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One module without kernel function - then core dump #248
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Hi @metal3d |
And if you are, we can no longer support Beignet - development has ceased on it, though you might be interested in the Intel Neo driver: https://github.com/intel/compute-runtime |
Even fglrx development ceased, and yet /s |
I get your point, but Beignet was particularly broken, and won't be getting fixes (as I understand it). |
Sorry for the late answer. I have Beignet drivers and I wanted to try Intel driver but my card is not 4th gen (only 3th gen). I really don't know how I can change it. Anyway, even POCL seems to crash the same way. Here is my clinfo output:
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I forget to say that in my container, mounting /dev/dri correctly, I get this clinfo:
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And removed Beignet from docker:
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It is easier for us to identify what's going wrong if you try running the SDK samples over at codeplaysoftware/computecpp-sdk . They are more simple than the whole of tensorflow and some of the samples have extended debugging output (if you run ctest -V, you'll get more verbose output from the samples). Thanks! |
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 18:01 (Docker)
TensorFlow installed from (source or binary):
From source
Python version:
3.6
Bazel version (if compiling from source):
0.8.0 (if I'm not wrong, that's the latest)
GCC/Compiler version (if compiling from source):
clang
GPU model and memory:
Intel(R) HD Graphics Haswell GT2 Mobile
python3 -c "import tensorflow as tf; print(tf.GIT_VERSION, tf.VERSION)"
ComputeCpp-v0.6.0-4145-g5fc11c4859 1.8.0-rc1
Describe the problem
Core dump and "One module without kernel" error.
I'm pretty sure that my card is not supported, but in case of a miracle can happend... ;)
Source code / logs
Using models repository from tensorflow:
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