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A Deep Learning Docker Image (PyTorch and TensorFlow) for arm64 architecture

Home Page: https://hub.docker.com/repository/docker/sonoisa/deep-learning-coding

License: Apache License 2.0

Dockerfile 21.07% Shell 77.14% Makefile 1.79%
arm64 dockerfile pytorch tensorflow m1-mac

arm64-docker-pytorch-tensorflow's People

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arm64-docker-pytorch-tensorflow's Issues

Native GPU on M1 Macs

This is really just a question: does the resulting image access the native GPUs on M1 Macs? In other words, can I use this image to train models on an M1 Mac?

The image does not MPS eanbled 

================================================================================
PyTorch and TensorFlow for AArch64
================================================================================
ubuntu@6c43f6619444:~$ ipython
bash: ipython: command not found
ubuntu@6c43f6619444:~$ python
Python 3.8.10 (default, Jun 22 2022, 20:18:18)
[GCC 9.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import platform
>>> platform.platform()
'Linux-5.15.49-linuxkit-aarch64-with-glibc2.29'
>>> import torch
>>> torch.backends.mps.is_available()
False

How to build image for M2 96GB

I am using M2 OSX 13.2. Python 3.11.1
How can I build docker image that enable MPS + PyTorch

To build on 64GB M1 Max MacBook Pro
Make sure to allocate 48GB of memory and 8 cpu to Docker.
$ ./build.sh --build-type full --jobs 8 --bazel_memory_limit 24576

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