1 FailedPreconditionError错误现象 在运行tensorflow时出现报错,报错语句如下: FailedPreconditionError (see above for traceback): Attempting to use uninitialized value Variable [[Node: Variable/read = _MklIdentity[T=DT_FLOAT, _kernel="MklOp", _device="/job:local
openCV/OpenCV-android-sdk/samples/tutorial-2-mixedprocessing 工程 - ::): Trying to get library list - ::): OpenCV error: Cannot load info library for OpenCV - ::): Library list: "" - ::): First attempt to load libs - ::): Trying to init OpenCV lib
利用pytorch加载mnist数据集的代码如下 import torchvision import torchvision.transforms as transforms from torch.utils.data import DataLoader train_data = torchvision.datasets.MNIST( root='./mnist/', train=True, # this is training data transform=torchvision.transf
TypeError: TF_SessionRun_wrapper: expected all values in input dict to be ndarray 对于下面的实际代码: import tensorflow as tf import os os.environ[' def myregression(): with tf.variable_scope("data"): x = tf.random_normal([100, 1], mean=1.75, stddev=0.5)
K-Means聚类算法 def randCent(dataSet, k): m, n = dataSet.shape # numpy中的shape函数的返回一个矩阵的规模,即是几行几列 centrodids = np.zeros(k, n) for i in range(k): index = int(np.random.uniform(0, m)) # centrodids[i, :] = dataSet[index, :] return centrodids 报错TypeError: dat
错误1: 训练正常开始后,能正常看到日志输出,但中途报错 ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1435,9,256] ..................... ResourceExhaustedError (see above for traceback): OOM when allocating tensor with shape[1435,9,256