#include "tensorflow/cc/framework/gradients.h"
#include "tensorflow/cc/framework/ops.h"
#include "tensorflow/cc/framework/scope_internal.h"
#include "tensorflow/cc/ops/while_loop.h"
#include "tensorflow/cc/saved_model/loader.h"
#include "tensorflow/core/distributed_runtime/server_lib.h"
#include "tensorflow/core/framework/logging.h"
#include "tensorflow/core/framework/op_gen_lib.h"

    const TP_OptimizerConfigs tp_configs, const char* device_type) {
  ConfigList configs;
  // disable_model_pruning is turned off by default.
  if (tp_configs.disable_model_pruning == TF_TriState_On)
    configs.disable_model_pruning = true;
  else
    configs.disable_model_pruning = false;
  // The other configs are turned on by default.
  CONFIG_TOGGLE(implementation_selector);

      RunModel(forward, ctx, inputs, model_outputs, use_function));
  AbstractTensorHandlePtr model_out(model_outputs[0]);

  TF_Tensor* model_out_tensor;
  TF_RETURN_IF_ERROR(GetValue(model_out.get(), &model_out_tensor));
  int num_dims_out = TF_NumDims(model_out_tensor);
  TF_DeleteTensor(model_out_tensor);

  // If the output is a scalar, then return the scalar output
  if (num_dims_out == 0) {
    outputs[0] = model_out.release();

  TF_RETURN_IF_ERROR(ops::SparseSoftmaxCrossEntropyWithLogits(
      ctx, inputs[0], inputs[1], &loss, &backprop,
      "SparseSoftmaxCrossEntropyWithLogits"));
  // `gradient_checker` only works with model that returns only 1 tensor.
  // Although, `ops::SparseSoftmaxCrossEntropyWithLogits` returns 2 tensors, the
  // second tensor isn't needed for computing gradient so we could safely drop
  // it.
  outputs[0] = loss;

  SetViaProto(desc_, {});
  FinishAndVerify(desc_, {});
}

TEST(CAPI, SavedModel) {
  // Load the saved model.
  const string saved_model_dir = tensorflow::GetDataDependencyFilepath(
      tensorflow::io::JoinPath("tensorflow", "cc", "saved_model", "testdata",
                               "half_plus_two", "00000123"));
  TF_SessionOptions* opt = TF_NewSessionOptions();