#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/checkpoint_reader.h"
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_op_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/compiler/jit/flags.h"

==============================================================================*/
#include "tensorflow/c/experimental/gradients/math_grad.h"

#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/unified_api_testutil.h"
#include "tensorflow/c/experimental/gradients/grad_test_helper.h"
#include "tensorflow/c/experimental/gradients/tape/tape_context.h"

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"
#include "tensorflow/c/eager/c_api_test_util.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/core/common_runtime/eager/eager_operation.h"
#include "tensorflow/core/distributed_runtime/rpc/grpc_server_lib.h"

#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/parallel_device/parallel_device_testlib.h"
#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/core/common_runtime/eager/context.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/lib/core/status_test_util.h"
#include "tensorflow/core/platform/test.h"

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

#include "absl/strings/str_cat.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/c_api_unified_experimental_internal.h"
#include "tensorflow/c/eager/gradients_internal.h"
#include "tensorflow/core/common_runtime/eager/attr_builder.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/errors.h"

namespace tensorflow {

#include <string>

#include "include/dlpack/dlpack.h"  // from @dlpack
#include "tensorflow/c/eager/c_api.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/core/common_runtime/eager/tensor_handle.h"
#include "tensorflow/core/framework/tensor.h"
#include "tensorflow/core/framework/tensor_reference.h"

#include <unordered_set>
#include <vector>

#include "absl/status/status.h"
#include "tensorflow/c/c_api_macros.h"
#include "tensorflow/c/experimental/grappler/grappler_internal.h"
#include "tensorflow/c/tf_buffer.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/framework/op.h"

#include <string>
#include <utility>

#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/tfe_cancellation_manager_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/c/tf_status_internal.h"
#include "tensorflow/core/lib/gtl/cleanup.h"
#include "tensorflow/core/platform/env.h"
#include "tensorflow/core/platform/mutex.h"

==============================================================================*/
#include "tensorflow/c/experimental/grappler/grappler.h"

#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/experimental/grappler/grappler_internal.h"
#include "tensorflow/c/tf_buffer_internal.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/grappler/clusters/single_machine.h"
#include "tensorflow/core/grappler/costs/graph_properties.h"

  if (!maybe_typed_outputs.has_value()) {
    TF_SetStatus(status, TF_INTERNAL, "OK status but no value was returned.");
    return;
  }

  std::vector<MaybeParallelTensorOwned> typed_outputs(
      std::move(maybe_typed_outputs.value()));

  if (typed_outputs.size() > *num_outputs) {
    TF_SetStatus(status, TF_INTERNAL,
                 "The allocated output buffer was too small.");
    return;
  }