错误：
TypeError: unsupported operand type(s) for /: 'Dimension' and 'int', please use // instead
问题：
使用tf.py_function()调用numpy函数时，执行出错。numpy函数出错代码如下：
def cal(boxes):
N = boxes.shape[0]
N1 = np.arange(N)
导致错误的代码是np.arange(N)。出错的原因是N的类型在tf中不是int，而是<class ‘tensorflow.python.framework.tensor_shape.Dimension’>
解决方案：
N = boxes.shape[0].value
# or
N = int(boxes.shape[0])
参考：
This line
self._num_examples = data.shape[0]
returns an int if data is a numpy array:
np_data = np.random.randn(10,10)
np_ans = np_data.shape[0]
print(type(np_ans))
>>> <class 'int'>
but if data is a tf.Variable :
tf_data = tf.Variable(np.random.randn(10,10), dtype=tf.float32)
tf_ans = tf_data.shape[0]
print(type(tf_ans))
>>> <class 'tensorflow.python.framework.tensor_shape.Dimension'>
an instance of tensor_shape.Dimension is returned which can then not be used by np.arrange() here:
---> 59 idx = np.arange(0, self._num_examples)
because np.arrange() requires int arguments.
As a quick fix, try swapping
self._num_examples = data.shape[0]
to
self._num_examples = data.shape[0].value
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