opts.prefix = prefix;

  for (int i = 0; i < dst_inputs.size(); ++i) {
    opts.input_map[ToTensorId(src_inputs[i])] =
        TensorId(dst_inputs[i].node()->name(), dst_inputs[i].index());
  }
  opts.skip_mapped_nodes = true;

  for (const tensorflow::Operation& op : control_deps) {
    opts.control_dependencies.push_back(op.node()->name());
  }

  for (int i = 0; i < nreturn_nodes; ++i) {

#include <optional>
#include <utility>
#include <vector>

#include <gtest/gtest.h>
#include "absl/log/check.h"
#include "xla/pjrt/c/pjrt_c_api.h"
#include "xla/pjrt/c/pjrt_c_api_cpu.h"
#include "xla/pjrt/c/pjrt_c_api_wrapper_impl.h"
#include "xla/pjrt/pjrt_api.h"
#include "xla/pjrt/pjrt_c_api_client.h"
#include "xla/pjrt/tfrt_cpu_pjrt_client.h"
#include "xla/shape.h"
#include "xla/shape_util.h"
#include "tensorflow/core/framework/types.h"

  }
  result.emplace(std::move(result_content));
  return result;
}

// Used as an argument to TFE_NewCustomDeviceTensorHandle, indicating how
// ParallelTensors wrapped in TFE_TensorHandles should be cleaned up once their
// reference counts drop to zero.
void ParallelTensorDeallocator(void* data) {
  delete reinterpret_cast<ParallelTensor*>(data);
}

    const auto& data = block->data;
    if (offset >= pos + data.size()) {
      // The requested offset is at or beyond the end of the file. This can
      // happen if `offset` is not block-aligned, and the read returns the last
      // block in the file, which does not extend all the way out to `offset`.
      std::stringstream os;

      // and hence expect the input to be forwarded to the return tensor.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));
    } else {
      // In sync mode, forwarding can't really happen since the client code will
      // have a reference count on the input tensor while the kernel is being
      // executed and thus it cannot be re-used for the return tensor.
      EXPECT_NE(orig_ptr, TF_TensorData(t));