ops->filesystem_ops = static_cast<TF_FilesystemOps*>(
      plugin_memory_allocate(TF_FILESYSTEM_OPS_SIZE));
  ops->filesystem_ops->init = tf_posix_filesystem::Init;
  ops->filesystem_ops->cleanup = tf_posix_filesystem::Cleanup;
  ops->filesystem_ops->new_random_access_file =
      tf_posix_filesystem::NewRandomAccessFile;

int TF_CheckpointReaderHasTensor(TF_CheckpointReader* reader,
                                 const char* name) {
  return reader->HasTensor(name);
}

const char* TF_CheckpointReaderGetVariable(TF_CheckpointReader* reader,
                                           int index) {
  return reader->variable_list[index].c_str();
}

int TF_CheckpointReaderSize(TF_CheckpointReader* reader) {

  TF_RETURN_IF_ERROR(
      env->GetSymbolFromLibrary(dso_handle, "TF_InitGraph", &dso_symbol));

  // Step 2: Call `TF_InitPlugin`
  auto init_fn = reinterpret_cast<TFInitGraphPluginFn>(dso_symbol);
  return InitGraphPlugin(init_fn);
}

absl::Status InitGraphPlugin(TFInitGraphPluginFn init_fn) {
  TP_OptimizerRegistrationParams params{
      TP_OPTIMIZER_REGISTRATION_PARAMS_STRUCT_SIZE};

}
Status SetAttrStringList(AbstractOperation* op_, const char* attr_name,
                         const void* const* values, const size_t* lengths,
                         int num_values, ForwardOperation* forward_op_) {
  std::vector<StringPiece> v(num_values);
  for (int i = 0; i < num_values; ++i) {
    v[i] = StringPiece(static_cast<const char*>(values[i]), lengths[i]);
  }
  forward_op_->attrs.Set(attr_name, v);

// data.
bool IsValidStrideCompactRowMajorData(int64_t* shape_arr, int64_t* stride_arr,
                                      int ndim) {
  bool valid = true;
  int64_t expected_stride = 1;
  for (int i = ndim - 1; i >= 0; --i) {
    // Empty tensors are always compact regardless of strides.
    if (shape_arr[i] == 0) return true;

TF_CAPI_EXPORT extern void TFE_ContextSetServerDefWithTimeout(
    TFE_Context* ctx, int keep_alive_secs, const void* proto, size_t proto_len,
    int64_t init_timeout_in_ms, TF_Status* status,
    bool clear_existing_contexts) {
  TFE_ContextSetServerDefWithTimeoutAndRetries(
      ctx, keep_alive_secs, proto, proto_len, init_timeout_in_ms,
      /*retries=*/0, status, clear_existing_contexts);
}

  }
  return server_def;
}

tensorflow::ServerDef GetServerDef(int num_tasks) {
  return GetServerDef("localhost", num_tasks);
}

tensorflow::ServerDef GetMultiClientServerDef(const std::string& job_name,
                                              int num_tasks,
                                              int num_virtual_gpus) {
  tensorflow::ServerDef server_def;
  server_def.set_protocol("grpc");

    const TF_Graph* fn_body, const char* fn_name, int ninputs,
    const TF_Output* inputs, std::vector<OutputTensor>* input_tensors,
    std::unordered_map<const Node*, std::vector<int>>* input_nodes)
    TF_EXCLUSIVE_LOCKS_REQUIRED(fn_body->mu) {
  input_tensors->reserve(ninputs);
  for (int i = 0; i < ninputs; ++i) {
    Node* node = inputs[i].oper ? &inputs[i].oper->node : nullptr;
    int idx = inputs[i].index;

  }
  TFE_OpAddAttrs(op_.get(), attributes);
  for (int input_index = 0; input_index < inputs.size(); ++input_index) {
    TFE_OpAddInput(op_.get(), inputs[input_index], status);
    if (TF_GetCode(status) != TF_OK) return;
  }
  std::vector<TFE_TensorHandle*> unwrapped_results(expected_max_outputs);
  int real_num_outputs = expected_max_outputs;

  // by the underlying tensorflow::VariableInfo.
  TF_VariableInfo(int index, const std::string& name, tensorflow::Var* var) {
    var_info = tensorflow::VariableInfo{index, name, var};
  }

  tensorflow::VariableInfo var_info{0, "", nullptr};
};

TF_VariableInfo* TF_CreateVariableInfoFromContext(TF_OpKernelContext* ctx,
                                                  int index,