return result;
}

int64_t TFE_MonitoringReadCounter0(TFE_MonitoringCounterReader* cell_reader) {
  int64_t result = cell_reader->Read();

  return result;
}

int64_t TFE_MonitoringReadCounter1(TFE_MonitoringCounterReader* cell_reader,
                                   const char* label) {
  int64_t result = cell_reader->Read(label);

  return result;

  TF_DeleteStatus(status);
  return counter;
}

void IncrementCounter0(TFE_MonitoringCounter0* counter, int64_t delta) {
  auto* cell = TFE_MonitoringGetCellCounter0(counter);
  TFE_MonitoringCounterCellIncrementBy(cell, delta);
}

TFE_MonitoringCounter1* CreateCounter1(const char* counter_name,
                                       const char* label) {
  TF_Status* status = TF_NewStatus();

_current_module.__path__ = [_module_dir] + _current_module.__path__

_current_module.nn.rnn_cell = _KerasLazyLoader(
    globals(),
    submodule="__internal__.legacy.rnn_cell",
    name="rnn_cell",
    mode="v1")
if _tf_uses_legacy_keras:
  _module_dir = _module_util.get_parent_dir_for_name(
      "tf_keras.api._v1.keras.__internal__.legacy.rnn_cell")
else:
  _module_dir = _module_util.get_parent_dir_for_name(

};

struct TFE_MonitoringIntGaugeCell {
  tensorflow::monitoring::GaugeCell<int64_t> cell;
};
struct TFE_MonitoringStringGaugeCell {
  tensorflow::monitoring::GaugeCell<tensorflow::string> cell;
};
struct TFE_MonitoringBoolGaugeCell {
  tensorflow::monitoring::GaugeCell<bool> cell;
};

template <typename ValueType, int NumLabels>
struct TFE_MonitoringGauge {
  template <typename... LabelDesc>

#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<
        ::tensorflow::monitoring::testing::CellReader<int64_t>>(name);
  }

#define TENSORFLOW_C_EAGER_C_API_EXPERIMENTAL_READER_H_

#include "tensorflow/c/eager/c_api.h"

#ifdef __cplusplus
extern "C" {
#endif

// Test only exports of the monitoring Cell Reader API which allows tests to
// read current values from streamz counters defined in other modules.
//
// The code under test will have created streamz counters like this:

// Wraps a pointer to a context implementation.
//
// WARNING: Since the underlying object could be ref-counted a user of this
// interface cannot destruct the underlying context object. Instead, call
// TFE_DeleteContext who calls Release() on the context pointer and deletes
// the TFE_Context structure.
typedef struct TFE_Context TFE_Context;

namespace tensorflow {

  tensorflow::mutex mu TF_ACQUIRED_AFTER(TF_Graph::mu);
  int last_num_graph_nodes;

  // If true, TF_SessionRun and similar methods will call
  // ExtendSessionGraphHelper before running the graph (this is the default
  // public behavior). Can be set to false if the caller needs to call
  // ExtendSessionGraphHelper manually.
  std::atomic<bool> extend_before_run;
};

struct TF_ImportGraphDefOptions {

                                   absl::Span<AbstractTensorHandle* const>,
                                   absl::Span<AbstractTensorHandle*>)>;

// Runs `model` maybe wrapped in a function call op. This can be thought as
// being equivalent to the following python code.
//
// if use_function:
//   outputs = tf.function(model)(inputs)
// else:
//   outputs = model(inputs)

                                            int keep_alive_secs) = 0;

  // Set up a multi-client distributed execution environment. Must be called
  // on all tasks in the cluster. This call internally coordinates with other
  // tasks to initialize the eager context and TF server for multi-client
  // execution.
  virtual Status EnableCollectiveOps(const ServerDef& server_def) = 0;