View source on GitHub

Helper class that converts between params of Cudnn and TF GRU.

num_layers the number of layers for the RNN model.
num_units the number of units within the RNN model.
input_size the size of the input, it could be different from the num_units.
num_proj The output dimensionality for the projection matrices. If None or 0, no projection is performed.
input_mode indicate whether there is a linear projection between the input and the actual computation before the first layer. It could be one of 'linear_input', 'skip_input' or 'auto_select'. * 'linear_input' (default) always applies a linear projection of input onto RNN hidden state. (standard RNN behavior). * 'skip_input' is only allowed when input_size == num_units; * 'auto_select' implies 'skip_input' when input_size == num_units; otherwise, it implies 'linear_input'.
direction the direction model that the model operates. Could be either 'unidirectional' or 'bidirectional'



View source

Converts cudnn opaque param to tf canonical weights.


View source

Converts tf canonical weights to cudnn opaque param.