Tensorflow：形状必须相等，但将形状0与其他形状合并则为2和0

Question

我正在尝试使用可可数据集中的转换器生成图像标题。因此，我确实需要以下代码的帮助：

model = CaptionGenerator(word_to_idx, dim_feature=[196, 512], dim_embed=512,
                                   dim_hidden=1024, n_time_step=16, prev2out=True,
                                             ctx2out=True, alpha_c=1.0, selector=True, dropout=True)
print("Done with model")

solver = CaptioningSolver(model, data, val_data, n_epochs=20, batch_size=128, update_rule='adam',
                                      learning_rate=0.001, print_every=1000, save_every=1, image_path='./image/',
                                pretrained_model=None, model_path='model/lstm/', test_model='model/lstm/model-10',
                                 print_bleu=True, log_path='log/')
print("Done with solver")

solver.train()

因此，从solver.py调用solver.train（）之后

class CaptioningSolver(object):
    def __init__(self, model, data, val_data, **kwargs):

    def train(self):
        # train/val dataset
        # Changed this because I keep less features than captions, see prepro
        # n_examples = self.data['captions'].shape[0]
        n_examples = self.data['features'].shape[0]
        n_iters_per_epoch = int(np.ceil(float(n_examples)/self.batch_size))
        features = self.data['features']
        captions = self.data['captions']
        image_idxs = self.data['image_idxs']
        val_features = self.val_data['features']
        n_iters_val = int(np.ceil(float(val_features.shape[0])/self.batch_size))

        # build graphs for training model and sampling captions
        # This scope fixed things!!
        with tf.variable_scope(tf.get_variable_scope()):
            print("HELLOOOOOOOOOOOOOO")
            loss = self.model.build_model() **#ERROR COMES AFTER THIS**
            tf.get_variable_scope().reuse_variables()


            _, _, generated_captions = self.model.build_sampler(max_len=20)
                    ........
                    ........

所以在
print("HELLOOOOOOOOOOOOOO") loss = self.model.build_model() **#ERROR COMES AFTER THIS**之后

我收到以下错误：

    c_op = c_api.TF_FinishOperation(op_desc)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Shapes must be equal rank, but are 2 and 0
    From merging shape 0 with other shapes. for 'encoder/enc_pe/Tile/multiples_1' (op: 'Pack') with input shapes: [196,512], [].```