def _dropout_from_layer(rng, layer, p):
    srng = theano.tensor.shared_randomstreams.RandomStreams(rng.randint(999999))
    # p=1-p because 1's indicate keep and p is prob of dropping
    mask = srng.binomial(n=1, p=1-p, size=layer.shape)
    # The cast is important because
    # int * float32 = float64 which pulls things off the gpu
    output = layer * T.cast(mask, theano.config.floatX)
    return output
Return the size (in bytes) that the bytecode for this takes up
dataset/ETHPy150Open flipkart-incubator/optimus/cnn_text_trainer/core/nn_classes.py/_dropout_from_layer--crossover with--dataset/ETHPy150Open googlei18n/compreffor/compreffor/pyCompressor.py/CandidateSubr.cost