prediction_model_stochastic_search.py 文件源码

def make_cdna_kerns_summary(cdna_kerns, t, suffix):

    sum = []
    cdna_kerns = tf.split(4, 10, cdna_kerns)
    for i, kern in enumerate(cdna_kerns):
        kern = tf.squeeze(kern)
        kern = tf.expand_dims(kern,-1)
        sum.append(
            tf.image_summary('step' + str(t) +'_filter'+ str(i)+ suffix, kern)
        )

    return  sum