我正在尝试加载每个不同大小的批量图像（具体来说，它们来自pascal voc数据集） . source_images.npy文件包含不同高度，宽度但相同通道的图像 . 我做错了什么？是否有其他方法可以发送不同大小的图像？
这是我的代码：
def feed(images, im, epochs=None):
epochs_elapsed = 0
while epochs is None or epochs_elapsed < epochs:
for i in range(len(images)):
yield {im: images[i]}
epochs_elapsed += 1
def tf_ops(images, capacity=200):
im = tf.placeholder(tf.float32)
queue = tf.FIFOQueue(capacity, [tf.float32])
enqueue_op = queue.enqueue(im)
fqr = FeedingQueueRunner(queue, [enqueue_op],
feed_fns=[feed(images,im).next()])
tf.train.add_queue_runner(fqr)
return queue.dequeue()
source_images = np.load('source_images.npy')
source_images=source_images.tolist()
source_im= tf_ops(source_images)
source_im_batch = tf.train.batch([source_im],batch_size=128,capacity=200, dynamic_pad=True)
错误：
source_im_batch = tf.train.batch([source_im], batch_size=128,capacity=200, dynamic_pad=True)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 872, in batch
name=name)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 655, in _batch
shapes = _shapes([tensor_list], shapes, enqueue_many)
File "/home/anaconda2/lib/python2.7/site-packages/tensorflow/python/training/input.py", line 598, in _shapes
raise ValueError("Cannot infer Tensor's rank: %s" % tl[i])
ValueError: Cannot infer Tensor's rank: Tensor("fifo_queue_Dequeue:0", dtype=float32)