Run twice occurred gpu error on Google Colaboratory - tensorflow

Question

I want to test the FIFIQueue, when I use "with tf.device("/device:GPU:0"):", the first time I run, it's just ok, but when I run it twice, error occurred just print cannot assign gpu to fifo_queue_EnqueueMany(the error detail is in the image below), anyone warm-hearted to help me？
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Answer 1

Per drpng's note on Tensorflow: using a FIFO queue for code running on GPUs I wouldn't expect FIFOQueue to schedule on a GPU, and indeed wrapping your code in a .py file (to see TF's logging output) and logging device placement confirms that even the first (successful) invocation schedules on a CPU.
In one cell run:
%%writefile go.py
import tensorflow as tf
config = tf.ConfigProto()
#config.allow_soft_placement=True
config.gpu_options.allow_growth = True
config.log_device_placement=True
def go():
Q = tf.FIFOQueue(3, tf.float16)
enq_many = Q.enqueue_many([[0.1, 0.2, 0.3],])
with tf.device('/device:GPU:0'):
with tf.Session(config=config) as sess:
sess.run(enq_many)
print(Q.size().eval())
go()
go()
And in another cell execute the above as:
!python3 go.py
and observe placement.
Uncomment the allow_soft_placement assignment to make the crash go away.
(I do not know why the first execution succeeds even in the face of non-soft-placement when asking FIFOQueue to schedule on the GPU explicitly as in your code's "first time")