[问题记录]TensorFlow测试mnist失败

来源：互联网发布：结婚照视频制作软件编辑：程序博客网时间：2024/06/05 23:49

前两篇TensorFlow测试mnist示例文章上传后，csdn吞了我的图，再次测试时，出现了以下问题

[test@dl1 mnist]$ python mnist_test_begin.pyI tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcublas.so.8.0 locallyI tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcudnn.so.5 locallyI tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcufft.so.8.0 locallyI tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcuda.so.1 locallyI tensorflow/stream_executor/dso_loader.cc:135] successfully opened CUDA library libcurand.so.8.0 locallyfilepath:MNIST_data/train-images-idx3-ubyte.gzExtracting MNIST_data/train-images-idx3-ubyte.gzfilepath:MNIST_data/train-labels-idx1-ubyte.gzExtracting MNIST_data/train-labels-idx1-ubyte.gzfilepath:MNIST_data/t10k-images-idx3-ubyte.gzExtracting MNIST_data/t10k-images-idx3-ubyte.gzfilepath:MNIST_data/t10k-labels-idx1-ubyte.gzExtracting MNIST_data/t10k-labels-idx1-ubyte.gzWARNING:tensorflow:From mnist_test_begin.py:23: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be removed after 2017-03-02.Instructions for updating:Use `tf.global_variables_initializer` instead.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.

测试后，是在启动回话时卡住了

sess = tf.Session()

目前还不知道怎么解决。。。

-------------------------------------------------------------------------------------------------------

三个小时之后再运行就可以了，WTF?

0 2