我收到了错误消息:
Python 3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 17:14:51)
[GCC 7.2.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> hello = tf.constant('Hello, TensorFlow!')
>
运行代码
export_path= '/content/gdrive/My Drive'+ '\\model\\'+'20191003053122'
with tf.Session(graph=tf.Graph()) as sess:
tf.saved_model.loader.load(sess, ["myTag"], export_path)
graph = tf.get_default_graph()
产生的错误
ValueError: The passed save_path is no
在GPU中运行tensorflow时,我会得到以下错误。
2018-09-15 18:56:51.011724: E tensorflow/core/common_runtime/direct_session.cc:158] Internal: cudaGetDevice() failed. Status: CUDA driver version is insufficient for CUDA runtime version
Traceback (most recent call last):
File "evaluate_sample.py", line 160, in
这是我得到的错误: Error: A resource with the ID "/subscriptions/subid/resourceGroups/tf-nonprod/providers/Microsoft.Compute/virtualMachines/windows-web1" already exists - to be managed via Terraform this resource needs to be imported into the State. Please see the resource documentation for "az
我是个新手。当我运行test.py时。有一个错误:
2018-05-13 10:00:03.012495: I tensorflow/core/platform/cpu_feature_guard.cc:140] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX AVX2 FMA
2018-05-13 10:00:03.312772: I tensorflow/core/common_runtime/gpu/gpu_device.cc:134
此代码应使用TF-Agents库在Cartpole环境中训练DQN (Deep Q Networks)代理,但该代理似乎没有正确训练。我正在尝试使用Driver模块编写一个最小的示例。
我还可以运行TF-Agents库中的示例。
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import tensorflow as tf
from tf_agents.environments import suite_gym
from
我正在使用jupyter笔记本在谷歌可乐。我的培训数据集看起来如下:
/data/label1/img1.jpeg
.
.
.
/data/label2/img90.jpeg
我想导入这样的数据集。我试过的东西
Step1:
!pip install -U -q PyDrive
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
from os import walk
import os
from pydrive.auth import GoogleAuth
from pydrive.drive import
image_path = tf.keras.utils.get_file('img.jpeg', 'link') #'link' in my code is replaces with a alink to a google drive image
image_raw = tf.io.read_file(image_path)
image = tf.image.decode_image(image_raw) 这段代码是我在网上找到的生成对抗性示例的代码的一部分。在原始代码中,它们将一个链接传递到在线图像的tf.keras
所以它是这样的:我想在AWS - p2.xlarge plan上使用带有图形处理器的TensorFlow。不幸的是,一定是出了什么问题,我继续得到:
InvalidArgumentError (see above for traceback): Cannot assign a device to node 'Variable_1': Could not satisfy explicit device specification '/device:GPU:0' because no devices matching that specification are r
在我安装GTX1080的驱动程序之后,tensorflow显示它可以找到cudnn库。
但是,modprobe无法识别GPU驱动程序。详细信息如下:
$ python
[14:22:14]
Python 2.7.6 (default, Jun 22 2015, 17:58:13)
[GCC 4.8.2] on linux2
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as
我试图在我的电脑上玩蒸汽游戏,运行Ubuntu14.04。在启动“堡垒2”时,我收到了错误Cannot find required OpenGL entry point 'glGetError'! Either your video card is unsupported, or your OpenGL driver need to be updated.
我在没有运气的情况下尝试了sudo rm /usr/lib/i386-linux-gnu/libGL.so和rm .local/share/Steam/ubuntu12_32/steam-runtime/i386/lib/
我使用朱庇特笔记本在我的机器上运行了这段代码,认为它可能无法工作,因为相关目录没有exist...However,结果证明它工作正常。因此,使用/datasets/ud730/mnist的相对目录必须相对于当前的工作目录,即C:\\Users\\george.liu\\OneDrive\\WorkingDir\\Temp。但是,我无法找到任何相关的文件夹或文件。我还检查了C:\\Users\\george.liu,没有什么either...What我遗漏了吗?文件到哪里去了?谢谢!
from tensorflow.examples.tutorials.mnist import input_da