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Installation Issues on Apple M1 device #655
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I can't check what works (the only mac I have access to has an i9), but if the problem for pip installing is TF == 2.4.1, could you work with the nightly build? That has TF 2.7. The nightly pip install also break? |
Hi Owen, thanks for the suggestion! I've just tried installing tfq-nightly using stadard
Again, this must have something to do with tfq-nightly looking for package However, after digging some more I found a way to install it using the x86_64 architecure! I don't know exactly if it is the minimal (or most efficient) solution, but it worked for me (at least for installation and import, haven't tested it in detail yet). Solution: Installing
|
I followed these steps and still get the error: ERROR: Could not find a version that satisfies the requirement tensorflow-quantum (from versions: none) |
I got the same error, too. |
I'm having troubles installing
tensorflow-quantum
on an Apple M1 device.Tensorflow installation is fine following Apple's official guide (https://developer.apple.com/metal/tensorflow-plugin/), though I am not able to install
tfq
, either viapip
or building from source:pip
requirestensorflow==2.4.1
, but Tensorflow for M1 chips comes at least at >v2.5.0;configure.sh
looks fortensorflow
buttensorflow-macos
is installed instead), and also due to Bazel, as the required version (3.7.2) is not available for M1 architectures.Step to reproduce the problem:
First install Tensorflow following Apple's guide, then follow
tfq
installation procedure https://github.com/tensorflow/quantum/blob/master/docs/install.mdIf modifying the
configure.sh
by having it look fortensorflow-macos
(instead oftensorflow
), then problems occur when building with Bazel (the required distribution 3.7.2 is not available for M1 architecture).Installing from source also Tensorflow itself comes with its own bag of installation issues (versions incompatibilities, problems with packages like
numpy
,grpcio
,h5f
, ...), and doesn't feel like the best way to proceed.Is there a workaround or fix? How should one proceed?
Thanks!
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