
}
@ -545,9 +545,9 @@ class ColocationGraph {
target->clear();
// Iterate in priority order.
for (DeviceType device_type : temp) {
for (const DeviceType& device_type : temp) {
bool found = false;
for (DeviceType other_device_type : other) {
for (const DeviceType& other_device_type : other) {
if (device_type == other_device_type) {
found = true;
break;

4
tensorflow/core/framework/function.cc
View File

@ -861,11 +861,11 @@ string DebugString(const GraphDef& instantiated_func_def) {
string DebugStringWhole(const GraphDef& gdef) {
string ret;
for (auto fdef : gdef.library().function()) {
for (const auto& fdef : gdef.library().function()) {
strings::StrAppend(&ret, Print(fdef));
}
strings::StrAppend(&ret, "\n");
for (auto ndef : gdef.node()) {
for (const auto& ndef : gdef.node()) {
strings::StrAppend(&ret, Print(ndef), "\n");
}
return ret;

6
tensorflow/core/framework/function_testlib.cc
View File

@ -31,11 +31,11 @@ GraphDef GDef(gtl::ArraySlice<NodeDef> nodes,
VersionDef* versions = g.mutable_versions();
versions->set_producer(TF_GRAPH_DEF_VERSION);
versions->set_min_consumer(TF_GRAPH_DEF_VERSION_MIN_CONSUMER);
for (auto n : nodes) {
for (const auto& n : nodes) {
*(g.add_node()) = n;
}
auto lib = g.mutable_library();
for (auto f : funcs) {
for (const auto& f : funcs) {
*(lib->add_function()) = f;
}
return g;
@ -49,7 +49,7 @@ NodeDef NDef(const string& name, const string& op,
NodeDef n;
n.set_name(name);
n.set_op(op);
for (auto in : inputs) n.add_input(in);
for (const auto& in : inputs) n.add_input(in);
n.set_device(device);
for (auto na : attrs) n.mutable_attr()->insert({na.first, na.second.proto});
return n;

2
tensorflow/core/framework/op_def_util.cc
View File

@ -60,7 +60,7 @@ Status AllowedTypeValue(DataType dt, const OpDef::AttrDef& attr) {
Status AllowedStringValue(const string& str, const OpDef::AttrDef& attr) {
const AttrValue& allowed_values(attr.allowed_values());
for (auto allowed : allowed_values.list().s()) {
for (const auto& allowed : allowed_values.list().s()) {
if (str == allowed) {
return Status::OK();
}

4
tensorflow/core/framework/op_kernel_test.cc
View File

@ -381,7 +381,7 @@ class OpKernelBuilderTest : public ::testing::Test {
DeviceTypeVector devices;
TF_EXPECT_OK(SupportedDeviceTypesForNode(DeviceTypes(), def, &devices));
bool found = false;
for (DeviceType dt : devices) {
for (const DeviceType& dt : devices) {
if (dt == device_type) {
found = true;
}
@ -414,7 +414,7 @@ class OpKernelBuilderTest : public ::testing::Test {
DeviceTypeVector devices;
if (errors::IsNotFound(status)) {
TF_EXPECT_OK(SupportedDeviceTypesForNode(DeviceTypes(), def, &devices));
for (DeviceType dt : devices) {
for (const DeviceType& dt : devices) {
EXPECT_NE(dt, device_type);
}
} else {

2
tensorflow/core/graph/optimizer_cse_test.cc
View File

@ -326,7 +326,7 @@ TEST_F(OptimizerCSETest, Constant_Dedup) {
// A graph contains a bunch of constants.
Graph g(OpRegistry::Global());
for (auto val : {a, b, c, d, d, c, b, a}) {
for (const auto& val : {a, b, c, d, d, c, b, a}) {
test::graph::Constant(&g, val); // Node name is n/_0, n/_1, ...
}
GraphDef gdef;

2
tensorflow/core/graph/quantize_training.cc
View File

@ -74,7 +74,7 @@ inline bool IsGradientNode(const Graph* graph, const Node* node) {
// Returns true if the root tensor op type is known, false otherwise.
bool FindType(const Graph* graph, const Node* node, bool* signed_input,
bool* range_given, float* input_min, float* input_max) {
const string src_op = node->type_string();
const string& src_op = node->type_string();
if (src_op == "Const" || src_op == "Variable") {
*signed_input = true;
*range_given = false;

2
tensorflow/core/kernels/argmax_op.cc
View File

@ -67,7 +67,7 @@ class ArgOp : public OpKernel {
input.shape().DebugString()));
TensorShape output_shape;
TensorShape input_shape = input.shape();
const TensorShape& input_shape = input.shape();
for (int d = 0; d < input_dims - 1; ++d) {
output_shape.AddDim(input_shape.dim_size((d < dim) ? d : d + 1));
}

2
tensorflow/core/kernels/attention_ops.cc
View File

@ -41,7 +41,7 @@ class ExtractGlimpseOp : public OpKernel {
// depth).
void Compute(OpKernelContext* context) override {
const Tensor& input = context->input(0);
const TensorShape input_shape = input.shape();
const TensorShape& input_shape = input.shape();
const int32 num_dims = input_shape.dims();
OP_REQUIRES(
context, num_dims == 4,

2
tensorflow/core/kernels/candidate_sampler_ops.cc
View File

@ -190,7 +190,7 @@ class ComputeAccidentalHitsOp : public OpKernel {
void Compute(OpKernelContext* context) override {
const Tensor& in_true_candidates = context->input(0);
TensorShape in_true_candidates_shape = in_true_candidates.shape();
const TensorShape& in_true_candidates_shape = in_true_candidates.shape();
OP_REQUIRES(context, TensorShapeUtils::IsMatrix(in_true_candidates_shape) &&
in_true_candidates_shape.dim_size(1) == num_true_,
errors::InvalidArgument(

4
tensorflow/core/kernels/gather_nd_op.cc
View File

@ -53,7 +53,7 @@ class GatherNdOp : public OpKernel {
"index innermost dimension length must be <= params rank; saw: ",
indices.dim_size(indices.dims() - 1), " vs. ", params.dims()));
TensorShape indices_shape(indices.shape());
const TensorShape& indices_shape(indices.shape());
const int64 indices_nd = indices_shape.dim_size(indices_shape.dims() - 1);
// Check that we have enough index space
@ -79,7 +79,7 @@ class GatherNdOp : public OpKernel {
N_result *= indices_shape.dim_size(i);
}
TensorShape params_shape(params.shape());
const TensorShape& params_shape(params.shape());
Index total_nd = params_shape.dims();
TensorShape result_shape(indices_shape);

2
tensorflow/core/kernels/maxpooling_op.cc
View File

@ -272,7 +272,7 @@ class MaxPoolingGradOp : public OpKernel {
OP_REQUIRES(context, out_backprop.dims() == 4,
errors::InvalidArgument("out_backprop must be 4-dimensional"));
TensorShape output_shape = tensor_in.shape();
const TensorShape& output_shape = tensor_in.shape();
Tensor tensor_out_dup;
OP_REQUIRES_OK(context,

2
tensorflow/core/kernels/scan_ops.cc
View File

@ -58,7 +58,7 @@ public:
errors::InvalidArgument("ScanOp: Expected scan axis in the range [", 0,
", ", input.dims(), "), but got ", axis));
TensorShape output_shape = input.shape();
const TensorShape& output_shape = input.shape();
Tensor* output = nullptr;
OP_REQUIRES_OK(ctx, ctx->allocate_output(0, output_shape, &output));

3
tensorflow/core/lib/jpeg/jpeg_mem.cc
View File

@ -23,6 +23,7 @@ limitations under the License.
#include <algorithm>
#include <memory>
#include <string>
#include <utility>
#include "tensorflow/core/lib/jpeg/jpeg_handle.h"
#include "tensorflow/core/platform/logging.h"
@ -52,7 +53,7 @@ class FewerArgsForCompiler {
: datasize_(datasize),
flags_(flags),
pnwarn_(nwarn),
allocate_output_(allocate_output),
allocate_output_(std::move(allocate_output)),
height_read_(0),
height_(0),
stride_(0) {

6
tensorflow/core/platform/cloud/gcs_file_system.cc
View File

@ -92,7 +92,7 @@ class GcsRandomAccessFile : public RandomAccessFile {
: bucket_(bucket),
object_(object),
auth_provider_(auth_provider),
http_request_factory_(std::move(http_request_factory)),
http_request_factory_(http_request_factory),
read_ahead_bytes_(read_ahead_bytes) {}
/// The implementation of reads with a read-ahead buffer.
@ -189,7 +189,7 @@ class GcsWritableFile : public WritableFile {
: bucket_(bucket),
object_(object),
auth_provider_(auth_provider),
http_request_factory_(std::move(http_request_factory)) {
http_request_factory_(http_request_factory) {
if (GetTmpFilename(&tmp_content_filename_).ok()) {
outfile_.open(tmp_content_filename_,
std::ofstream::binary | std::ofstream::app);
@ -208,7 +208,7 @@ class GcsWritableFile : public WritableFile {
: bucket_(bucket),
object_(object),
auth_provider_(auth_provider),
http_request_factory_(std::move(http_request_factory)) {
http_request_factory_(http_request_factory) {
tmp_content_filename_ = tmp_content_filename;
outfile_.open(tmp_content_filename_,
std::ofstream::binary | std::ofstream::app);

3
tensorflow/core/util/tensor_slice_reader.cc
View File

@ -15,6 +15,7 @@ limitations under the License.
#include "tensorflow/core/util/tensor_slice_reader.h"
#include <utility>
#include <vector>
#include "tensorflow/core/framework/types.pb_text.h"
#include "tensorflow/core/framework/versions.h"
@ -107,7 +108,7 @@ TensorSliceReader::TensorSliceReader(const string& filepattern,
TensorSliceReader::TensorSliceReader(const string& filepattern,
OpenTableFunction open_function,
int preferred_shard)
: filepattern_(filepattern), open_function_(open_function) {
: filepattern_(filepattern), open_function_(std::move(open_function)) {
VLOG(1) << "TensorSliceReader for " << filepattern;
Status s = io::GetMatchingFiles(Env::Default(), filepattern, &fnames_);
if (!s.ok()) {

10
tensorflow/core/util/tensor_slice_set.cc
View File

@ -42,7 +42,7 @@ Status TensorSliceSet::Register(const TensorSlice& slice, const string& tag,
// We check if there is any intersection between this slice and any of the
// registered slices.
if (slices_hull_.Overlaps(slice)) {
for (const auto x : slices_) {
for (const auto& x : slices_) {
if (slice.Overlaps(x.second.slice)) {
return errors::Internal("Overlapping slices: existing slice = ",
x.first, ", new slice = ", str);
@ -89,7 +89,7 @@ bool TensorSliceSet::Query(const TensorSlice& slice, float* data) const {
int64 overlap_size = 0;
TensorSlice intersection;
TensorShape inter_shape;
for (const auto x : slices_) {
for (const auto& x : slices_) {
if (slice.Intersect(x.second.slice, &intersection)) {
s = intersection.SliceTensorShape(shape_, &inter_shape);
if (!s.ok()) {
@ -103,7 +103,7 @@ bool TensorSliceSet::Query(const TensorSlice& slice, float* data) const {
// We have it!
// Now we need to copy the data to "data"
if (data) {
for (const auto x : slices_) {
for (const auto& x : slices_) {
CopyDataFromTensorSliceToTensorSlice(shape_, x.second.slice, slice,
x.second.data, data);
}
@ -146,7 +146,7 @@ bool TensorSliceSet::QueryMeta(
int64 overlap_size = 0;
TensorSlice intersection;
TensorShape inter_shape;
for (const auto x : slices_) {
for (const auto& x : slices_) {
if (slice.Intersect(x.second.slice, &intersection)) {
s = intersection.SliceTensorShape(shape_, &inter_shape);
if (!s.ok()) {
@ -180,7 +180,7 @@ Status RegisterTensorSlice(
tensor_slices->insert(std::make_pair(name, tss));
} else {
// Check if the shapes match
TensorShape tss_shape(tss->shape());
const TensorShape& tss_shape(tss->shape());
if (!shape.IsSameSize(tss_shape)) {
return errors::Internal("Incompatible tensor shapes detected for tensor ",
name, ": existing = ", tss_shape.DebugString(),

4
tensorflow/core/util/tensor_slice_writer.cc
View File

@ -15,6 +15,8 @@ limitations under the License.
#include "tensorflow/core/util/tensor_slice_writer.h"
#include <utility>
#include "tensorflow/core/lib/core/errors.h"
#include "tensorflow/core/lib/io/table_builder.h"
#include "tensorflow/core/lib/random/random.h"
@ -81,7 +83,7 @@ Status CreateTableTensorSliceBuilder(const string& name,
TensorSliceWriter::TensorSliceWriter(const string& filename,
CreateBuilderFunction create_builder)
: filename_(filename),
create_builder_(create_builder),
create_builder_(std::move(create_builder)),
tmpname_(strings::StrCat(filename, ".tempstate", random::New64())),
slices_(0) {
VersionDef* versions = sts_.mutable_meta()->mutable_versions();

6
tensorflow/tools/proto_text/gen_proto_text_functions_lib.cc
View File

@ -294,7 +294,7 @@ void Generator::AppendFieldValueAppend(const FieldDescriptor& field,
}
void Generator::AppendFieldAppend(const FieldDescriptor& field) {
const string name = field.name();
const string& name = field.name();
if (field.is_map()) {
Print("{").Nest();
@ -445,7 +445,7 @@ void Generator::AppendParseMessageFunction(const Descriptor& md) {
Unnest().Print("}");
for (int i = 0; i < md.field_count(); ++i) {
const FieldDescriptor* field = md.field(i);
const string field_name = field->name();
const string& field_name = field->name();
string mutable_value_expr;
string set_value_prefix;
if (map_append) {
@ -530,7 +530,7 @@ void Generator::AppendParseMessageFunction(const Descriptor& md) {
for (int enum_i = 0; enum_i < enum_d->value_count(); ++enum_i) {
const auto* value_d = enum_d->value(enum_i);
const string value_name = value_d->name();
const string& value_name = value_d->name();
string condition = StrCat("value == \"", value_name,
"\" || value == \"", value_d->number(), "\"");
if (value_d->number() == 0) {