tensorflow: Prebuilt binaries do not work with CPUs that do not have AVX instruction sets.
As announced in release notes, TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets. This means on any CPU that do not have these instruction sets either CPU or GPU version of TF will fail to load with any of the following errors:
ImportError: DLL load failed:- A crash with return code 132
Our recommendation is to build TF from sources on these systems.
System information
- Have I written custom code (as opposed to using a stock example script provided in TensorFlow): No
- OS Platform and Distribution (e.g., Linux Ubuntu 16.04): ubuntu/windows/macos
- TensorFlow installed from (source or binary): binary
- TensorFlow version (use command below): 1.6 and up
- Python version: 2.7, 3.3, 3.4, 3.5, 3.6 and any newer
- Bazel version (if compiling from source): n/a
- GCC/Compiler version (if compiling from source): n/a
- CUDA/cuDNN version: any
- GPU model and memory: any
- Exact command to reproduce: python -c “import tensorflow as tf”
About this issue
- Original URL
- State: open
- Created 6 years ago
- Reactions: 37
- Comments: 29 (11 by maintainers)
We encourage the community to build and share binaries for older CPU models.
We have no plans to build and release non-AVX binaries at the moment.
I have the same issue. Tried to build binary with bazel but failed. Try this “pip install tensorflow==1.5”. It works for me.
FYI, here is a Docker image that can build TensorFlow https://github.com/hadim/docker-tensorflow-builder. It can help to compile TF on a wide range of configurations as long as you have Docker installed on it.
I’ve built tf 1.13 for CPU without any fancy instructions here:
Python 2.7: https://github.com/yaroslavvb/tensorflow-community-wheels/issues/97 Python 3.6: https://github.com/yaroslavvb/tensorflow-community-wheels/issues/103
Hope it helps someone
Well, why just you do not build a matrix of combinations? AVX -> AVX2 -> GPU -> CPU Only If the builds take too much time, prepare docker images which are ready for building and people will build them themselves.
Check this repo for more unofficial wheels: https://github.com/yaroslavvb/tensorflow-community-wheels/issues I found the right one for our server. YAY!
Any compilation for Linux (no AVX) and Python 3.5 (Ubuntu 16.04)?
Here’s a TensorFlow 1.13.1 binary package for Westmere CPUs (no AVX) and Python 2.7: yaroslavvb/tensorflow-community-wheels#105
Any chance for you to make the build for the community?