Closed ianferreira closed 3 years ago
Yes, you need recompile tensorflow with gfx1030, but itis no guanrontee that we can run ROCm on gfx1030 properly.
Good news is ROCm said they will support navi in 2021. So my suggestion is waiting for official support.
I guess gfx1030 will be supported on ROCm-4.3. https://github.com/ROCmSoftwarePlatform/rocBLAS/blob/release/rocm-rel-4.3/CMakeLists.txt#L169
ROCm-4.3 may be released about June or July 2021, I wish.
Indeed. Thanks for this project.
Hi.
I have ROCm 4.3 with gfx1030. I installed tensorflow-rocm and when it imports fine. But when I run to check if it's using GPU, then I get this:
tf.config.list_physical_devices('GPU')
2021-09-11 09:15:31.830208: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libamdhip64.so
"hipErrorNoBinaryForGpu: Unable to find code object for all current devices!"
Aborted (core dumped)
Any suggestions?
Sadly ROCM still doesnt supper Navi. I was also hoping 4.3 would. Some of the libraries did add support.
Which deep learning frameworks can I use then?
@Flock1 The tensorflow cost more time than pytorch. If I have a gfx1030, I will recompile pytorch to test.
Here is some scipts for gfx1030: https://github.com/xuhuisheng/rocm-build/tree/master/navi21
Environment
What is the expected behavior
tensorflow-rocm works after completing the install in this repo
What actually happens
ian@xxxx~/Documents/Src$ /home/ian/.envs/py3tf2/bin/python /home/ian/Documents/Src/test.py 2021-05-27 12:35:24.176982: I tensorflow/compiler/jit/xla_cpu_device.cc:41] Not creating XLA devices, tf_xla_enable_xla_devices not set 2021-05-27 12:35:24.177308: I tensorflow/stream_executor/platform/default/dso_loader.cc:53] Successfully opened dynamic library libamdhip64.so /home/ian/Documents/rocm-build/ROCm/HIP/rocclr/hip_code_object.cpp:486: "hipErrorNoBinaryForGpu: Unable to find code object for all current devices!" Aborted (core dumped)
How to reproduce
pip install tensorflow-rocm ... ... Successfully installed tensorflow-rocm-2.4.3
python
import tensorflow as tf from tensorflow.keras.models import Sequential from tensorflow.keras.layers import Dense, Conv2D, Flatten, Dropout
model = Sequential()