What's the difference between the print inside and outside

Question

I am learning the tensorflow which version is 2.8.0 on my MacBook M1. For debugging the code in the map function of dataset, I want to print tensor value in my function.

def function(i):
    print("in: ", i)
    if i < 2:
        i = i - 1
    return i


dataset = tf.data.Dataset.range(1, 6)
dataset = dataset.map(lambda x: tf.py_function(function, inp=[x], Tout=tf.int64))
for x in dataset:
    print("out:", x)

I got the output as blew:

in:  tf.Tensor(1, shape=(), dtype=int64)
out: tf.Tensor(0, shape=(), dtype=int64)
in:  tf.Tensor(2, shape=(), dtype=int64)
out: tf.Tensor(2, shape=(), dtype=int64)
in:  tf.Tensor(3, shape=(), dtype=int64)
out: tf.Tensor(3, shape=(), dtype=int64)
in:  tf.Tensor(4, shape=(), dtype=int64)
out: tf.Tensor(4, shape=(), dtype=int64)
in:  tf.Tensor(5, shape=(), dtype=int64)
out: tf.Tensor(5, shape=(), dtype=int64)

After I delete the print outside, I did not get any output. What's the difference between the print inside and the print outside. I don't understand why it can only take effect when the prints appear at the same time. Beside that, what the difference between print and tf.print?