docstr: Initializes an LSTM cell.
  
  Args:
      batch_size (int): Internal batch size is set to `batch_size`.
      state_size (int): Internal state size is set to `state_size`.
      h (~nnabla.Variable): Input N-D array with shape (batch_size, state_size). If not specified, it is initialized to zero by default.
      c (~nnabla.Variable): Input N-D array with shape (batch_size, state_size). If not specified, it is initialized to zero by default.
      name (str): Name for this LSTM Cell.
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code: def __init__(self, batch_size, state_size, h=None, c=None, name=None):
      """
      Initializes an LSTM cell.
  
      Args:
          batch_size (int): Internal batch size is set to `batch_size`.
          state_size (int): Internal state size is set to `state_size`.
          h (~nnabla.Variable): Input N-D array with shape (batch_size, state_size). If not specified, it is initialized to zero by default.
          c (~nnabla.Variable): Input N-D array with shape (batch_size, state_size). If not specified, it is initialized to zero by default.
          name (str): Name for this LSTM Cell.
      """
      self.batch_size = batch_size
      self.state_size = state_size
      self.name = name
      if h:  # when user defines h
          self.h = h
      else:
          self.h = nn.Variable((self.batch_size, self.state_size))
          self.h.data.zero()
      if c:  # when user defines c
          self.c = c
      else:
          self.c = nn.Variable((self.batch_size, self.state_size))
          self.c.data.zero()
  
imports: from six import exec_
  import numpy
  import nnabla
  import nnabla.functions
  from nnabla.parameter import get_parameter_or_create, get_parameter
  from nnabla.initializer import calc_uniform_lim_glorot, ConstantInitializer, NormalInitializer, UniformInitializer, WeightNormalizationScaleInitializer
label_desc: Use image node_id 1 to create a new LSTMCell object  with example: obj = LSTMCell(batch_size, state_size, h, c, name)