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-rw-r--r--configure.py2
-rw-r--r--tensorflow/contrib/tensorrt/BUILD1
-rw-r--r--tensorflow/contrib/tensorrt/convert/convert_graph.cc94
-rw-r--r--tensorflow/contrib/tensorrt/convert/convert_nodes.cc7
-rw-r--r--tensorflow/contrib/tensorrt/convert/convert_nodes.h9
-rw-r--r--tensorflow/contrib/tensorrt/convert/utils.h2
-rw-r--r--tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc28
-rw-r--r--tensorflow/contrib/tensorrt/kernels/trt_engine_op.h10
-rw-r--r--tensorflow/contrib/tensorrt/python/trt_convert.py12
-rw-r--r--tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc1
-rw-r--r--tensorflow/contrib/tensorrt/resources/trt_resources.h12
-rw-r--r--tensorflow/contrib/tensorrt/test/test_tftrt.py11
12 files changed, 101 insertions, 88 deletions
diff --git a/configure.py b/configure.py
index a14d006a73..ad585fa52e 100644
--- a/configure.py
+++ b/configure.py
@@ -944,7 +944,7 @@ def set_tf_cudnn_version(environ_cp):
def is_cuda_compatible(lib, cuda_ver, cudnn_ver):
- """Check the compatibility between given library and cudnn/cudart libraries."""
+ """Check compatibility between given library and cudnn/cudart libraries."""
ldd_bin = which('ldd') or '/usr/bin/ldd'
ldd_out = run_shell([ldd_bin, lib], True)
ldd_out = ldd_out.split(os.linesep)
diff --git a/tensorflow/contrib/tensorrt/BUILD b/tensorflow/contrib/tensorrt/BUILD
index e7b3fe38e5..adda0b758b 100644
--- a/tensorflow/contrib/tensorrt/BUILD
+++ b/tensorflow/contrib/tensorrt/BUILD
@@ -207,6 +207,7 @@ tf_cuda_library(
],
deps = [
":trt_logging",
+ ":utils",
"//tensorflow/core:framework_headers_lib",
"//tensorflow/core:framework_lite",
"//tensorflow/core:lib_proto_parsing",
diff --git a/tensorflow/contrib/tensorrt/convert/convert_graph.cc b/tensorflow/contrib/tensorrt/convert/convert_graph.cc
index ba7d3b5f86..1c4fd4a0ce 100644
--- a/tensorflow/contrib/tensorrt/convert/convert_graph.cc
+++ b/tensorflow/contrib/tensorrt/convert/convert_graph.cc
@@ -49,13 +49,14 @@ limitations under the License.
#include "tensorflow/core/lib/strings/numbers.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/types.h"
-#include "tensorflow/core/protobuf/config.pb.h"
+#include "tensorflow/core/protobuf/config.pb.h" // NOLINT
#include "tensorflow/core/protobuf/device_properties.pb.h" // NOLINT
+#include "tensorflow/core/protobuf/rewriter_config.pb.h" // NOLINT
#include "tensorflow/core/util/device_name_utils.h"
#if GOOGLE_CUDA
#if GOOGLE_TENSORRT
-#include <cuda/include/cuda_runtime_api.h>
+#include "cuda/include/cuda_runtime_api.h"
#include "tensorrt/include/NvInfer.h"
namespace tensorflow {
namespace tensorrt {
@@ -238,14 +239,14 @@ tensorflow::Status ConvertGraphDefToTensorRT(
}
// Function to get subsegment information structure.
-EngineInfo GetEngineInfo(
+tensorflow::Status GetEngineInfo(
const tensorflow::Graph* g,
const tensorflow::grappler::GraphProperties& graph_properties,
const std::set<string>& segment_nodes,
const std::unordered_map<string, tensorflow::Node*>& node_map,
- const std::vector<tensorflow::Node*>& reverse_topo_order) {
+ const std::vector<tensorflow::Node*>& reverse_topo_order,
+ EngineInfo* info) {
std::vector<int> subgraph_node_ids;
- EngineInfo info;
std::set<string> segment_devices;
int input_port = 0;
int output_port = 0;
@@ -296,9 +297,9 @@ EngineInfo GetEngineInfo(
created_edges.insert({s, port});
input_port++;
}
- info.connections.emplace_back(input_node->name(), input_node->id(),
- edge->src_output(), node_name, node_id,
- edge->dst_input(), true, port);
+ info->connections.emplace_back(input_node->name(), input_node->id(),
+ edge->src_output(), node_name, node_id,
+ edge->dst_input(), true, port);
}
}
}
@@ -316,28 +317,28 @@ EngineInfo GetEngineInfo(
created_edges.insert({s, port});
output_port++;
}
- info.connections.emplace_back(output_node->name(), output_node->id(),
- edge->dst_input(), node_name, node_id,
- edge->src_output(), false, port);
+ info->connections.emplace_back(output_node->name(), output_node->id(),
+ edge->dst_input(), node_name, node_id,
+ edge->src_output(), false, port);
}
}
}
- ConvertSegmentToGraphDef(g, graph_properties, subgraph_node_ids,
- &info.connections, &info.segment_graph_def,
- &info.engine_name);
+ TF_RETURN_IF_ERROR(ConvertSegmentToGraphDef(
+ g, graph_properties, subgraph_node_ids, &info->connections,
+ &info->segment_graph_def, &info->engine_name));
// TODO(sami): This should not happen once segmenter is updated.
if (segment_devices.size() == 1) {
- info.device = *segment_devices.begin();
+ info->device = *segment_devices.begin();
} else if (segment_devices.size() > 1) {
LOG(WARNING) << "Detected multiple(" << segment_devices.size()
<< ") devices for the segment. Picking first one to continue "
<< "but this shouldn't have happened";
- info.device = *segment_devices.begin();
+ info->device = *segment_devices.begin();
} else {
VLOG(1) << "Segment devices size is 0";
}
- return info;
+ return Status::OK();
}
// Function to insert a TRT node into the graph. The graph is not modified if
@@ -562,7 +563,9 @@ tensorflow::Status RegisterSegmentFunctionToFunctionLibrary(
tensorflow::NodeDefBuilder node_builder(
StrCat(name, "_Arg"), tensorflow::FunctionLibraryDefinition::kArgOp);
VLOG(1) << "Adding " << StrCat(name, "_Arg");
- node_builder.Attr("T", node->output_type(0)).Attr("index", i).Finalize(&nd);
+ TF_RETURN_IF_ERROR(node_builder.Attr("T", node->output_type(0))
+ .Attr("index", i)
+ .Finalize(&nd));
tensorflow::Status s;
auto node_arg = sgraph.AddNode(nd, &s);
if (!s.ok()) {
@@ -593,7 +596,9 @@ tensorflow::Status RegisterSegmentFunctionToFunctionLibrary(
VLOG(1) << " input " << nout.node << ":" << nout.index
<< " dtype=" << tensorflow::DataTypeString(nout.data_type);
node_builder.Input({nout});
- node_builder.Attr("T", node->output_type(0)).Attr("index", i).Finalize(&nd);
+ TF_RETURN_IF_ERROR(node_builder.Attr("T", node->output_type(0))
+ .Attr("index", i)
+ .Finalize(&nd));
if (VLOG_IS_ON(3)) {
VLOG(3) << nd.DebugString();
}
@@ -713,11 +718,12 @@ tensorflow::Status ConvertAfterShapes(ConversionParams& params) {
segment_options.exclude_node_list.insert(node);
}
segment_options.minimum_segment_size = params.minimum_segment_size;
- tensorflow::tensorrt::segment::SegmentNodesVector segments;
+ tensorflow::tensorrt::segment::SegmentNodesVector initial_segments;
TF_RETURN_IF_ERROR(tensorrt::segment::SegmentGraph(
- &graph, IsTensorRTCandidate, segment_options, &segments));
- if (segments.size() > 1) {
- VLOG(0) << "MULTIPLE tensorrt candidate conversion: " << segments.size();
+ &graph, IsTensorRTCandidate, segment_options, &initial_segments));
+ if (initial_segments.size() > 1) {
+ VLOG(0) << "MULTIPLE tensorrt candidate conversion: "
+ << initial_segments.size();
}
// Get the EngineInfo for each segment.
@@ -725,17 +731,24 @@ tensorflow::Status ConvertAfterShapes(ConversionParams& params) {
TF_RETURN_IF_ERROR(BuildNodeMap(graph, &node_map));
float total_num_nodes_in_segments = 0.;
std::vector<EngineInfo> engine_segments;
- engine_segments.reserve(segments.size());
+ engine_segments.reserve(initial_segments.size());
std::vector<tensorflow::Node*> reverse_topo_order;
tensorflow::GetPostOrder(graph, &reverse_topo_order);
size_t total_engine_bytes_size = 0;
std::vector<size_t> engine_bytes_size;
- for (size_t t = 0; t < segments.size(); t++) {
- auto& s = segments.at(t);
- engine_segments.emplace_back(GetEngineInfo(&graph, *params.graph_properties,
- s.first, node_map,
- reverse_topo_order));
- auto& curr_engine = engine_segments.back();
+ tensorflow::tensorrt::segment::SegmentNodesVector converted_segments;
+ converted_segments.reserve(initial_segments.size());
+ for (size_t t = 0; t < initial_segments.size(); t++) {
+ auto& curr_segment = initial_segments.at(t);
+ EngineInfo curr_engine;
+ Status status =
+ GetEngineInfo(&graph, *params.graph_properties, curr_segment.first,
+ node_map, reverse_topo_order, &curr_engine);
+ if (!status.ok()) {
+ LOG(WARNING) << "Failed to get engine info for segment " << t << ": "
+ << status;
+ continue;
+ }
curr_engine.precision_mode = params.precision_mode;
curr_engine.engine_type =
(params.is_dyn_op || params.precision_mode == INT8MODE
@@ -744,12 +757,19 @@ tensorflow::Status ConvertAfterShapes(ConversionParams& params) {
curr_engine.cached_engine_batches = params.cached_engine_batches;
curr_engine.maximum_cached_engines = params.max_cached_engines;
StrAppend(&curr_engine.engine_name, "my_trt_op_", t);
- RegisterSegmentFunctionToFunctionLibrary(
+ status = RegisterSegmentFunctionToFunctionLibrary(
&graph, curr_engine.segment_graph_def, curr_engine.engine_name);
+ if (!status.ok()) {
+ LOG(WARNING) << "Failed to register segment graphdef as a function " << t
+ << ": " << status;
+ continue;
+ }
engine_bytes_size.push_back(curr_engine.segment_graph_def.ByteSizeLong());
total_engine_bytes_size += engine_bytes_size.back();
- total_num_nodes_in_segments += s.first.size();
+ total_num_nodes_in_segments += curr_segment.first.size();
+ engine_segments.push_back(std::move(curr_engine));
+ converted_segments.push_back(std::move(curr_segment));
if (VLOG_IS_ON(8)) {
string fname = curr_engine.engine_name;
@@ -775,7 +795,7 @@ tensorflow::Status ConvertAfterShapes(ConversionParams& params) {
engine.max_workspace_size_bytes =
params.max_workspace_size_bytes *
(engine_bytes_size.at(i) / total_engine_bytes_size +
- segments.at(i).first.size() / total_num_nodes_in_segments) /
+ converted_segments.at(i).first.size() / total_num_nodes_in_segments) /
2.0;
// The allocator is used to build the engine. The build and the built engine
// will be destroyed after we get the serialized engine string, so it's fine
@@ -793,17 +813,17 @@ tensorflow::Status ConvertAfterShapes(ConversionParams& params) {
cudaSetDevice(cuda_device_id);
auto status = CreateTRTNode(&graph, engine_segments, i, alloc.get(),
params.max_batch_size);
- // If status is ok, we successfuly added the node to the graph and can
+ // If status is ok, we successfully added the node to the graph and can
// remove segment ops. Otherwise graph is not modified.
if (status.ok()) {
- for (auto node_name : segments.at(i).first) {
+ for (auto node_name : converted_segments.at(i).first) {
graph.RemoveNode(node_map.at(node_name));
}
} else {
// Graph is not modified.
LOG(WARNING) << "Engine creation for segment " << i << ", composed of "
- << segments.at(i).first.size() << " nodes failed: " << status
- << ". Skipping...";
+ << converted_segments.at(i).first.size() << " nodes failed: "
+ << status << ". Skipping...";
}
}
cudaSetDevice(old_cuda_device);
diff --git a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc
index b5214b461a..146b9c7344 100644
--- a/tensorflow/contrib/tensorrt/convert/convert_nodes.cc
+++ b/tensorflow/contrib/tensorrt/convert/convert_nodes.cc
@@ -2130,13 +2130,10 @@ void Converter::register_op_converters() {
} // namespace
tensorflow::Status ConvertGraphDefToEngine(
- const tensorflow::GraphDef& gdef,
- int precision_mode,
- int max_batch_size,
+ const tensorflow::GraphDef& gdef, int precision_mode, int max_batch_size,
size_t max_workspace_size_bytes,
const std::vector<tensorflow::PartialTensorShape>& input_shapes,
- Logger* logger,
- nvinfer1::IGpuAllocator* allocator,
+ Logger* logger, nvinfer1::IGpuAllocator* allocator,
TRTInt8Calibrator* calibrator,
TrtUniquePtrType<nvinfer1::ICudaEngine>* engine,
bool* convert_successfully) {
diff --git a/tensorflow/contrib/tensorrt/convert/convert_nodes.h b/tensorflow/contrib/tensorrt/convert/convert_nodes.h
index 2da4edf7f5..7684d8d4a2 100644
--- a/tensorflow/contrib/tensorrt/convert/convert_nodes.h
+++ b/tensorflow/contrib/tensorrt/convert/convert_nodes.h
@@ -78,7 +78,7 @@ struct EngineInfo {
EngineInfo()
: engine_type(EngineType::TRTStatic),
max_workspace_size_bytes(0),
- precision_mode(FP32MODE) {};
+ precision_mode(FP32MODE) {}
string engine_name;
string device;
@@ -120,13 +120,10 @@ tensorflow::Status ConvertSegmentToGraphDef(
// is successful. This is different than successfully building the engine:
// building can still fail afterwards.
tensorflow::Status ConvertGraphDefToEngine(
- const tensorflow::GraphDef& gdef,
- int precision_mode,
- int max_batch_size,
+ const tensorflow::GraphDef& gdef, int precision_mode, int max_batch_size,
size_t max_workspace_size_bytes,
const std::vector<tensorflow::PartialTensorShape>& input_shapes,
- Logger* logger,
- nvinfer1::IGpuAllocator* allocator,
+ Logger* logger, nvinfer1::IGpuAllocator* allocator,
TRTInt8Calibrator* calibrator,
TrtUniquePtrType<nvinfer1::ICudaEngine>* engine,
bool* convert_successfully);
diff --git a/tensorflow/contrib/tensorrt/convert/utils.h b/tensorflow/contrib/tensorrt/convert/utils.h
index 021fdaf8c5..f601c06701 100644
--- a/tensorflow/contrib/tensorrt/convert/utils.h
+++ b/tensorflow/contrib/tensorrt/convert/utils.h
@@ -31,7 +31,7 @@ struct TrtDestroyer {
template <typename T>
using TrtUniquePtrType = std::unique_ptr<T, TrtDestroyer<T>>;
-} // namespace convert
} // namespace tensorrt
+} // namespace tensorflow
#endif // TENSORFLOW_CONTRIB_TENSORRT_CONVERT_UTILS_H_
diff --git a/tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc b/tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc
index d12f738ac5..75e32559bb 100644
--- a/tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc
+++ b/tensorflow/contrib/tensorrt/kernels/trt_engine_op.cc
@@ -15,8 +15,8 @@ limitations under the License.
#include "tensorflow/contrib/tensorrt/kernels/trt_engine_op.h"
#include <algorithm>
-#include "tensorflow/contrib/tensorrt/convert/utils.h"
#include "tensorflow/contrib/tensorrt/convert/convert_nodes.h"
+#include "tensorflow/contrib/tensorrt/convert/utils.h"
#include "tensorflow/contrib/tensorrt/log/trt_logger.h"
#include "tensorflow/contrib/tensorrt/resources/trt_resource_manager.h"
#include "tensorflow/contrib/tensorrt/resources/trt_resources.h"
@@ -77,9 +77,8 @@ tensorflow::Status TRTEngineOp::ConstructFunctionHandle(OpKernelContext* ctx) {
}
auto fdef = lib->GetFunctionLibraryDefinition()->Find(funcdef_name_);
if (fdef == nullptr) {
- return tensorflow::errors::Internal(
- "Native FunctionDef ", funcdef_name_,
- " can't be found in function library");
+ return tensorflow::errors::Internal("Native FunctionDef ", funcdef_name_,
+ " can't be found in function library");
}
tensorflow::FunctionLibraryRuntime::InstantiateOptions inst_ops;
inst_ops.overlay_lib = nullptr;
@@ -128,8 +127,8 @@ TRTEngineOp::TRTEngineOp(OpKernelConstruction* context)
} else if (precision_string == "INT8") {
precision_mode_ = convert::INT8MODE;
}
- calibration_mode_ = (precision_mode_ == convert::INT8MODE &&
- calibration_data.size() == 0);
+ calibration_mode_ =
+ (precision_mode_ == convert::INT8MODE && calibration_data.size() == 0);
if (calibration_data.size()) {
calibrator_.reset(new TRTInt8Calibrator(calibration_data));
calibration_data.resize(0);
@@ -291,8 +290,8 @@ void TRTEngineOp::ComputeAsync(tensorflow::OpKernelContext* ctx,
std::vector<void*> buffers(num_binding);
for (int i = 0; i < ctx->num_inputs(); i++) {
const string inp_name = StrCat(kInputPHName, i);
- const size_t binding_index = trt_engine_ptr->getBindingIndex(
- inp_name.c_str());
+ const size_t binding_index =
+ trt_engine_ptr->getBindingIndex(inp_name.c_str());
const Tensor& input_tensor = ctx->input(i);
const TensorShape& input_shape = input_tensor.shape();
@@ -320,7 +319,7 @@ void TRTEngineOp::ComputeAsync(tensorflow::OpKernelContext* ctx,
default:
LOG(ERROR) << "Unknown TRT data type: " << int(dtype);
ctx->SetStatus(tensorflow::errors::InvalidArgument(
- "Unknown ouput TRT data type! ", int(dtype)));
+ "Unknown ouput TRT data type! ", static_cast<int>(dtype)));
return;
}
}
@@ -343,8 +342,8 @@ void TRTEngineOp::ComputeAsync(tensorflow::OpKernelContext* ctx,
&output_shape));
} else {
LOG(ERROR) << "output node not found, at " << output_name;
- ctx->SetStatus(tensorflow::errors::Internal(
- "output ", output_name, " couldn't be found!"));
+ ctx->SetStatus(tensorflow::errors::Internal("output ", output_name,
+ " couldn't be found!"));
return;
}
auto status = ctx->allocate_output(i, output_shape, &output_tensor);
@@ -370,7 +369,7 @@ void TRTEngineOp::ComputeAsync(tensorflow::OpKernelContext* ctx,
"INT8 outputs are not supported!"));
return;
default:
- LOG(ERROR) << "Unknown TRT data type: " << int(dtype);
+ LOG(ERROR) << "Unknown TRT data type: " << static_cast<int>(dtype);
ctx->SetStatus(tensorflow::errors::InvalidArgument(
"Unsupported output data type! ", int(dtype)));
return;
@@ -442,7 +441,7 @@ TRTEngineOp::EngineCtxPair& TRTEngineOp::GetEngine(int batch_size,
if (allocator == nullptr) {
// GetAllocator already set the Status.
return null_pair;
- };
+ }
infer->setGpuAllocator(allocator);
#endif
TrtUniquePtrType<nvinfer1::ICudaEngine> static_engine(
@@ -506,8 +505,7 @@ TRTEngineOp::EngineCtxPair& TRTEngineOp::GetEngine(int batch_size,
}
tensorflow::Status TRTEngineOp::AllocateCalibrationResources(
- tensorflow::OpKernelContext* ctx,
- TRTCalibrationResource** cr) {
+ tensorflow::OpKernelContext* ctx, TRTCalibrationResource** cr) {
auto cres = new TRTCalibrationResource();
*cr = cres;
// Get the allocator.
diff --git a/tensorflow/contrib/tensorrt/kernels/trt_engine_op.h b/tensorflow/contrib/tensorrt/kernels/trt_engine_op.h
index 0d2f9e8a9d..6fe318be6a 100644
--- a/tensorflow/contrib/tensorrt/kernels/trt_engine_op.h
+++ b/tensorflow/contrib/tensorrt/kernels/trt_engine_op.h
@@ -52,19 +52,17 @@ class TRTEngineOp : public AsyncOpKernel {
private:
// Execute calibration
- void ExecuteCalibration(OpKernelContext* ctx,
- AsyncHelper* helper);
+ void ExecuteCalibration(OpKernelContext* ctx, AsyncHelper* helper);
// Construct a function handle for executing native funcdef graph
Status ConstructFunctionHandle(OpKernelContext* ctx);
// Execute replaced native segment as function Op.
- void ExecuteNativeSegment(OpKernelContext* ctx,
- AsyncHelper* helper);
+ void ExecuteNativeSegment(OpKernelContext* ctx, AsyncHelper* helper);
// Allocate necessary resources for calibration
- Status AllocateCalibrationResources(
- OpKernelContext* ctx, TRTCalibrationResource** cr);
+ Status AllocateCalibrationResources(OpKernelContext* ctx,
+ TRTCalibrationResource** cr);
// TODO(samikama): context should go to a resource manager!
typedef std::pair<TrtUniquePtrType<nvinfer1::ICudaEngine>,
diff --git a/tensorflow/contrib/tensorrt/python/trt_convert.py b/tensorflow/contrib/tensorrt/python/trt_convert.py
index 490c74a701..79f512dbcf 100644
--- a/tensorflow/contrib/tensorrt/python/trt_convert.py
+++ b/tensorflow/contrib/tensorrt/python/trt_convert.py
@@ -21,9 +21,9 @@ from __future__ import print_function
# pylint: disable=unused-import,line-too-long
import six as _six
from tensorflow.contrib.tensorrt.wrap_conversion import calib_convert
-from tensorflow.contrib.tensorrt.wrap_conversion import trt_convert
-from tensorflow.contrib.tensorrt.wrap_conversion import get_loaded_tensorrt_version
from tensorflow.contrib.tensorrt.wrap_conversion import get_linked_tensorrt_version
+from tensorflow.contrib.tensorrt.wrap_conversion import get_loaded_tensorrt_version
+from tensorflow.contrib.tensorrt.wrap_conversion import trt_convert
from tensorflow.core.framework import graph_pb2
from tensorflow.core.protobuf import rewriter_config_pb2
from tensorflow.python.framework import errors
@@ -58,6 +58,10 @@ def create_inference_graph(input_graph_def,
precision_mode: one of 'FP32', 'FP16' and 'INT8'
minimum_segment_size: the minimum number of nodes required for a subgraph to
be replaced by TRTEngineOp.
+ is_dynamic_op: whether to generate dynamic TRT ops which will build the TRT
+ network and engine at run time.
+ maximum_cached_engines: max number of cached TRT engines in dynamic TRT ops.
+ cached_engine_batches: batch sizes used to pre-create cached engines.
Returns:
New GraphDef with TRTEngineOps placed in graph replacing subgraphs.
@@ -81,7 +85,7 @@ def create_inference_graph(input_graph_def,
"TensorRT %s but library loaded from environment is TensorRT %s" %
(".".join([str(x) for x in compiled_version]),
".".join([str(x) for x in loaded_version])) +
- ". Please make sure that correct version of TensorRT "\
+ ". Please make sure that correct version of TensorRT " +
"is available in the system and added to ldconfig or LD_LIBRARY_PATH"
)
raise RuntimeError("Incompatible TensorRT library version")
@@ -178,7 +182,7 @@ def calib_graph_to_infer_graph(calibration_graph_def, is_dynamic_op=False):
is_calib_graph = False
for n in calibration_graph_def.node:
if n.op == "TRTEngineOp":
- is_calib_graph = is_calib_graph or len(n.attr["calibration_data"].s) == 0
+ is_calib_graph = is_calib_graph or not n.attr["calibration_data"].s
if not is_calib_graph:
tf_logging.error(
"Not a calib graph. Doesn't seem to contain any calibration nodes.")
diff --git a/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc b/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc
index 59ae860bc0..32e81858b9 100644
--- a/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc
+++ b/tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.cc
@@ -16,7 +16,6 @@ limitations under the License.
#include "tensorflow/contrib/tensorrt/resources/trt_int8_calibrator.h"
#include <atomic>
-#include <chrono>
#include <unordered_map>
#include "tensorflow/core/platform/logging.h"
diff --git a/tensorflow/contrib/tensorrt/resources/trt_resources.h b/tensorflow/contrib/tensorrt/resources/trt_resources.h
index 76863503bd..b7d5ffd674 100644
--- a/tensorflow/contrib/tensorrt/resources/trt_resources.h
+++ b/tensorflow/contrib/tensorrt/resources/trt_resources.h
@@ -49,15 +49,15 @@ class TRTCalibrationResource : public tensorflow::ResourceBase {
string DebugString() override {
std::stringstream oss;
- using std::hex;
using std::dec;
using std::endl;
+ using std::hex;
oss << " Calibrator = " << hex << calibrator_.get() << dec << endl
- << " Builder = " << hex << builder_.get() << dec << endl
- << " Engine = " << hex << engine_.get() << dec << endl
- << " Logger = " << hex << &logger_ << dec << endl
- << " Allocator = " << hex << allocator_.get() << dec << endl
- << " Thread = " << hex << thr_.get() << dec << endl;
+ << " Builder = " << hex << builder_.get() << dec << endl
+ << " Engine = " << hex << engine_.get() << dec << endl
+ << " Logger = " << hex << &logger_ << dec << endl
+ << " Allocator = " << hex << allocator_.get() << dec << endl
+ << " Thread = " << hex << thr_.get() << dec << endl;
return oss.str();
}
diff --git a/tensorflow/contrib/tensorrt/test/test_tftrt.py b/tensorflow/contrib/tensorrt/test/test_tftrt.py
index 5e74f9295d..090aa8bdb0 100644
--- a/tensorflow/contrib/tensorrt/test/test_tftrt.py
+++ b/tensorflow/contrib/tensorrt/test/test_tftrt.py
@@ -76,7 +76,7 @@ def get_multi_engine_graph_def(mode="FP32"):
g = ops.Graph()
with g.as_default():
x = aops.placeholder(shape=[None, 3, 7, 5], name="input", dtype=dtype)
- with g.name_scope("Global_scope") as scope:
+ with g.name_scope("Global_scope"):
with g.name_scope("first_scope"):
e = cop.constant(
np.random.randn(3, 2, 3, 4), name="weights", dtype=dtype)
@@ -92,15 +92,14 @@ def get_multi_engine_graph_def(mode="FP32"):
b = cop.constant(np.random.randn(1, 4, 1, 1), name="bias2", dtype=dtype)
q = conv / b
- c = cop.constant(np.random.randn(1, 4, 1, 1), name="bias3", dtype=dtype)
edge = mops.sin(q)
edge1 = mops.cos(conv)
with g.name_scope("test_scope"):
de = edge + edge1
- t = t - edge1
- q = q * edge
- t = t + q
- t = t - de
+ t -= edge1
+ q *= edge
+ t += q
+ t -= de
k = aops.squeeze(t, name="output")
print(k.dtype)
return g.as_graph_def()
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-22 23:24:39 +0000