code: def _rnn_getter(sess):
      def _get(scope, attr):
          if not attr.bidirectional:
              raise NotImplementedError()
          fw_M, fw_b, bw_M, bw_b = _rnn_trainable_in_scope(scope)
          fw_W, fw_H = np.split(
              _trainable_getter(sess)(fw_M), [attr.input_dim]
          )
          fw_b = _adjust_forget_bias(
              _trainable_getter(sess)(fw_b),
              attr.hidden_dim,
              attr.forget_bias,
          )
          bw_W, bw_H = np.split(
              _trainable_getter(sess)(bw_M), [attr.input_dim]
          )
          bw_b = _adjust_forget_bias(
              _trainable_getter(sess)(bw_b),
              attr.hidden_dim,
              attr.forget_bias,
          )
          return cstk.RnnArgs(
              fw_W=fw_W,
              fw_H=fw_H,
              fw_b=fw_b,
              bw_W=bw_W,
              bw_H=bw_H,
              bw_b=bw_b,
          )
  
      return _get
  
imports: import tensorflow
  import numpy
  from cntk.contrib import crosstalk
label_desc: Use image node_id 11 for calling a global function with example usage: _rnn_getter(sess) and returns: _get, cstk