I'm trying to run some projects using the new Mac M1. Those projects already work on Intel processor and are used by other developers that use Intel.
I am not able to build this simple Dockerfile:
FROM python:3.9
RUN python -m pip install --upgrade pip
RUN pip install tensorflow==2.6.2
I get this message:
> [3/3] RUN pip install tensorflow==2.6.2:
#6 0.583 ERROR: Could not find a version that satisfies the requirement tensorflow==2.6.2 (from versions: none)
#6 0.583 ERROR: No matching distribution found for tensorflow==2.6.2
I am able to install tensorflow locally, outside of the Dockerfile. Also, friends are able to build this image from their intel Mac.
I even tried to run docker build com different console architectures: i386 and arm64, but none work.
Any suggestions?
EDIT: you may want to check menrfa's answer by looking at https://github.com/KumaTea/tensorflow-aarch64
The package tensorflow is not available for armv8.
I'll guessing your local python is running using rosetta2 (intel x86_64). You can check that using:
python3 -c "import platform; print(platform.machine())"
x86_64
The solution is forcing Docker to build that image for x86_64 also.
It's easy. Just change your Dockerfile to:
FROM --platform=linux/x86_64 python:3.9
RUN python -m pip install --upgrade pip
RUN pip install tensorflow==2.6.2
Or, if you do not want to change your Dockerfile, you may build that image with:
docker build --platform linux/x86_64 -t myimage .
post note:
as [tyrex] said in a comment, although the tensorflow gets installed on the armv8, it will probably fail due to some bugs on the emulation (eg qemu: uncaught target signal 6 (Aborted) - core dumped).
He solved his requirements using PyTorch instead.
The following works for me. (Chip Apple M1 Pro + MacOS 12.1)
Docker: Debian GNU/Linux 11 (bullseye)
RUN pip install tensorflow==2.6.0 -f https://tf.kmtea.eu/whl/stable.html
Obviously thanks to https://github.com/KumaTea/tensorflow-aarch64
Tensorflow currently does not provide binaries (.whl files) for linux/arch64 inside docker containers on M1.
But you can use my prebuilt TensorFlow .whl file for M1: https://github.com/diyor28/tf-docker-m1