if (!ValidateInputWhileParams(*params, status)) return;

  TF_Graph* parent = params->cond_graph->parent;
  TF_Output* parent_inputs = params->cond_graph->parent_inputs;
  int num_loop_vars = params->ninputs;

  mutex_lock l(parent->mu);

  // 'cond_fn' copies the cond graph into the parent graph.
  tensorflow::ops::CondGraphBuilderFn cond_fn =

        `tf.quantization.fake_quant_with_min_max_args_gradient`,
        `tf.quantization.fake_quant_with_min_max_vars`,
        `tf.quantization.fake_quant_with_min_max_vars_gradient`,
        `tf.quantization.fake_quant_with_min_max_vars_per_channel`,
        `tf.quantization.fake_quant_with_min_max_vars_per_channel_gradient`.
    *   New endpoints in tf.strings namespace: `tf.strings.join` (corresponds to

        map sigbuild-r2.12-python3.9 2.12-python3.9
        map sigbuild-r2.12-python3.10 2.12-python3.10
        map sigbuild-r2.12-python3.11 2.12-python3.11
        # TF 2.12 + Clang (containers are the same, but env vars in configs.bzl are different)
        map sigbuild-r2.12-clang 2.12-python3.9
        map sigbuild-r2.12-clang-python3.8 2.12-python3.8
        map sigbuild-r2.12-clang-python3.9 2.12-python3.9

  environ_cp['TF_CUDA_COMPUTE_CAPABILITIES'] = tf_cuda_compute_capabilities
  write_action_env_to_bazelrc(
      'TF_CUDA_COMPUTE_CAPABILITIES', tf_cuda_compute_capabilities
  )


def set_other_cuda_vars(environ_cp):
  """Set other CUDA related variables."""
  # If CUDA is enabled, always use GPU during build and test.
  if environ_cp.get('TF_CUDA_CLANG') == '1':
    write_to_bazelrc('build --config=cuda_clang')