ActivationFunctions.py 文件源码

def applyActivationFunction_PReLU_v3(inputData,PreluActivations) :
    """ inputData is a tensor5D with shape:
     (batchSize,
     Number of feature Maps,
     convolvedImageShape[0],
     convolvedImageShape[1],
     convolvedImageShape[2]) """ 

    # The input is a tensor of shape (batchSize, FeatMaps, xDim, yDim, zDim)
    preluActivationsAsRow = PreluActivations.dimshuffle('x', 0, 'x', 'x', 'x')

    pos = 0.5 * (1 + preluActivationsAsRow )
    neg = 0.5 * (1 - preluActivationsAsRow )
    output = pos * inputData + neg * abs(inputData)

    return ( output)

# Benchmark on ReLU/PReLU activations:
# http://gforge.se/2015/06/benchmarking-relu-and-prelu/

# TODO. Implement some other activation functions:
# Ex: Randomized ReLU
#     S-shape Relu
#     ThresholdedReLU