#include "tensorflow/c/tensor_interface.h"
#include "tensorflow/core/framework/cancellation.h"
#include "tensorflow/core/framework/device_attributes.pb.h"
#include "tensorflow/core/framework/op_def.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/casts.h"
#include "tensorflow/core/platform/status.h"
#include "tensorflow/core/util/managed_stack_trace.h"

struct TFE_Op;

namespace tensorflow {

#ifndef TENSORFLOW_C_EAGER_TFE_MONITORING_READER_INTERNAL_H_
#define TENSORFLOW_C_EAGER_TFE_MONITORING_READER_INTERNAL_H_

#include <memory>

#include "tensorflow/core/lib/monitoring/cell_reader.h"

struct TFE_MonitoringCounterReader {
  explicit TFE_MonitoringCounterReader(const char* name) {
    counter = std::make_unique<

// Unified Execution APIs for Eager and tracing backends.
// =============================================================================

// -----------------------------------------------------------------------------
// Core APIs
// -----------------------------------------------------------------------------

// A TF_ExecutionContext stores knowledge about how to execute an operation.

    absl::MutexLock lock(&mu_);
    return DeleteLocked(key);
  }

  /// Look up the entry with key `key` and copy it to `value` if found. Returns
  /// true if an entry was found for `key`, and its timestamp is not more than
  /// max_age_ seconds in the past.
  bool Lookup(const std::string& key, T* value) {
    if (max_age_ == 0) {
      return false;
    }
    absl::MutexLock lock(&mu_);
    return LookupLocked(key, value);
  }

#include "tensorflow/c/eager/parallel_device/parallel_device.h"
#include "tensorflow/c/eager/parallel_device/parallel_device_lib.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace parallel_device {

// A helper for performing common operations on variables. A much more
// restricted stand-in for tf.Variable in Python.
class Variable {
 public:
  // Construct a Variable from a resource-dtype TFE_TensorHandle and an

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/tf_datatype.h"
#include "tensorflow/core/platform/logging.h"
#include "tensorflow/core/platform/tstring.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/protobuf/tensorflow_server.pb.h"

// Return a tensor handle containing a float scalar
TFE_TensorHandle* TestScalarTensorHandle(TFE_Context* ctx, float value);

// the same shape, although this requirement may be relaxed in the future.
//
// `device_name` must not name an existing physical or custom device (see
// the documentation for TFE_RegisterCustomDevice for more information).
//
// Tensors may be copied on or off the device explicitly using
// TPUReplicatedInput and TPUReplicatedOutput respectively. For example, with

TF_CAPI_EXPORT extern void TF_DeleteFile(const char* filename,
                                         TF_Status* status);

// Retrieves the next item from the given TF_StringStream and places a pointer
// to it in *result. If no more items are in the list, *result is set to NULL
// and false is returned.
//
// Ownership of the items retrieved with this function remains with the library.
// Item points are invalidated after a call to TF_StringStreamDone.

#ifndef TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_
#define TENSORFLOW_C_EAGER_ABSTRACT_FUNCTION_H_

#include "absl/status/statusor.h"
#include "tensorflow/core/framework/function.pb.h"
#include "tensorflow/core/platform/intrusive_ptr.h"
#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

#define TENSORFLOW_C_EXPERIMENTAL_FILESYSTEM_MODULAR_FILESYSTEM_REGISTRATION_H_

#include "tensorflow/c/experimental/filesystem/filesystem_interface.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace filesystem_registration {

// Implementation for filesystem registration
//
// Don't call this directly. Instead call `RegisterFilesystemPlugin`.