class_docstr: Basic LSTM recurrent network cell.
  
  The implementation is based on: http://arxiv.org/abs/1409.2329.
  
  We add `forget_bias` (default: 1) to the biases of the forget gate in order to
  reduce the scale of forgetting in the beginning of the training.
  
  Unlike `rnn_cell.LSTMCell`, this is a monolithic op and should be much
  faster.  The weight and bias matrices should be compatible as long as the
  variable scope matches.
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code: def output_size(self):
      return self._num_units
  
imports: import tensorflow.compat.v1
  import tf_slim
  from tensorflow.python.ops import gen_nn_ops
label_desc: Use image node_id 3 for calling the LSTMBlockCell obj's underlying member method code with example usage: obj.output_size() and returns: self