tf.contrib.rnn.TimeFreqLSTMCell.__init__()

tf.contrib.rnn.TimeFreqLSTMCell.__init__(num_units, use_peepholes=False, cell_clip=None, initializer=None, num_unit_shards=1, forget_bias=1.0, feature_size=None, frequency_skip=None)

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_unit_shards: int, How to split the weight matrix. If >1, the weight matrix is stored across num_unit_shards.
• forget_bias: float, 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.
• feature_size: int, The size of the input feature the LSTM spans over.
• frequency_skip: int, The amount the LSTM filter is shifted by in frequency.