在用jupyter notebook运行程序时出现如下bug：
ResourceExhaustedError: OOM when allocating tensor with shape[4096,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc
[[Node: random_normal_1/RandomStandardNormal = RandomStandardNormal[T=DT_INT32, dtype=DT_FLOAT, seed=0, seed2=0, _device="/job:localhost/replica:0/task:0/device:GPU:0"](random_normal_1/shape)]]
Hint: If you want to see a list of allocated tensors when OOM happens, add report_tensor_allocations_upon_oom to RunOptions for current allocation info.
原因：Jupyter notebook 每次运行完tensorflow的程序，占着显存不释放。
解决方式：在程序开头加上如下程序
import os
import tensorflow as tf
os.environ["CUDA_VISIBLE_DEVICES"] = '0' #指定第一块GPU可用
config = tf.ConfigProto()
config.gpu_options.per_process_gpu_memory_fraction = 0.5 # 程序最多只能占用指定gpu50%的显存
config.gpu_options.allow_growth = True #程序按需申请内存
sess = tf.Session(config = config)