-
Notifications
You must be signed in to change notification settings - Fork 39
New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
Issue of tensorflow installation #62
Comments
May be insufficient memory space (tensorflow/models#3647 )... Also you should read this log file where the error is probably well explained. |
Thank you for your quick reply... The installation via bazel: bazel build -c opt --copt=-mavx --copt=-mavx2 --copt=-mfma --copt=-mfpmath=both --copt=-msse4.1 --copt=-msse4.2 //tensorflow:libtensorflow_framework.so //tensorflow:libtensorflow_cc.so //tensorflow:libtensorflow.so //tensorflow/tools/pip_package:build_pip_package --noincompatible_do_not_split_linking_cmdline And the condition of installation: Server terminated abruptly (error code: 14, error message: 'Socket closed', log file: '/home/yla18/.cache/bazel/_bazel_yla18/d4ef3948567f7f7d65fbd5757d6da7fb/server/jvm.out') |
I installed it in the virtual system but it has its own cpu, so I guess this should be no problem... |
Looking at the bazel output, you're building with 8 cores. So you probably need more RAM, or less cores. But to be sure, you should read this file "'/home/yla18/.cache/bazel/_bazel_yla18/d4ef3948567f7f7d65fbd5757d6da7fb/server/jvm.out". Also you could watch your memory usage just after typing the build command. Which TF version are you building ? |
|
You should avoid building from the TF master branch. Just checkout a release Also you can add the |
Thank you for your support and I will check it... |
I am sorry because I used the virtual machine, so the question is that I may not have CUDA. Is it possible for me to install? The error I encountered just now is: Thank you for your help and I am looking forward to your reply! |
Yes you can use TF without GPU / CUDA. Bazel is kind of messy, it could be some dependency version mismatch or something else related to your env / VM. Make sure to check your python deps, including numpy<1.20, and check your environment variable, you can look at this file for some reference : https://github.com/remicres/otbtf/blob/develop/tools/docker/build-env-tf.sh I'm not sure, but it is most likely an Out Of Memory error and this would explain you can't see any log file. Thus you'd better pull a Docker image if possible... |
Which bazel version are you running ? If you really want to build the latest tensorflow release, check the Dockerfile for a more up-to-date installation script example (Ubuntu 18.04 or 20.04). |
Thank you for your quick reply. I used the bazel 3.7.2. |
In that case you should checkout v2.5.0. |
Thank you for your help! |
Check this file : |
Thank you for your quick reply! This is the PatchesExtraction application, version 7.2.0 This application extracts patches in multiple input images. Change the OTB_TF_NSOURCES environment variable to set the number of sources. The application takes an input vector layer which is a set of points, typically the output of the "SampleSelection" or the "LabelImageSampleSelection" application to sample patches in the input images (samples are centered on the points). A "source" parameters group is composed of (i) an input image list (can be one image e.g. high res. image, or multiple e.g. time series), (ii) the size of the patches to sample, and (iii) the output images of patches which will be generated at the end of the process. The example below show how to set the samples sizes. For a SPOT6 image for instance, the patch size can be 64x64 and for an input Sentinel-2 time series the patch size could be 1x1. Note that if a dimension size is not defined, the largest one will be used (i.e. input image dimensions. The number of input sources can be changed at runtime by setting the system environment variable OTB_TF_NSOURCES Parameters: Use -help param1 [... paramN] to see detailed documentation of those parameters. Examples: Authors: Limitations: See also: |
So everything is working OK.You need to learn how to use Docker, they provide a great documentation ! |
Hi:
When I install the tensorflow with bazel, the problem is:
Server terminated abruptly (error code: 14, error message: 'Socket closed', log file: '/home/yla18/.cache/bazel/_bazel_yla18/d4ef3948567f7f7d65fbd5757d6da7fb/server/jvm.out')
Anyone has the solution for this issue?
Thx!
The text was updated successfully, but these errors were encountered: