// Enables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextEnableGraphCollection(TFE_Context* ctx);

// Disables only graph collection in RunMetadata on the functions executed from
// this context.
TF_CAPI_EXPORT extern void TFE_ContextDisableGraphCollection(TFE_Context* ctx);

// TODO(fishx): Move these monitoring APIs into a separate file.

TFE_Op* AddOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b);

// Return a matmul op multiplying `a` by `b`.
TFE_Op* MatMulOp(TFE_Context* ctx, TFE_TensorHandle* a, TFE_TensorHandle* b);

// Return an identity op.
TFE_Op* IdentityOp(TFE_Context* ctx, TFE_TensorHandle* a);

// Return a shape op fetching the shape of `a`.
TFE_Op* ShapeOp(TFE_Context* ctx, TFE_TensorHandle* a);

  template <typename DataType>
  std::unique_ptr<ParallelTensor> ScalarsFromSequence(
      absl::Span<const DataType> values, TFE_Context* context,
      TF_Status* status) const;

  // A parallel tensor with scalar integers numbering component devices.
  std::unique_ptr<ParallelTensor> DeviceIDs(TFE_Context* context,
                                            TF_Status* status) const;

  // The number of devices operations run on.

// `funcs` and sets status to OK. The caller takes ownership of
// all the returned TF_Functions. They must be deleted with TF_DeleteFunction.
// On error, returns 0, sets status to the encountered error, and the contents
// of funcs will be undefined.
TF_CAPI_EXPORT extern int TF_GraphGetFunctions(TF_Graph* g, TF_Function** funcs,
                                               int max_func, TF_Status* status);

//
// TODO(ashankar): Merge with TF_Session?
typedef struct TFE_Context TFE_Context;

TF_CAPI_EXPORT extern TFE_Context* TFE_NewContext(
    const TFE_ContextOptions* opts, TF_Status* status);
TF_CAPI_EXPORT extern void TFE_DeleteContext(TFE_Context* ctx);
TF_CAPI_EXPORT extern TF_DeviceList* TFE_ContextListDevices(TFE_Context* ctx,
                                                            TF_Status* status);

  virtual ~ImmediateExecutionDistributedManager() {}

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created
  // on remote tasks will be considered stale and garbage collected after

==============================================================================*/
#ifndef TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_
#define TENSORFLOW_C_EAGER_UNIFIED_API_TESTUTIL_H_

#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental.h"

// Returns the graph content in a human-readable format, with length set in
// `len`. The format is subject to change in the future.
// The returned string is heap-allocated, and caller should call free() on it.
TF_CAPI_EXPORT extern const char* TF_GraphDebugString(TF_Graph* graph,
                                                      size_t* len);

// Returns the function content in a human-readable format, with length set in

#ifndef TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_CONTEXT_H_
#define TENSORFLOW_C_EAGER_IMMEDIATE_EXECUTION_CONTEXT_H_

#include <functional>
#include <map>
#include <memory>
#include <vector>

#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/immediate_execution_distributed_manager.h"

#ifndef TENSORFLOW_C_EAGER_GRADIENTS_H_
#define TENSORFLOW_C_EAGER_GRADIENTS_H_

#include "absl/container/flat_hash_map.h"
#include "tensorflow/c/eager/abstract_context.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/tape.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"

namespace tensorflow {
namespace gradients {