lasagne.random¶
A module with a package-wide random number generator, used for weight initialization and seeding noise layers. This can be replaced by a numpy.random.RandomState instance with a particular seed to facilitate reproducibility.
Note: When using cuDNN, the backward passes of convolutional and max-pooling layers will introduce additional nondeterminism (for performance reasons). For 2D convolutions, you can enforce a deterministic backward pass implementation via the Theano flags dnn.conv.algo_bwd_filter=deterministic and dnn.conv.algo_bwd_data=deterministic. Alternatively, you can disable cuDNN completely with dnn.enabled=False.