[TF-TRT] s/absl::make_unique/std::make_unique
diff --git a/tensorflow/compiler/tf2tensorrt/convert/convert_nodes_test.cc b/tensorflow/compiler/tf2tensorrt/convert/convert_nodes_test.cc
index fa82050..430e7f1 100644
--- a/tensorflow/compiler/tf2tensorrt/convert/convert_nodes_test.cc
+++ b/tensorflow/compiler/tf2tensorrt/convert/convert_nodes_test.cc
@@ -1599,22 +1599,22 @@
DeviceFactory::NewDevice("GPU", {}, "/job:a/replica:0/task:0"));
Device* device_ptr = device_.get();
- device_mgr_ = absl::make_unique<StaticDeviceMgr>(std::move(device_));
+ device_mgr_ = std::make_unique<StaticDeviceMgr>(std::move(device_));
- managed_allocator_ = absl::make_unique<GpuManagedAllocator>();
+ managed_allocator_ = std::make_unique<GpuManagedAllocator>();
Allocator* allocator = managed_allocator_.get();
step_container_ =
- absl::make_unique<ScopedStepContainer>(0, [](const string&) {});
+ std::make_unique<ScopedStepContainer>(0, [](const string&) {});
slice_reader_cache_wrapper_ =
- absl::make_unique<checkpoint::TensorSliceReaderCacheWrapper>();
+ std::make_unique<checkpoint::TensorSliceReaderCacheWrapper>();
- flib_def_ = absl::make_unique<FunctionLibraryDefinition>(
+ flib_def_ = std::make_unique<FunctionLibraryDefinition>(
OpRegistry::Global(), FunctionDefLibrary{});
thread_pool_ =
- absl::make_unique<thread::ThreadPool>(Env::Default(), "default",
+ std::make_unique<thread::ThreadPool>(Env::Default(), "default",
/*num_threads=*/1);
- pflr_ = absl::make_unique<ProcessFunctionLibraryRuntime>(
+ pflr_ = std::make_unique<ProcessFunctionLibraryRuntime>(
device_mgr_.get(), Env::Default(), /*config=*/nullptr,
TF_GRAPH_DEF_VERSION, flib_def_.get(), OptimizerOptions(),
thread_pool_.get());
@@ -1646,7 +1646,7 @@
params_.slice_reader_cache = slice_reader_cache_wrapper_.get();
params_.op_device_context = device_context;
- context_ = absl::make_unique<OpKernelContext>(¶ms_);
+ context_ = std::make_unique<OpKernelContext>(¶ms_);
// Outputs.
*kernel = op_kernel_.get();
diff --git a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc
index 3f284ba..5b19c6b 100644
--- a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc
+++ b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_op.cc
@@ -1040,7 +1040,7 @@
// Store an empty engine in the cache for these input shapes so we don't try
// to build the same failing engine again.
cache_resource->cache_.emplace(input_concrete_shapes,
- absl::make_unique<EngineContext>());
+ std::make_unique<EngineContext>());
return status;
}
return engine;
@@ -1101,7 +1101,7 @@
TF_RETURN_IF_ERROR(cache_res->profiles_.CreateExecutionContexts(
static_engine.get(), &exec_contexts));
cache.emplace(input_concrete_shapes,
- absl::make_unique<EngineContext>(std::move(static_engine),
+ std::make_unique<EngineContext>(std::move(static_engine),
std::move(exec_contexts)));
VLOG(1) << "Added new engine to cache of " << name()
<< ". Cache size: " << cache.size();
@@ -1119,7 +1119,7 @@
// Store an empty engine in the cache so we don't try to load the same
// failing engine again.
cache.emplace(input_concrete_shapes,
- absl::make_unique<EngineContext>());
+ std::make_unique<EngineContext>());
return std::pair<EngineContext*, int>(&empty_context, 0);
}
if (segment_graph_def_.node().empty()) {
@@ -1151,7 +1151,7 @@
// TODO(laigd): here we assume engine_input_shapes matches the actual input
// shapes of the engine, we should verify that.
cache.emplace(engine_input_shapes,
- absl::make_unique<EngineContext>(std::move(static_engine),
+ std::make_unique<EngineContext>(std::move(static_engine),
std::move(context)));
// Runtime is safe to delete after engine creation
VLOG(1) << "Size of serialized TRT engine: "
@@ -1193,7 +1193,7 @@
<< "The native segment will be used instead.";
// Store an empty engine in the cache for these input shapes so we don't
// try to build the same failing engine again.
- cache.emplace(input_concrete_shapes, absl::make_unique<EngineContext>());
+ cache.emplace(input_concrete_shapes, std::make_unique<EngineContext>());
return std::pair<EngineContext*, int>(&empty_context, 0);
}
@@ -1211,7 +1211,7 @@
TF_RETURN_IF_ERROR(cache_res->profiles_.CreateExecutionContexts(
engine.get(), &exec_contexts));
cache.emplace(input_concrete_shapes,
- absl::make_unique<EngineContext>(std::move(engine),
+ std::make_unique<EngineContext>(std::move(engine),
std::move(exec_contexts)));
VLOG(1) << "Added new engine to cache of " << name()
<< ". Cache size: " << cache.size();
@@ -1227,7 +1227,7 @@
// possible.
Status TRTEngineOp::AllocateCalibrationResources(
OpKernelContext* ctx, TRTEngineCacheResource* cache_res) {
- cache_res->calib_ctx_ = absl::make_unique<CalibrationContext>();
+ cache_res->calib_ctx_ = std::make_unique<CalibrationContext>();
auto* cres = cache_res->calib_ctx_.get();
// Get the input shapes.
@@ -1326,13 +1326,13 @@
auto calib_result = cache_res->profiles_.CreateExecutionContexts(
cres->engine_.get(), &exec_contexts);
cache_res->cache_.emplace(
- shapes, absl::make_unique<EngineContext>(std::move(cres->engine_),
+ shapes, std::make_unique<EngineContext>(std::move(cres->engine_),
std::move(exec_contexts)));
} else {
ExecutionContext context =
ExecutionContext::Create(cres->engine_.get());
cache_res->cache_.emplace(
- shapes, absl::make_unique<EngineContext>(std::move(cres->engine_),
+ shapes, std::make_unique<EngineContext>(std::move(cres->engine_),
std::move(context)));
}
}
diff --git a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops.cc b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops.cc
index d9e3f09..fdb8004 100644
--- a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops.cc
+++ b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops.cc
@@ -115,7 +115,7 @@
// Parse the serialized engines and add them to the cache.
std::unique_ptr<RandomAccessFile> file;
OP_REQUIRES_OK(ctx, ctx->env()->NewRandomAccessFile(filename, &file));
- auto reader = absl::make_unique<io::RecordReader>(file.get());
+ auto reader = std::make_unique<io::RecordReader>(file.get());
uint64 offset = 0;
int num_loaded_engine = 0;
@@ -156,7 +156,7 @@
ctx_vec.push_back(ExecutionContext::Create(raw_engine));
}
resource->cache_.emplace(engine_input_shapes,
- absl::make_unique<EngineContext>(
+ std::make_unique<EngineContext>(
std::move(engine), std::move(ctx_vec)));
++num_loaded_engine;
} while (1);
@@ -207,7 +207,7 @@
// Serialize the engines and write them to file.
std::unique_ptr<WritableFile> file;
OP_REQUIRES_OK(ctx, ctx->env()->NewWritableFile(filename, &file));
- auto writer = absl::make_unique<io::RecordWriter>(file.get());
+ auto writer = std::make_unique<io::RecordWriter>(file.get());
int num_serialized_engines = 0;
if (save_gpu_specific_engines_) {
diff --git a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops_test.cc b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops_test.cc
index 40163de..dfa248d 100644
--- a/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops_test.cc
+++ b/tensorflow/compiler/tf2tensorrt/kernels/trt_engine_resource_ops_test.cc
@@ -286,7 +286,7 @@
}
resource->cache_.emplace(
engine_input_shape,
- absl::make_unique<EngineContext>(std::move(engine), std::move(context)));
+ std::make_unique<EngineContext>(std::move(engine), std::move(context)));
// Check that the resource has multiple references before it is unregistered
// from the resource manager.
EXPECT_FALSE(resource->RefCountIsOne());
@@ -322,7 +322,7 @@
// Verify the file for the serialized engine.
std::unique_ptr<RandomAccessFile> file;
TF_ASSERT_OK(env->NewRandomAccessFile(filename, &file));
- auto reader = absl::make_unique<io::RecordReader>(file.get());
+ auto reader = std::make_unique<io::RecordReader>(file.get());
uint64 offset = 0;
tstring record;
TF_ASSERT_OK(reader->ReadRecord(&offset, &record));
