TF_CAPI_EXPORT extern void TFE_ContextUpdateServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status);

// This API is for experimental usage and may be subject to change.
TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,

}

TF_Tensor* BoolTensor(bool v) {
  const int num_bytes = sizeof(bool);
  bool* values = new bool[1];
  values[0] = v;
  return TF_NewTensor(TF_BOOL, nullptr, 0, values, num_bytes, &BoolDeallocator,
                      nullptr);
}

TF_Tensor* Int8Tensor(const int64_t* dims, int num_dims, const char* values) {
  int64_t num_values = 1;
  for (int i = 0; i < num_dims; ++i) {
    num_values *= dims[i];
  }

// Prepare tracing to the expected number of output for an operation.
void TF_OutputListSetNumOutputs(TF_OutputList* o, int num_outputs, TF_Status*);
// Return the number of outputs in the list.
int TF_OutputListNumOutputs(TF_OutputList* o);
// Return the `i`th output in the list.
TF_AbstractTensor* TF_OutputListGet(TF_OutputList* o, int i);
// Append a tensor at the end of the output list, growing its size by one.

    const TF_GrapplerItem* item, char** values, size_t* lengths, int num_values,
    void* storage, size_t storage_size, TF_Status* status);

// Get a set of node names for fetch nodes. Fills in `values` and `lengths`,
// they will be used in `TF_GetFetchNodesList`
TF_CAPI_EXPORT extern void TF_GetFetchNodesListSize(const TF_GrapplerItem* item,
                                                    int* num_values,

  virtual bool HasCustomDeviceInput() const = 0;

  virtual const tensorflow::OpDef* OpDef() const = 0;

  virtual Status InputLength(const char* input_name, int* length) = 0;
  virtual Status OutputLength(const char* output_name, int* length) = 0;

  // Set stack trace to be used for potential async error reporting.
  virtual void SetStackTrace(ManagedStackTrace stack_trace) = 0;

namespace tensorflow {
namespace gradients {
Status NotDifferentiableGradientFunction::Compute(
    AbstractContext* ctx, absl::Span<AbstractTensorHandle* const> grad_outputs,
    absl::Span<AbstractTensorHandle*> grad_inputs) {
  for (int i = 0; i < grad_inputs.size(); i++) {
    grad_inputs[i] = nullptr;
  }
  return OkStatus();
}

Status RegisterNotDifferentiable(GradientRegistry* registry, const string& op) {

 * hold the numerical gradient data at the end of the function.
 */
Status CalcNumericalGrad(AbstractContext* ctx, Model forward,
                         absl::Span<AbstractTensorHandle* const> inputs,
                         int input_index, bool use_function,
                         AbstractTensorHandle** numerical_grad);

}  // namespace gradients
}  // namespace tensorflow

      MatMulOp(context, hcpu, hdevice), TFE_DeleteOp);
  TFE_OpSetDevice(matmul.get(), name, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  TFE_TensorHandle* retval;
  int num_retvals = 1;
  TFE_Execute(matmul.get(), &retval, &num_retvals, status.get());
  ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get());
  ASSERT_TRUE(executed);

  TFE_DeleteTensorHandle(retval);

// LINT.ThenChange()

// LINT.IfChange(read_only_memory_region_ops_version)
constexpr int TF_READ_ONLY_MEMORY_REGION_OPS_API = 0;
constexpr int TF_READ_ONLY_MEMORY_REGION_OPS_ABI = 0;
constexpr size_t TF_READ_ONLY_MEMORY_REGION_OPS_SIZE =
    sizeof(TF_ReadOnlyMemoryRegionOps);
// LINT.ThenChange()

// LINT.IfChange(filesystem_ops_version)
constexpr int TF_FILESYSTEM_OPS_API = 0;

#include "tensorflow/core/util/device_name_utils.h"

namespace tensorflow {
class EagerExecutor;
class EagerContext;
class CustomDevice;
class CustomDeviceOpHandler;
class Device;

// LINT.IfChange
// Note: Keep in sync with exported copy of enum in eager/c_api.h.
enum ContextDevicePlacementPolicy {
  // Running operations with input tensors on the wrong device will fail.
  DEVICE_PLACEMENT_EXPLICIT = 0,