|View source on GitHub|
DEPRECATED: Please use
tf.compat.v1.nn.rnn_cell.BasicLSTMCell( num_units, forget_bias=1.0, state_is_tuple=True, activation=None, reuse=None, name=None, dtype=None, **kwargs )
Basic LSTM recurrent network cell.
The implementation is based on
We add forget_bias (default: 1) to the biases of the forget gate in order to reduce the scale of forgetting in the beginning of the training.
It does not allow cell clipping, a projection layer, and does not use peep-hole connections: it is the basic baseline.
For advanced models, please use the full
Note that this cell is not optimized for performance. Please use
tf.contrib.cudnn_rnn.CudnnLSTM for better performance on GPU, or
better performance on CPU.
||int, The number of units in the LSTM cell.|
float, The bias added to forget gates (see above). Must set
||If True, accepted and returned|