tf.contrib.rnn.TimeFreqLSTMCell.__call__()

tf.contrib.rnn.TimeFreqLSTMCell.__call__(inputs, state, scope=None)

Run one step of LSTM.

Args:

• inputs: input Tensor, 2D, batch x num_units.
• state: state Tensor, 2D, batch x state_size.
• scope: VariableScope for the created subgraph; defaults to "TimeFreqLSTMCell".

Returns:

A tuple containing: - A 2D, batch x output_dim, Tensor representing the output of the LSTM after reading "inputs" when previous state was "state". Here output_dim is num_units. - A 2D, batch x state_size, Tensor representing the new state of LSTM after reading "inputs" when previous state was "state".

Raises:

• ValueError: if an input_size was specified and the provided inputs have a different dimension.