def inference(x, seq_length, training):
cnn_feature = getcnnfeature(x, training=training)
feashape = cnn_feature.get_shape().as_list()
ratio = FLAGS.segment_len / feashape[1]
logits = rnn_layers(cnn_feature, seq_length / ratio, training, class_n=5)
# logits = rnn_layers_one_direction(cnn_feature,seq_length/ratio,training,class_n = 4**FLAGS.k_mer+1 )
# logits = getcnnlogit(cnn_feature)
return logits, ratio
def inference(x, seq_length, training):
cnn_feature = getcnnfeature(x, training=training)
logits = rnn_layers(cnn_feature, seq_length, training)
return logits
