class_docstr: Layer-Norm, with Ortho Init. and Recurrent Dropout without Memory Loss.
  
  https://arxiv.org/abs/1607.06450 - Layer Norm
  https://arxiv.org/abs/1603.05118 - Recurrent Dropout without Memory Loss
class_docstr_tok: ["Layer-Norm",",","with","Ortho","Init",".","and","Recurrent","Dropout","without","Memory","Loss",".","https",":","\/\/arxiv.org\/abs\/1607.06450","-","Layer","Norm","https",":","\/\/arxiv.org\/abs\/1603.05118","-","Recurrent","Dropout","without","Memory","Loss"]
docstr: Initialize the Layer Norm LSTM cell.
  
  Args:
    num_units: int, The number of units in the LSTM cell.
    forget_bias: float, The bias added to forget gates (default 1.0).
    use_recurrent_dropout: Whether to use Recurrent Dropout (default False)
    dropout_keep_prob: float, dropout keep probability (default 0.90)
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code: def __init__(
      self,
      num_units,
      forget_bias=1.0,
      use_recurrent_dropout=False,
      dropout_keep_prob=0.90,
  ):
      """Initialize the Layer Norm LSTM cell.
  
      Args:
        num_units: int, The number of units in the LSTM cell.
        forget_bias: float, The bias added to forget gates (default 1.0).
        use_recurrent_dropout: Whether to use Recurrent Dropout (default False)
        dropout_keep_prob: float, dropout keep probability (default 0.90)
      """
      self.num_units = num_units
      self.forget_bias = forget_bias
      self.use_recurrent_dropout = use_recurrent_dropout
      self.dropout_keep_prob = dropout_keep_prob
  
imports: import numpy
  import tensorflow.compat.v1
label_desc: Use image node_id 1 to create a new LayerNormLSTMCell object from inherited base classes: tf.nn.rnn_cell with example: obj = LayerNormLSTMCell(num_units, forget_bias, use_recurrent_dropout, dropout_keep_prob)