utils.py 文件源码

def grad_nan_report(grads, tparams):
    numpy.set_printoptions(precision=3)
    D = OrderedDict()
    i = 0
    NaN_keys = []
    magnitude = []
    assert len(grads) == len(tparams)
    for k, v in tparams.iteritems():
        grad = grads[i]
        magnitude.append(numpy.abs(grad).mean())
        if numpy.isnan(grad.sum()):
            NaN_keys.append(k)
        #assert v.get_value().shape == grad.shape
        D[k] = grad
        i += 1
    #norm = [numpy.sqrt(numpy.sum(grad**2)) for grad in grads]
    #print '\tgrad mean(abs(x))', numpy.array(magnitude)
    return D, NaN_keys