ClangTidy - Readability cleanup:/code-findings-fixes.

* unused using-declarations * redundant string conversions * C-style casts * redundant get() call on smart pointer * the 'empty' method should be used to check for emptiness instead of 'size' PiperOrigin-RevId: 196585984
tensorflow · May 14, 2018 · f94d60a · f94d60a
1 parent 5334631
commit f94d60a
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Showing 14 changed files with 21 additions and 32 deletions.
diff --git a/tensorflow/cc/gradients/math_grad_test.cc b/tensorflow/cc/gradients/math_grad_test.cc
@@ -31,7 +31,6 @@ using ops::AddN;
 using ops::BatchMatMul;
 using ops::Const;
 using ops::Div;
-using ops::Greater;
 using ops::MatMul;
 using ops::Max;
 using ops::Maximum;
@@ -46,7 +45,6 @@ using ops::RealDiv;
 using ops::SquaredDifference;
 using ops::Sub;
 using ops::Sum;
-using ops::Where3;
 
 // TODO(andydavis) Test gradient function against numeric gradients output.
 // TODO(andydavis) As more gradients are added move common test functions

diff --git a/tensorflow/compiler/xla/service/gpu/convolution_thunk.cc b/tensorflow/compiler/xla/service/gpu/convolution_thunk.cc
@@ -29,11 +29,6 @@ namespace xla {
 namespace gpu {
 
 using se::dnn::AlgorithmDesc;
-using se::dnn::BatchDescriptor;
-using se::dnn::ConvolutionDescriptor;
-using se::dnn::DataLayout;
-using se::dnn::FilterDescriptor;
-using se::dnn::FilterLayout;
 
 ConvolutionThunk::ConvolutionThunk(
     CudnnConvKind convolution_kind, const BufferAllocation::Slice& input_buffer,

diff --git a/tensorflow/compiler/xla/service/hlo_evaluator.cc b/tensorflow/compiler/xla/service/hlo_evaluator.cc
@@ -52,7 +52,6 @@ namespace xla {
 namespace {
 
 using tensorflow::gtl::ArraySlice;
-using tensorflow::gtl::FlatSet;
 
 template <typename OperandT>
 StatusOr<std::unique_ptr<Literal>> Compare(const Shape& shape, HloOpcode opcode,

diff --git a/tensorflow/compiler/xla/tests/literal_test_util.cc b/tensorflow/compiler/xla/tests/literal_test_util.cc
@@ -43,7 +43,6 @@ namespace xla {
 using ::tensorflow::strings::Appendf;
 using ::tensorflow::strings::Printf;
 using ::tensorflow::strings::StrAppend;
-using ::tensorflow::strings::StrCat;
 
 /* static */ ::testing::AssertionResult LiteralTestUtil::EqualShapes(
     const Shape& expected, const Shape& actual) {

diff --git a/tensorflow/core/common_runtime/gpu/gpu_event_mgr_test.cc b/tensorflow/core/common_runtime/gpu/gpu_event_mgr_test.cc
@@ -119,7 +119,7 @@ TEST(EventMgr, DelayedPolling) {
   EXPECT_EQ(0, th.queue_size());
   TensorReferenceVector* v = nullptr;
   std::unique_ptr<se::Stream> stream(new se::Stream(stream_exec));
-  CHECK(stream.get());
+  CHECK(stream);
   stream->Init();
   for (int i = 0; i < 5; ++i) {
     v = new TensorReferenceVector;
@@ -151,7 +151,7 @@ TEST(EventMgr, FlushLargeTensorImmediately) {
   TEST_EventMgrHelper th(&em);
   EXPECT_EQ(0, live_tensor_bytes);
   std::unique_ptr<se::Stream> stream(new se::Stream(stream_exec));
-  CHECK(stream.get());
+  CHECK(stream);
   stream->Init();
   for (int i = 0; i < 5; ++i) {
     TensorReferenceVector v;
@@ -168,7 +168,7 @@ TEST(EventMgr, ManySmallTensorsFlushedImmediately) {
   TEST_EventMgrHelper th(&em);
   EXPECT_EQ(0, live_tensor_bytes);
   std::unique_ptr<se::Stream> stream(new se::Stream(stream_exec));
-  CHECK(stream.get());
+  CHECK(stream);
   stream->Init();
   for (int i = 0; i < 5; ++i) {
     TensorReferenceVector v;
@@ -209,7 +209,7 @@ TEST(EventMgr, ManySmallTensorsSeparateCallsFlushed) {
   TEST_EventMgrHelper th(&em);
   EXPECT_EQ(0, live_tensor_bytes);
   std::unique_ptr<se::Stream> stream(new se::Stream(stream_exec));
-  CHECK(stream.get());
+  CHECK(stream);
   stream->Init();
   for (int i = 0; i < 5; ++i) {
     for (int i = 0; i < 1000; i++) {
@@ -232,7 +232,7 @@ TEST(EventMgr, NonEmptyShutdown) {
   EXPECT_EQ(0, th.queue_size());
   EXPECT_EQ(0, th.free_size());
   std::unique_ptr<se::Stream> stream(new se::Stream(stream_exec));
-  CHECK(stream.get());
+  CHECK(stream);
   stream->Init();
   for (int i = 0; i < 5; ++i) {
     TensorReferenceVector* v = new TensorReferenceVector;

diff --git a/tensorflow/core/distributed_runtime/rpc/grpc_worker_service.cc b/tensorflow/core/distributed_runtime/rpc/grpc_worker_service.cc
@@ -577,7 +577,7 @@ void GrpcWorker::LoggingAsync(const LoggingRequest* request,
                               LoggingResponse* response, StatusCallback done) {
   auto env = this->env();
   if (env) {
-    auto session_mgr = (SessionMgr*)env->session_mgr;
+    auto session_mgr = env->session_mgr;
     if (session_mgr) {
       session_mgr->SetLogging(request->rpc_logging());
       for (const auto& step_id : request->fetch_step_id()) {

diff --git a/tensorflow/core/distributed_runtime/session_mgr.cc b/tensorflow/core/distributed_runtime/session_mgr.cc
@@ -67,7 +67,7 @@ Status SessionMgr::CreateSession(const string& session,
     worker_name = WorkerNameFromServerDef(server_def);
   }
 
-  if (worker_cache != nullptr && default_worker_cache_.get() != nullptr) {
+  if (worker_cache != nullptr && default_worker_cache_ != nullptr) {
     worker_cache->SetLogging(this->is_logging_active_);
   }
 

diff --git a/tensorflow/core/distributed_runtime/worker_cache_partial.cc b/tensorflow/core/distributed_runtime/worker_cache_partial.cc
@@ -67,7 +67,7 @@ Status WorkerCachePartial::RefreshDeviceStatus(const string& device_name) {
   };
   std::unique_ptr<WorkerInterface, decltype(deleter)> rwi(CreateWorker(task),
                                                           deleter);
-  if (s.ok() && !rwi.get()) {
+  if (s.ok() && !rwi) {
     s = errors::Internal("RefreshDeviceStatus, unknown worker task: ", task);
   }
 

diff --git a/tensorflow/core/grappler/optimizers/loop_optimizer.cc b/tensorflow/core/grappler/optimizers/loop_optimizer.cc
@@ -390,7 +390,7 @@ Status LoopInvariantNodeMotionOptimizer::Optimize() {
       frame_children_[frame_ids[0]].insert(frame_ids[1]);
       frame_parent_[frame_ids.back()] = frame_ids[frame_ids.size() - 2];
     }
-    if (frame_ids.size() >= 1) {
+    if (!frame_ids.empty()) {
       frame_children_.insert(std::make_pair(frame_ids.back(), empty_set_));
       if (node->op() == "LoopCond") {
         if (loop_cond_.count(frame_ids.back())) {
@@ -409,7 +409,7 @@ Status LoopInvariantNodeMotionOptimizer::Optimize() {
   }
 
   for (auto it = frame_children_.begin(); it != frame_children_.end(); ++it) {
-    if (it->second.size() == 0) {
+    if (it->second.empty()) {
       worklist.push_back(it->first);
     }
   }
@@ -422,7 +422,7 @@ Status LoopInvariantNodeMotionOptimizer::Optimize() {
     if (parent_it != frame_parent_.end()) {
       int parent_id = parent_it->second;
       frame_children_[parent_id].erase(frame_id);
-      if (frame_children_[parent_id].size() == 0) {
+      if (frame_children_[parent_id].empty()) {
         worklist.push_back(parent_id);
       }
     }

diff --git a/tensorflow/core/kernels/cudnn_rnn_ops.cc b/tensorflow/core/kernels/cudnn_rnn_ops.cc
@@ -1411,7 +1411,7 @@ class CudnnRNNForwardOpV2<GPUDevice, T>
       CudnnRnnAllocatorInTemp<T> reserve_space_allocator(context);
       CudnnRnnAllocatorInTemp<uint8> workspace_allocator(context);
       status = DoForward<T>(
-          context, *rnn_desc.get(), model_types(), model_shapes, input, input_h,
+          context, *rnn_desc, model_types(), model_shapes, input, input_h,
           input_c, params, is_training(), output, output_h, output_c,
           &reserve_space_allocator, &workspace_allocator, &fwd_profile_result);
       if (!status.ok()) {
@@ -1422,12 +1422,11 @@ class CudnnRNNForwardOpV2<GPUDevice, T>
         // Get reserve space from the forward pass.
         Tensor reserve_space = reserve_space_allocator.get_allocated_tensor(0);
         status = DoBackward<T>(
-            context, *rnn_desc.get(), model_types(), model_shapes, input,
-            input_h, input_c, params, output, output_h, output_c,
-            &output_backprop, &output_h_backprop, &output_c_backprop,
-            &reserve_space, &input_backprop, &input_h_backprop,
-            &input_c_backprop, &params_backprop, &workspace_allocator,
-            &bak_profile_result);
+            context, *rnn_desc, model_types(), model_shapes, input, input_h,
+            input_c, params, output, output_h, output_c, &output_backprop,
+            &output_h_backprop, &output_c_backprop, &reserve_space,
+            &input_backprop, &input_h_backprop, &input_c_backprop,
+            &params_backprop, &workspace_allocator, &bak_profile_result);
         if (!status.ok()) {
           continue;
         }

diff --git a/tensorflow/core/kernels/ops_testutil.cc b/tensorflow/core/kernels/ops_testutil.cc
@@ -24,7 +24,7 @@ namespace tensorflow {
 
 void OpsTestBase::SetDevice(const DeviceType& device_type,
                             std::unique_ptr<Device> device) {
-  CHECK(device_.get()) << "No device provided";
+  CHECK(device_) << "No device provided";
   device_type_ = device_type;
   device_ = std::move(device);
 #ifdef GOOGLE_CUDA

diff --git a/tensorflow/core/ops/rpc_ops.cc b/tensorflow/core/ops/rpc_ops.cc
@@ -18,7 +18,6 @@ limitations under the License.
 
 namespace tensorflow {
 
-using tensorflow::shape_inference::DimensionHandle;
 using tensorflow::shape_inference::InferenceContext;
 using tensorflow::shape_inference::ShapeHandle;
 

diff --git a/tensorflow/core/platform/cloud/oauth_client.cc b/tensorflow/core/platform/cloud/oauth_client.cc
@@ -97,7 +97,7 @@ Status CreateSignature(RSA* private_key, StringPiece to_sign,
   }
   std::unique_ptr<EVP_MD_CTX, std::function<void(EVP_MD_CTX*)>> md_ctx(
       EVP_MD_CTX_create(), [](EVP_MD_CTX* ptr) { EVP_MD_CTX_destroy(ptr); });
-  if (!md_ctx.get()) {
+  if (!md_ctx) {
     return errors::Internal("Could not create MD_CTX.");
   }
 
@@ -196,7 +196,7 @@ Status OAuthClient::GetTokenFromServiceAccountJson(
   std::unique_ptr<RSA, std::function<void(RSA*)>> private_key(
       PEM_read_bio_RSAPrivateKey(bio.get(), nullptr, nullptr, nullptr),
       [](RSA* ptr) { RSA_free(ptr); });
-  if (!private_key.get()) {
+  if (!private_key) {
     return errors::Internal("Could not deserialize the private key.");
   }
 

diff --git a/tensorflow/python/lib/core/ndarray_tensor.cc b/tensorflow/python/lib/core/ndarray_tensor.cc
@@ -145,7 +145,7 @@ Status PyBytesArrayMap(PyArrayObject* array, F f) {
   while (PyArray_ITER_NOTDONE(iter.get())) {
     auto item = tensorflow::make_safe(PyArray_GETITEM(
         array, static_cast<char*>(PyArray_ITER_DATA(iter.get()))));
-    if (!item.get()) {
+    if (!item) {
       return errors::Internal("Unable to get element from the feed - no item.");
     }
     char* ptr;