using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringStringGauge1 : TFE_MonitoringGauge<tensorflow::string, 1> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringStringGauge2 : TFE_MonitoringGauge<tensorflow::string, 2> {
  using TFE_MonitoringGauge::TFE_MonitoringGauge;
};
struct TFE_MonitoringStringGauge3 : TFE_MonitoringGauge<tensorflow::string, 3> {

using tensorflow::AbstractFunction;
using tensorflow::AbstractTensorHandle;
using tensorflow::DataType;
using tensorflow::dyn_cast;
using tensorflow::OutputList;
using tensorflow::Status;
using tensorflow::unwrap;
using tensorflow::wrap;
using tensorflow::tracing::CreateTracingExecutionContext;
using tensorflow::tracing::SetDefaultTracingEngine;

#include "tensorflow/c/experimental/ops/nn_ops.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

using std::vector;
using tensorflow::ops::BiasAddGrad;
using tensorflow::ops::Mul;
using tensorflow::ops::ReluGrad;

namespace tensorflow {
namespace gradients {
namespace {

class ReluGradientFunction : public GradientFunction {
 public:

## Conflict Resolution

using tensorflow::PartialTensorShape;
using tensorflow::RunMetadata;
using tensorflow::RunOptions;
using tensorflow::Session;
using tensorflow::Status;
using tensorflow::string;
using tensorflow::Tensor;
using tensorflow::TensorId;
using tensorflow::TensorShapeProto;
using tensorflow::VersionDef;
using tensorflow::errors::FailedPrecondition;
using tensorflow::errors::InvalidArgument;
using tensorflow::errors::OutOfRange;

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);
  ~GraphFunction() override;

TFCI_ARTIFACT_FINAL_GCS_URI="gs://tensorflow/versions/"
TFCI_ARTIFACT_FINAL_PYPI_ARGS="--config-file=$KOKORO_KEYSTORE_DIR/73361_tensorflow_pypirc_using_global_api_token --repository pypi-warehouse"
TFCI_ARTIFACT_FINAL_PYPI_ENABLE=1
TFCI_ARTIFACT_LATEST_GCS_URI="gs://tensorflow/versions/latest/"
TFCI_ARTIFACT_STAGING_GCS_ENABLE=1

} TFE_ContextDevicePlacementPolicy;
// LINT.ThenChange(//tensorflow/c/eager/immediate_execution_context.h)

// Sets the default execution mode (sync/async). Note that this can be
// overridden per thread using TFE_ContextSetExecutorForThread.
TF_CAPI_EXPORT extern void TFE_ContextOptionsSetAsync(TFE_ContextOptions*,
                                                      unsigned char enable);

+++ b/locale/xlocale.h
@@ -20,6 +20,9 @@
 #ifndef _XLOCALE_H
 #define _XLOCALE_H	1
 
+#ifndef _BITS_TYPES___LOCALE_T_H
+#define _BITS_TYPES___LOCALE_T_H 1
+
 /* Structure for reentrant locale using functions.  This is an
    (almost) opaque type for the user level programs.  The file and
    this data structure is not standardized.  Don't rely on it.  It can
@@ -41,4 +44,6 @@ typedef struct __locale_struct

//       if (d.IsBad()) {
//         LOG(ERROR) << "Bad Data";
//         return;
//       }
//       PushGoodData(d);
//     }
//   }
//
// You can use Cleanup<F> directly, instead of using MakeCleanup and auto,
// but there's rarely a reason to do that.
//
// You can call 'release()' on a Cleanup object to cancel the cleanup.

#ifndef TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_PLUGINS_GCS_CLEANUP_H_