utils.py 文件源码

def sample_weights(sizeX, sizeY, sparsity, scale, rng):
    """
    Initialization that fixes the largest singular value.
    """
    sizeX = int(sizeX)
    sizeY = int(sizeY)
    sparsity = numpy.minimum(sizeY, sparsity)
    values = numpy.zeros((sizeX, sizeY), dtype=theano.config.floatX)
    for dx in xrange(sizeX):
        perm = rng.permutation(sizeY)
        new_vals = rng.uniform(low=-scale, high=scale, size=(sparsity,))
        vals_norm = numpy.sqrt((new_vals**2).sum())
        new_vals = scale*new_vals/vals_norm
        values[dx, perm[:sparsity]] = new_vals
    _,v,_ = numpy.linalg.svd(values)
    values = scale * values/v[0]
    return values.astype(theano.config.floatX)