close(src_fd);
  close(dst_fd);
  if (error_code != 0) {
    errno = error_code;
    return -1;
  } else {
    return 0;
  }
}

int RemoveSpecialDirectoryEntries(const struct dirent* entry) {
  return strcmp(entry->d_name, ".") != 0 && strcmp(entry->d_name, "..") != 0;
}

  job_def->set_name(job_name);
  for (int i = 0; i < num_tasks; i++) {
    int port = tensorflow::testing::PickUnusedPortOrDie();
    job_def->mutable_tasks()->insert(
        {i, tensorflow::strings::StrCat("localhost", ":", port)});
    LOG(INFO) << "Picked test port: " << port << " for job: " << job_name
              << ", task: " << i;
  }
  return server_def;
}

namespace tensorflow {
namespace parallel_device {

  auto entry = GetFactories().find(name);
  if (entry != GetFactories().end()) {
    default_factory = GetFactories().find(name)->second;
    return absl::OkStatus();
  }
  string msg = absl::StrCat(
      "No tracing engine factory has been registered with the key '", name,
      "' (available: ");
  // Ensure deterministic (sorted) order in the error message
  std::set<string> factories_sorted;

    // TODO(skyewm): prefix names with underscore (requires some plumbing)
    if (!CreateInput(inputs[i], cond_graph, StrCat("cond_input", i).c_str(),
                     &cond_inputs[i], status)) {
      break;
    }
    if (!CreateInput(inputs[i], body_graph, StrCat("body_input", i).c_str(),
                     &body_inputs[i], status)) {
      break;
    }
  }

#include "tensorflow/c/eager/tfe_context_internal.h"
#include "tensorflow/c/eager/tfe_tensorhandle_internal.h"
#include "tensorflow/c/tf_status.h"
#include "tensorflow/core/lib/llvm_rtti/llvm_rtti.h"
#include "tensorflow/core/platform/strcat.h"

// =============================================================================
// Public C API entry points
// These are only the entry points specific to the Eager API.

  tensorflow::JobDef* job_def = server_def->mutable_cluster()->mutable_job(0);
  int port = tensorflow::testing::PickUnusedPortOrDie();
  job_def->mutable_tasks()->at(task_index) =
      tensorflow::strings::StrCat("localhost:", port);
}

void CheckTFE_TensorHandleHasFloats(TFE_TensorHandle* handle,
                                    const std::vector<float>& expected_values) {

      session->graph,
      tensorflow::strings::StrCat("fifo_queue_enqueue_", tensor_id).c_str());
  if (enqueue_op == nullptr) {
    status->status = tensorflow::errors::Internal(
        "Unable to find the enqueue node in the TF graph.");
    return;
  }

  TF_Operation* placeholder_op = TF_GraphOperationByName(
      session->graph,
      tensorflow::strings::StrCat("arg_tensor_enqueue_", tensor_id).c_str());

// SECTION 1. Implementation for `TF_RandomAccessFile`
// ----------------------------------------------------------------------------
namespace tf_random_access_file {

typedef struct PosixFile {
  const char* filename;
  int fd;
} PosixFile;

static void Cleanup(TF_RandomAccessFile* file) {
  auto posix_file = static_cast<PosixFile*>(file->plugin_file);
  close(posix_file->fd);

    // The default NumPy-style output can be distractingly long in error
    // messages.
    value_string = absl::StrCat(value_string.substr(0, 100), " [...]");
  }
  Status s;
  const char* device_name = DeviceName(&s);
  if (!s.ok()) {
    device_name = "<error fetching device name>";
  }
  return absl::StrCat("TensorHandle(", value_string, ", shape=", shape_string,

  TF_RETURN_IF_ERROR(op->Reset("ZerosLike", /*raw_device_name=*/nullptr));
  if (isa<tracing::TracingOperation>(op.get())) {
    TF_RETURN_IF_ERROR(dyn_cast<tracing::TracingOperation>(op.get())->SetOpName(
        absl::StrCat("ZerosLike", ToId(t)).c_str()));
  }
  TF_RETURN_IF_ERROR(op->AddInput(t));
  int num_outputs = 1;
  std::vector<AbstractTensorHandle*> outputs(num_outputs);
  TF_RETURN_IF_ERROR(