keras 自适应分配显存 & 清理不用的变量释放 GPU 显存 Intro Are you running out of GPU memory when using keras or tensorflow deep learning models, but only some of the time? Are you curious about exactly how much GPU memory your tensorflow model uses during training? Are
错误一:二分类,标签y ValueError: Cannot feed value of shape (128,1) for Tensor u'input_y_2:0', which has shape '(?, 2)' 我的输入y_train维度为(128,1),即是一个向量,batch_size为128. 在tensorflow中你在做数据喂养的时候你输入的是一个一维数组如:[0,1,0],他的shape 为(3,) 在tensorflow中一维数组是不能与同样的一维数组进行运算的,必须通过
问题描述 程序开始运行的时候报出警告:I tensorflow/core/platform/cpu_feature_guard.cc:141] Your CPU supports instructions that this TensorFlow binary was not compiled to use: AVX2 FMA 解决方法 加入下面两行代码,忽略警告: import os os.environ[' 说明: os.environ[' # 这是默认的显示等级,显示所有信息 os.env
Keras 2.2.4版本和 tensorflow1.2.1 版本不兼容导致的错误.降低Keras 为2.1.2版本 import keras 出现: Using TensorFlow backend. Kernel died, restarting conda uninstall keras conda
Visual Studio提示Bonjour backend初始化失败 错误信息:The Bonjour backend failed to initialize, automatic Mac Build server discovery will not be available.这是由于Windows下的Bonjour服务没有开启,需要到服务管理中,开启该服务,即可.
C:\....\Anaconda3\envs\py35\lib\site-packages\h5py\__init__.py:36: FutureWarning: Conversion of the second argument of issubdtype from `float` to `np.floating` is deprecated. In future, it will be treated as `np.float64 == np.dtype(float).type`. from