Method __init__

tensorflow/python/ops/rnn_cell_impl.py:833–933

Initialize the parameters for an LSTM cell. Args: num_units: int, The number of units in the LSTM cell. use_peepholes: bool, set True to enable diagonal/peephole connections. cell_clip: (optional) A float value, if provided the cell state is clipped by this value prior

(self,
               num_units,
               use_peepholes=False,
               cell_clip=None,
               initializer=None,
               num_proj=None,
               proj_clip=None,
               num_unit_shards=None,
               num_proj_shards=None,
               forget_bias=1.0,
               state_is_tuple=True,
               activation=None,
               reuse=None,
               name=None,
               dtype=None,
               **kwargs)

  @deprecated(None, "This class is equivalent as tf.keras.layers.LSTMCell,"
              " and will be replaced by that in Tensorflow 2.0.")
  def __init__(self,
               num_units,
               use_peepholes=False,
               cell_clip=None,
               initializer=None,
               num_proj=None,
               proj_clip=None,
               num_unit_shards=None,
               num_proj_shards=None,
               forget_bias=1.0,
               state_is_tuple=True,
               activation=None,
               reuse=None,
               name=None,
               dtype=None,
               **kwargs):
    """Initialize the parameters for an LSTM cell.

    Args:
      num_units: int, The number of units in the LSTM cell.
      use_peepholes: bool, set True to enable diagonal/peephole connections.
      cell_clip: (optional) A float value, if provided the cell state is clipped
        by this value prior to the cell output activation.
      initializer: (optional) The initializer to use for the weight and
        projection matrices.
      num_proj: (optional) int, The output dimensionality for the projection
        matrices.  If None, no projection is performed.
      proj_clip: (optional) A float value.  If `num_proj > 0` and `proj_clip` is
        provided, then the projected values are clipped elementwise to within
        `[-proj_clip, proj_clip]`.
      num_unit_shards: Deprecated, will be removed by Jan. 2017. Use a
        variable_scope partitioner instead.
      num_proj_shards: Deprecated, will be removed by Jan. 2017. Use a
        variable_scope partitioner instead.
      forget_bias: Biases of the forget gate are initialized by default to 1 in
        order to reduce the scale of forgetting at the beginning of the
        training. Must set it manually to `0.0` when restoring from CudnnLSTM
        trained checkpoints.
      state_is_tuple: If True, accepted and returned states are 2-tuples of the
        `c_state` and `m_state`.  If False, they are concatenated along the
        column axis.  This latter behavior will soon be deprecated.
      activation: Activation function of the inner states.  Default: `tanh`. It
        could also be string that is within Keras activation function names.
      reuse: (optional) Python boolean describing whether to reuse variables in
        an existing scope.  If not `True`, and the existing scope already has
        the given variables, an error is raised.
      name: String, the name of the layer. Layers with the same name will share
        weights, but to avoid mistakes we require reuse=True in such cases.
      dtype: Default dtype of the layer (default of `None` means use the type of
        the first input). Required when `build` is called before `call`.
      **kwargs: Dict, keyword named properties for common layer attributes, like
        `trainable` etc when constructing the cell from configs of get_config().
        When restoring from CudnnLSTM-trained checkpoints, use
        `CudnnCompatibleLSTMCell` instead.
    """
    super(LSTMCell, self).__init__(
        _reuse=reuse, name=name, dtype=dtype, **kwargs)
    _check_supported_dtypes(self.dtype)