code: def lstm_cell(
      inputs,
      state,
      num_units,
      use_peepholes=False,
      cell_clip=0.0,
      initializer=None,
      num_proj=None,
      num_unit_shards=None,
      num_proj_shards=None,
      reuse=None,
      name=None,
  ):
      """Full LSTM cell."""
      input_shape = common_layers.shape_list(inputs)
      cell = tf.nn.rnn_cell.LSTMCell(
          num_units,
          use_peepholes=use_peepholes,
          cell_clip=cell_clip,
          initializer=initializer,
          num_proj=num_proj,
          num_unit_shards=num_unit_shards,
          num_proj_shards=num_proj_shards,
          reuse=reuse,
          name=name,
          state_is_tuple=False,
      )
      if state is None:
          state = cell.zero_state(input_shape[0], tf.float32)
      outputs, new_state = cell(inputs, state)
      return outputs, new_state
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import numpy
  from tensor2tensor.layers import common_layers
  from tensor2tensor.utils import contrib
  import tensorflow.compat.v1
  from tensorflow.python.ops import summary_op_util
label_desc: Use image node_id 5 for calling a global function with example usage: lstm_cell(inputs, state, num_units, use_peepholes, cell_clip, initializer, num_proj, num_unit_shards, num_proj_shards, reuse, name) and returns: outputs,  new_state