报错如下：
otFoundError: 2 root error(s) found. (0) Not found: Resource localhost/total/N10tensorflow3VarE does not exist. [[{
{
node metrics/accuracy/AssignAddVariableOp}}]] [[metrics/precision/Mean/_87]] (1) Not found: Resource localhost/total/N10tensorflow3VarE does not exist. [[{
{
node metrics/accuracy/AssignAddVariableOp}}]] 0 successful operations. 0 derived errors ignored. 解决方案：
主要原因是GPU被占用导致内存不足，使用nvitop -m查看被占用的程序PID，sudo kill 对应PID,可能还是不需要用。part2部分
## part 1 能从TensorFlow导入keras及其子库，从里面进口 from tensorflow.keras.layers import Conv2D, Flatten, Dense, MaxPool2D, Dropout, BatchNormalization from keras.utils.np_utils import to_categorical from tensorflow.keras.preprocessing.image import ImageDataGenerator from tensorflow.keras.callbacks import LearningRateScheduler import tensorflow.compat.v1 as tf from sklearn.model_selection import train_test_split ## part 2 os.environ["CUDA_VISIBLE_DEVICES"] = "0" config = tf.ConfigProto() config.gpu_options.per_process_gpu_memory_fraction = 0.85 # 最多只能占用指定的程序gpu75%的显存 config.gpu_options
.allow_growth
=True #不全部占满显存
, 按需分配 sess
= tf
.
Session
(config
=config
)