Installing JAX with gpu/tpu support using poetry

• I have searched the issues of this repo and believe that this is not a duplicate.
• I have searched the documentation and believe that my question is not covered.

Issue

Hi everyone,

I am installing JAX using poetry. I run the command poetry add jax and it works fine but this installs the cpu version, as expected. To install the gpu/tpu version of JAX the documentation indicates that I have to run:

pip install --upgrade "jax[cuda]" -f https://storage.googleapis.com/jax-releases/jax_releases.html pip install "jax[tpu]>=0.2.16" -f https://storage.googleapis.com/jax-releases/libtpu_releases.html

I understand I could run this specific command in my environment, but if I do this, I believe, it is not handled well by poetry. Is there a more poetry way of installing JAX for gpu/tpu ?

Thank you for the help 😃

[pablo2909]

here is the .toml file I have:

[tool.poetry]
name = "test"
version = "0.1.0"
description = ""
authors = 
readme = "README.md"

[tool.poetry.dependencies]
python = "^3.10"
jaxlib = {version = "^0.3.7+cuda11.cudnn82", source = "jax"}



[[tool.poetry.source]]
name = "jax"
url = "https://storage.googleapis.com/jax-releases/jax_releases.html"
default = false
secondary = false

[build-system]
requires = ["poetry-core"]
build-backend = "poetry.core.masonry.api"

and .lock

[[package]]
name = "absl-py"
version = "1.0.0"
description = "Abseil Python Common Libraries, see https://github.com/abseil/abseil-py."
category = "main"
optional = false
python-versions = ">=3.6"

[package.dependencies]
six = "*"

[[package]]
name = "flatbuffers"
version = "2.0"
description = "The FlatBuffers serialization format for Python"
category = "main"
optional = false
python-versions = "*"

[[package]]
name = "jaxlib"
version = "0.3.7+cuda11.cudnn82"
description = "XLA library for JAX"
category = "main"
optional = false
python-versions = ">=3.7"

[package.dependencies]
absl-py = "*"
flatbuffers = ">=1.12,<3.0"
numpy = ">=1.19"
scipy = "*"

[package.source]
type = "legacy"
url = "https://storage.googleapis.com/jax-releases/jax_releases.html"
reference = "jax"

[[package]]
name = "numpy"
version = "1.22.3"
description = "NumPy is the fundamental package for array computing with Python."
category = "main"
optional = false
python-versions = ">=3.8"

[[package]]
name = "scipy"
version = "1.6.1"
description = "SciPy: Scientific Library for Python"
category = "main"
optional = false
python-versions = ">=3.7"

[package.dependencies]
numpy = ">=1.16.5"

[[package]]
name = "six"
version = "1.16.0"
description = "Python 2 and 3 compatibility utilities"
category = "main"
optional = false
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"

[metadata]
lock-version = "1.1"
python-versions = "^3.10"
content-hash = "9f10c226d6b941232791e19862e24808f4136300ba691a1f8505220b8c36ab57"

[metadata.files]
absl-py = [
    {file = "absl-py-1.0.0.tar.gz", hash = "sha256:ac511215c01ee9ae47b19716599e8ccfa746f2e18de72bdf641b79b22afa27ea"},
    {file = "absl_py-1.0.0-py3-none-any.whl", hash = "sha256:84e6dcdc69c947d0c13e5457d056bd43cade4c2393dce00d684aedea77ddc2a3"},
]
flatbuffers = [
    {file = "flatbuffers-2.0-py2.py3-none-any.whl", hash = "sha256:3751954f0604580d3219ae49a85fafec9d85eec599c0b96226e1bc0b48e57474"},
    {file = "flatbuffers-2.0.tar.gz", hash = "sha256:12158ab0272375eab8db2d663ae97370c33f152b27801fa6024e1d6105fd4dd2"},
]
jaxlib = [
    {file = "jaxlib-0.3.7+cuda11.cudnn82-cp310-none-manylinux2014_x86_64.whl", hash = "sha256:1d7e540071bad5a76a2ad8a2b6c0dd075adaabe4bab7fb6e116f04ff5425fe1b"},
    {file = "jaxlib-0.3.7+cuda11.cudnn82-cp37-none-manylinux2014_x86_64.whl", hash = "sha256:8ce56ccf18fd79c476910251875e7f0f73417d4ec4912b29b2066d9ff8d82997"},
    {file = "jaxlib-0.3.7+cuda11.cudnn82-cp38-none-manylinux2014_x86_64.whl", hash = "sha256:f6076884c5d1bbf55c2fb153454afb118beeedcd85189793217c82ecb234fc8c"},
    {file = "jaxlib-0.3.7+cuda11.cudnn82-cp39-none-manylinux2014_x86_64.whl", hash = "sha256:16a87c125f0075d62995b18eba449e962b45db010435e6f0a65ee701378fc75f"},
]
numpy = [
    {file = "numpy-1.22.3-cp310-cp310-macosx_10_14_x86_64.whl", hash = "sha256:92bfa69cfbdf7dfc3040978ad09a48091143cffb778ec3b03fa170c494118d75"},
    {file = "numpy-1.22.3-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:8251ed96f38b47b4295b1ae51631de7ffa8260b5b087808ef09a39a9d66c97ab"},
    {file = "numpy-1.22.3-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:48a3aecd3b997bf452a2dedb11f4e79bc5bfd21a1d4cc760e703c31d57c84b3e"},
    {file = "numpy-1.22.3-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a3bae1a2ed00e90b3ba5f7bd0a7c7999b55d609e0c54ceb2b076a25e345fa9f4"},
    {file = "numpy-1.22.3-cp310-cp310-win32.whl", hash = "sha256:f950f8845b480cffe522913d35567e29dd381b0dc7e4ce6a4a9f9156417d2430"},
    {file = "numpy-1.22.3-cp310-cp310-win_amd64.whl", hash = "sha256:08d9b008d0156c70dc392bb3ab3abb6e7a711383c3247b410b39962263576cd4"},
    {file = "numpy-1.22.3-cp38-cp38-macosx_10_14_x86_64.whl", hash = "sha256:201b4d0552831f7250a08d3b38de0d989d6f6e4658b709a02a73c524ccc6ffce"},
    {file = "numpy-1.22.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:f8c1f39caad2c896bc0018f699882b345b2a63708008be29b1f355ebf6f933fe"},
    {file = "numpy-1.22.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:568dfd16224abddafb1cbcce2ff14f522abe037268514dd7e42c6776a1c3f8e5"},
    {file = "numpy-1.22.3-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:3ca688e1b9b95d80250bca34b11a05e389b1420d00e87a0d12dc45f131f704a1"},
    {file = "numpy-1.22.3-cp38-cp38-win32.whl", hash = "sha256:e7927a589df200c5e23c57970bafbd0cd322459aa7b1ff73b7c2e84d6e3eae62"},
    {file = "numpy-1.22.3-cp38-cp38-win_amd64.whl", hash = "sha256:07a8c89a04997625236c5ecb7afe35a02af3896c8aa01890a849913a2309c676"},
    {file = "numpy-1.22.3-cp39-cp39-macosx_10_14_x86_64.whl", hash = "sha256:2c10a93606e0b4b95c9b04b77dc349b398fdfbda382d2a39ba5a822f669a0123"},
    {file = "numpy-1.22.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:fade0d4f4d292b6f39951b6836d7a3c7ef5b2347f3c420cd9820a1d90d794802"},
    {file = "numpy-1.22.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5bfb1bb598e8229c2d5d48db1860bcf4311337864ea3efdbe1171fb0c5da515d"},
    {file = "numpy-1.22.3-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:97098b95aa4e418529099c26558eeb8486e66bd1e53a6b606d684d0c3616b168"},
    {file = "numpy-1.22.3-cp39-cp39-win32.whl", hash = "sha256:fdf3c08bce27132395d3c3ba1503cac12e17282358cb4bddc25cc46b0aca07aa"},
    {file = "numpy-1.22.3-cp39-cp39-win_amd64.whl", hash = "sha256:639b54cdf6aa4f82fe37ebf70401bbb74b8508fddcf4797f9fe59615b8c5813a"},
    {file = "numpy-1.22.3-pp38-pypy38_pp73-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c34ea7e9d13a70bf2ab64a2532fe149a9aced424cd05a2c4ba662fd989e3e45f"},
    {file = "numpy-1.22.3.zip", hash = "sha256:dbc7601a3b7472d559dc7b933b18b4b66f9aa7452c120e87dfb33d02008c8a18"},
]
scipy = [
    {file = "scipy-1.6.1-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:a15a1f3fc0abff33e792d6049161b7795909b40b97c6cc2934ed54384017ab76"},
    {file = "scipy-1.6.1-cp37-cp37m-manylinux1_i686.whl", hash = "sha256:e79570979ccdc3d165456dd62041d9556fb9733b86b4b6d818af7a0afc15f092"},
    {file = "scipy-1.6.1-cp37-cp37m-manylinux1_x86_64.whl", hash = "sha256:a423533c55fec61456dedee7b6ee7dce0bb6bfa395424ea374d25afa262be261"},
    {file = "scipy-1.6.1-cp37-cp37m-manylinux2014_aarch64.whl", hash = "sha256:33d6b7df40d197bdd3049d64e8e680227151673465e5d85723b3b8f6b15a6ced"},
    {file = "scipy-1.6.1-cp37-cp37m-win32.whl", hash = "sha256:6725e3fbb47da428794f243864f2297462e9ee448297c93ed1dcbc44335feb78"},
    {file = "scipy-1.6.1-cp37-cp37m-win_amd64.whl", hash = "sha256:5fa9c6530b1661f1370bcd332a1e62ca7881785cc0f80c0d559b636567fab63c"},
    {file = "scipy-1.6.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:bd50daf727f7c195e26f27467c85ce653d41df4358a25b32434a50d8870fc519"},
    {file = "scipy-1.6.1-cp38-cp38-manylinux1_i686.whl", hash = "sha256:f46dd15335e8a320b0fb4685f58b7471702234cba8bb3442b69a3e1dc329c345"},
    {file = "scipy-1.6.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:0e5b0ccf63155d90da576edd2768b66fb276446c371b73841e3503be1d63fb5d"},
    {file = "scipy-1.6.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:2481efbb3740977e3c831edfd0bd9867be26387cacf24eb5e366a6a374d3d00d"},
    {file = "scipy-1.6.1-cp38-cp38-win32.whl", hash = "sha256:68cb4c424112cd4be886b4d979c5497fba190714085f46b8ae67a5e4416c32b4"},
    {file = "scipy-1.6.1-cp38-cp38-win_amd64.whl", hash = "sha256:5f331eeed0297232d2e6eea51b54e8278ed8bb10b099f69c44e2558c090d06bf"},
    {file = "scipy-1.6.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:0c8a51d33556bf70367452d4d601d1742c0e806cd0194785914daf19775f0e67"},
    {file = "scipy-1.6.1-cp39-cp39-manylinux1_i686.whl", hash = "sha256:83bf7c16245c15bc58ee76c5418e46ea1811edcc2e2b03041b804e46084ab627"},
    {file = "scipy-1.6.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:794e768cc5f779736593046c9714e0f3a5940bc6dcc1dba885ad64cbfb28e9f0"},
    {file = "scipy-1.6.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:5da5471aed911fe7e52b86bf9ea32fb55ae93e2f0fac66c32e58897cfb02fa07"},
    {file = "scipy-1.6.1-cp39-cp39-win32.whl", hash = "sha256:8e403a337749ed40af60e537cc4d4c03febddcc56cd26e774c9b1b600a70d3e4"},
    {file = "scipy-1.6.1-cp39-cp39-win_amd64.whl", hash = "sha256:a5193a098ae9f29af283dcf0041f762601faf2e595c0db1da929875b7570353f"},
    {file = "scipy-1.6.1.tar.gz", hash = "sha256:c4fceb864890b6168e79b0e714c585dbe2fd4222768ee90bc1aa0f8218691b11"},
]
six = [
    {file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
    {file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
]

[pablo2909]

Nice, thank you for your help. Looking forward for this feature to be merged !