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20 hours ago •
astral-sh
astral-sh
uv pip and python -m pip resolve different versions of tensorflow in pyhf developer environment
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Hi. :wave: While trying to adopt uv for use in the pyhf CI system (https://github.com/scikit-hep/pyhf/pull/2444) we've found that we're getting different environment solves between python -m pip install and uv pip install. The result of uv pip install results in an unusable environment of tensorflow v2.11.1 and tensorflow-probability v0.20.1 while python -m pip install resolves in the (in our view "correct") usable environment of tensorflow v2.13.1 and tensorflow-probability v0.20.1.
To avoid overwhelming wall of text I've broken the reproducible example in a Docker container into two sections that can be expanded below.
Here's the other requested info up front though:
- The current uv platform: The
python:3.8Docker container image
# uname -a
Linux 2c24021d2969 6.5.0-15-generic #15~22.04.1-Ubuntu SMP PREEMPT_DYNAMIC Fri Jan 12 18:54:30 UTC 2 x86_64 GNU/Linux
- The current uv version (
uv --version):uv 0.1.12
Using pip
Using pip:
$ docker run --rm -ti python:3.8 /bin/bash
root@2c24021d2969:/# python -m venv venv && . venv/bin/activate
(venv) root@2c24021d2969:/# python -m pip --quiet install --upgrade pip setuptools wheel
(venv) root@2c24021d2969:/# git clone https://github.com/scikit-hep/pyhf.git --branch main --single-branch && cd pyhf
(venv) root@2c24021d2969:/pyhf# git reset --hard fc5e83018d2a2c98156e5073a6e630793a1edd55
(venv) root@2c24021d2969:/pyhf# python -m pip --verbose --no-cache-dir install --upgrade '.[all,test]' &> /tmp/python-pip-install-verbose.txt
(venv) root@2c24021d2969:/pyhf# python -m pip list
Package Version
---------------------------- ---------------
absl-py 2.1.0
ansiwrap 0.8.4
anyio 4.3.0
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.3.0
asttokens 2.4.1
astunparse 1.6.3
async-lru 2.0.4
attrs 23.2.0
awkward 2.6.1
awkward-cpp 29
Babel 2.14.0
backcall 0.2.0
beautifulsoup4 4.12.3
bleach 6.1.0
cachetools 5.3.3
certifi 2024.2.2
cffi 1.16.0
charset-normalizer 3.3.2
click 8.1.7
click-completion 0.5.2
cloudpickle 3.0.0
comm 0.2.1
contourpy 1.1.1
coverage 7.4.3
cramjam 2.8.1
cycler 0.12.1
debugpy 1.8.1
decorator 5.1.1
defusedxml 0.7.1
dm-tree 0.1.8
entrypoints 0.4
exceptiongroup 1.2.0
executing 2.0.1
fastjsonschema 2.19.1
filelock 3.13.1
flatbuffers 23.5.26
fonttools 4.49.0
fqdn 1.5.1
fsspec 2024.2.0
gast 0.4.0
google-auth 2.28.1
google-auth-oauthlib 1.0.0
google-pasta 0.2.0
graphviz 0.20.1
grpcio 1.62.0
h11 0.14.0
h5py 3.10.0
httpcore 1.0.4
httpx 0.27.0
idna 3.6
iminuit 2.25.2
importlib-metadata 7.0.1
importlib_resources 6.1.2
iniconfig 2.0.0
ipykernel 6.29.3
ipympl 0.9.3
ipython 8.12.3
ipython-genutils 0.2.0
ipywidgets 8.1.2
isoduration 20.11.0
jax 0.4.13
jaxlib 0.4.13
jedi 0.19.1
Jinja2 3.1.3
json5 0.9.17
jsonpatch 1.33
jsonpointer 2.4
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
jupyter 1.0.0
jupyter_client 8.6.0
jupyter-console 6.6.3
jupyter_core 5.7.1
jupyter-events 0.9.0
jupyter-lsp 2.2.3
jupyter_server 2.12.5
jupyter_server_terminals 0.5.2
jupyterlab 4.1.2
jupyterlab_pygments 0.3.0
jupyterlab_server 2.25.3
jupyterlab_widgets 3.0.10
keras 2.13.1
kiwisolver 1.4.5
libclang 16.0.6
Markdown 3.5.2
MarkupSafe 2.1.5
matplotlib 3.7.5
matplotlib-inline 0.1.6
mistune 3.0.2
ml-dtypes 0.2.0
mpmath 1.3.0
nbclient 0.9.0
nbconvert 7.16.1
nbformat 5.9.2
nest-asyncio 1.6.0
networkx 3.1
notebook 7.1.1
notebook_shim 0.2.4
numpy 1.24.3
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu12 2.18.1
nvidia-nvjitlink-cu12 12.3.101
nvidia-nvtx-cu12 12.1.105
oauthlib 3.2.2
opt-einsum 3.3.0
overrides 7.7.0
packaging 23.2
pandas 2.0.3
pandocfilters 1.5.1
papermill 2.3.4
parso 0.8.3
pexpect 4.9.0
pickleshare 0.7.5
pillow 10.2.0
pip 24.0
pkgutil_resolve_name 1.3.10
platformdirs 4.2.0
pluggy 1.4.0
prometheus_client 0.20.0
prompt-toolkit 3.0.43
protobuf 4.25.3
psutil 5.9.8
ptyprocess 0.7.0
pure-eval 0.2.2
py-cpuinfo 9.0.0
pyarrow 15.0.0
pyasn1 0.5.1
pyasn1-modules 0.3.0
pycparser 2.21
pydocstyle 6.3.0
pygal 3.0.4
pygaljs 1.0.2
Pygments 2.17.2
pyhf 0.7.1.dev220
pyparsing 3.1.1
pytest 8.0.2
pytest-benchmark 4.0.0
pytest-console-scripts 1.4.1
pytest-mock 3.12.0
pytest-mpl 0.17.0
pytest-socket 0.7.0
python-dateutil 2.8.2
python-json-logger 2.0.7
pytz 2024.1
PyYAML 6.0.1
pyzmq 25.1.2
qtconsole 5.5.1
QtPy 2.4.1
referencing 0.33.0
requests 2.31.0
requests-mock 1.11.0
requests-oauthlib 1.3.1
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rpds-py 0.18.0
rsa 4.9
scikit_hep_testdata 0.4.38
scipy 1.10.1
scrapbook 0.5.0
Send2Trash 1.8.2
setuptools 69.1.1
shellingham 1.5.4
six 1.16.0
sniffio 1.3.1
snowballstemmer 2.2.0
soupsieve 2.5
stack-data 0.6.3
sympy 1.12
tenacity 8.2.3
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
terminado 0.18.0
textwrap3 0.9.2
tinycss2 1.2.1
tomli 2.0.1
torch 2.1.2
tornado 6.4
tqdm 4.66.2
traitlets 5.14.1
triton 2.1.0
types-python-dateutil 2.8.19.20240106
typing_extensions 4.5.0
tzdata 2024.1
uproot 5.3.1
uri-template 1.3.0
urllib3 2.2.1
wcwidth 0.2.13
webcolors 1.13
webencodings 0.5.1
websocket-client 1.7.0
Werkzeug 3.0.1
wheel 0.42.0
widgetsnbextension 4.0.10
wrapt 1.16.0
zipp 3.17.0
(venv) root@2c24021d2969:/pyhf# python -m pip list | grep 'tensor'
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(venv) root@2c24021d2969:/pyhf# python -m pip show tensorflow
Name: tensorflow
Version: 2.13.1
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: [email protected]
License: Apache 2.0
Location: /venv/lib/python3.8/site-packages
Requires: absl-py, astunparse, flatbuffers, gast, google-pasta, grpcio, h5py, keras, libclang, numpy, opt-einsum, packaging, protobuf, setuptools, six, tensorboard, tensorflow-estimator, tensorflow-io-gcs-filesystem, termcolor, typing-extensions, wrapt
Required-by:
(venv) root@2c24021d2969:/pyhf# python -c 'import tensorflow; import tensorflow_probability' # no error
2024-02-29 00:04:43.719791: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-02-29 00:04:43.764247: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-29 00:04:44.089063: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-02-29 00:04:44.090564: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-02-29 00:04:44.978663: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
(venv) root@2c24021d2969:/pyhf#
python-pip-install-verbose.txt
and now in a virtual environment with uv (version 0.1.12)
uv v0.1.12:
(venv) root@2c24021d2969:/pyhf# deactivate
root@2c24021d2969:/pyhf# python -m venv /uv-venv && . /uv-venv/bin/activate
(uv-venv) root@2c24021d2969:/pyhf# python -m pip --quiet install --upgrade pip setuptools wheel uv
(uv-venv) root@2c24021d2969:/pyhf# uv --version
uv 0.1.12
(uv-venv) root@2c24021d2969:/pyhf# uv pip --verbose --no-cache install --upgrade 'pyhf[all,test] @ .' &> /tmp/uv-pip-install-verbose.txt
(uv-venv) root@2c24021d2969:/pyhf# uv pip list
Package Version
---------------------------- ---------------
absl-py 2.1.0
ansiwrap 0.8.4
anyio 4.3.0
argon2-cffi 23.1.0
argon2-cffi-bindings 21.2.0
arrow 1.3.0
asttokens 2.4.1
astunparse 1.6.3
async-lru 2.0.4
attrs 23.2.0
awkward 2.6.1
awkward-cpp 29
babel 2.14.0
backcall 0.2.0
beautifulsoup4 4.12.3
bleach 6.1.0
cachetools 5.3.3
certifi 2024.2.2
cffi 1.16.0
charset-normalizer 3.3.2
click 8.1.7
click-completion 0.5.2
cloudpickle 3.0.0
comm 0.2.1
contourpy 1.1.1
coverage 7.4.3
cramjam 2.8.1
cycler 0.12.1
debugpy 1.8.1
decorator 5.1.1
defusedxml 0.7.1
dm-tree 0.1.8
entrypoints 0.4
exceptiongroup 1.2.0
executing 2.0.1
fastjsonschema 2.19.1
filelock 3.13.1
flatbuffers 23.5.26
fonttools 4.49.0
fqdn 1.5.1
fsspec 2024.2.0
gast 0.4.0
google-auth 2.28.1
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
graphviz 0.20.1
grpcio 1.62.0
h11 0.14.0
h5py 3.10.0
httpcore 1.0.4
httpx 0.27.0
idna 3.6
iminuit 2.25.2
importlib-metadata 7.0.1
importlib-resources 6.1.2
iniconfig 2.0.0
ipykernel 6.29.3
ipympl 0.9.3
ipython 8.12.3
ipython-genutils 0.2.0
ipywidgets 8.1.2
isoduration 20.11.0
jax 0.4.13
jaxlib 0.4.13
jedi 0.19.1
jinja2 3.1.3
json5 0.9.17
jsonpatch 1.33
jsonpointer 2.4
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
jupyter 1.0.0
jupyter-client 8.6.0
jupyter-console 6.6.3
jupyter-core 5.7.1
jupyter-events 0.9.0
jupyter-lsp 2.2.3
jupyter-server 2.12.5
jupyter-server-terminals 0.5.2
jupyterlab 4.1.2
jupyterlab-pygments 0.3.0
jupyterlab-server 2.25.3
jupyterlab-widgets 3.0.10
keras 2.11.0
kiwisolver 1.4.5
libclang 16.0.6
markdown 3.5.2
markupsafe 2.1.5
matplotlib 3.7.5
matplotlib-inline 0.1.6
mistune 3.0.2
ml-dtypes 0.2.0
mpmath 1.3.0
nbclient 0.9.0
nbconvert 7.16.1
nbformat 5.9.2
nest-asyncio 1.6.0
networkx 3.1
notebook 7.1.1
notebook-shim 0.2.4
numpy 1.24.4
nvidia-cublas-cu12 12.1.3.1
nvidia-cuda-cupti-cu12 12.1.105
nvidia-cuda-nvrtc-cu12 12.1.105
nvidia-cuda-runtime-cu12 12.1.105
nvidia-cudnn-cu12 8.9.2.26
nvidia-cufft-cu12 11.0.2.54
nvidia-curand-cu12 10.3.2.106
nvidia-cusolver-cu12 11.4.5.107
nvidia-cusparse-cu12 12.1.0.106
nvidia-nccl-cu12 2.19.3
nvidia-nvjitlink-cu12 12.3.101
nvidia-nvtx-cu12 12.1.105
oauthlib 3.2.2
opt-einsum 3.3.0
overrides 7.7.0
packaging 23.2
pandas 2.0.3
pandocfilters 1.5.1
papermill 2.3.4
parso 0.8.3
pexpect 4.9.0
pickleshare 0.7.5
pillow 10.2.0
pip 24.0
pkgutil-resolve-name 1.3.10
platformdirs 4.2.0
pluggy 1.4.0
prometheus-client 0.20.0
prompt-toolkit 3.0.43
protobuf 3.19.6
psutil 5.9.8
ptyprocess 0.7.0
pure-eval 0.2.2
py-cpuinfo 9.0.0
pyarrow 15.0.0
pyasn1 0.5.1
pyasn1-modules 0.3.0
pycparser 2.21
pydocstyle 6.3.0
pygal 3.0.4
pygaljs 1.0.2
pygments 2.17.2
pyhf 0.7.1.dev220
pyparsing 3.1.1
pytest 8.0.2
pytest-benchmark 4.0.0
pytest-console-scripts 1.4.1
pytest-mock 3.12.0
pytest-mpl 0.17.0
pytest-socket 0.7.0
python-dateutil 2.8.2
python-json-logger 2.0.7
pytz 2024.1
pyyaml 6.0.1
pyzmq 25.1.2
qtconsole 5.5.1
qtpy 2.4.1
referencing 0.33.0
requests 2.31.0
requests-mock 1.11.0
requests-oauthlib 1.3.1
rfc3339-validator 0.1.4
rfc3986-validator 0.1.1
rpds-py 0.18.0
rsa 4.9
scikit-hep-testdata 0.4.38
scipy 1.10.1
scrapbook 0.5.0
send2trash 1.8.2
setuptools 69.1.1
shellingham 1.5.4
six 1.16.0
sniffio 1.3.1
snowballstemmer 2.2.0
soupsieve 2.5
stack-data 0.6.3
sympy 1.12
tenacity 8.2.3
tensorboard 2.11.2
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow 2.11.1
tensorflow-estimator 2.11.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.20.1
termcolor 2.4.0
terminado 0.18.0
textwrap3 0.9.2
tinycss2 1.2.1
tomli 2.0.1
torch 2.2.1
tornado 6.4
tqdm 4.66.2
traitlets 5.14.1
triton 2.2.0
types-python-dateutil 2.8.19.20240106
typing-extensions 4.10.0
tzdata 2024.1
uproot 5.3.1
uri-template 1.3.0
urllib3 2.2.1
uv 0.1.12
wcwidth 0.2.13
webcolors 1.13
webencodings 0.5.1
websocket-client 1.7.0
werkzeug 3.0.1
wheel 0.42.0
widgetsnbextension 4.0.10
wrapt 1.16.0
zipp 3.17.0
(uv-venv) root@2c24021d2969:/pyhf# uv pip list | grep tensorflow
tensorflow 2.11.1
tensorflow-estimator 2.11.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.20.1
(uv-venv) root@2c24021d2969:/pyhf# python -m pip show tensorflow
Name: tensorflow
Version: 2.11.1
Summary: TensorFlow is an open source machine learning framework for everyone.
Home-page: https://www.tensorflow.org/
Author: Google Inc.
Author-email: [email protected]
License: Apache 2.0
Location: /uv-venv/lib/python3.8/site-packages
Requires: absl-py, astunparse, flatbuffers, gast, google-pasta, grpcio, h5py, keras, libclang, numpy, opt-einsum, packaging, protobuf, setuptools, six, tensorboard, tensorflow-estimator, tensorflow-io-gcs-filesystem, termcolor, typing-extensions, wrapt
Required-by:
(uv-venv) root@2c24021d2969:/pyhf# python -c 'import tensorflow; import tensorflow_probability'
2024-02-29 00:04:00.444303: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-02-29 00:04:00.527810: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-02-29 00:04:00.531317: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2024-02-29 00:04:00.531351: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2024-02-29 00:04:01.047385: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2024-02-29 00:04:01.047437: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2024-02-29 00:04:01.047442: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/__init__.py", line 20, in <module>
from tensorflow_probability import substrates
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/substrates/__init__.py", line 17, in <module>
from tensorflow_probability.python.internal import all_util
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/python/__init__.py", line 138, in <module>
dir(globals()[pkg_name]) # Forces loading the package from its lazy loader.
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/python/internal/lazy_loader.py", line 57, in __dir__
module = self._load()
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/python/internal/lazy_loader.py", line 37, in _load
self._on_first_access()
File "/uv-venv/lib/python3.8/site-packages/tensorflow_probability/python/__init__.py", line 59, in _validate_tf_environment
raise ImportError(
ImportError: This version of TensorFlow Probability requires TensorFlow version >= 2.12; Detected an installation of version 2.11.1. Please upgrade TensorFlow to proceed.
(uv-venv) root@2c24021d2969:/pyhf#
Will take a look... My guess is that these are both "valid" resolutions (since uv did pin some packages to more recent versions), and the difference is due to semi-arbitrary choices in how resolution played out in the two systems. But there could be a bug somewhere.
Also confusing is that tensorflow_probability doesn't encode this constraint in its metadata, as far as I can tell? There's no tensorflow version constraint in tensorflow_probability.
Will take a look
Thanks!
Also confusing is that
tensorflow_probabilitydoesn't encode this constraint in its metadata, as far as I can tell? There's notensorflowversion constraint intensorflow_probability.
Correct, tensorflow-probability doesn't specifically require tensorflow as a dependency as it can work with other libraries, but it then does the internal check on the tensorflow version seen in the error log if you attempt to import them together. I can make an additional reproducer later today, but I believe if you just create an environment with just tensorflow and tensorflow-probability then uv will match pip's solve.
I'm speculating here, but I would make the guess that this is another example of uv backtracking on the package creating an upper bound requirement, rather than backtracking on the package being upper bounded, like in https://github.com/astral-sh/uv/issues/1398.
In this case tensorflow is upper bounding gast, grpcio, keras, numpy, protobuf, tensorboard, tensorflow-estimator, and wrapt. Skimming over the verbose logs I would say the most likely culprit is numpy. I can check later but I suspect the resolution is going to be better (and faster) with a pinned or lower bound requirement on numpy, or one of the other packages.
This kind of issue would came up a lot on the pip issue tracker after pip debuted it's resolver, that a new release of pip would cause a different solution. It's not that the resolver is incorrect, it's a kind of performance issue, if the user has strict lower bounds they want on certain packages they should include it in their requirements or constraints.
I can make an additional reproducer later today, but I believe if you just create an environment with just
tensorflowandtensorflow-probabilitythenuvwill matchpip's solve.
Yeah, for just installing tensorflow and tensorflow-probability the solves are the same
Using pip:
$ docker run --rm -ti python:3.8 /bin/bash
root@0aa33f8bda2c:/# python -m venv venv && . venv/bin/activate
(venv) root@0aa33f8bda2c:/# python -m pip --quiet install --upgrade pip setuptools wheel
(venv) root@0aa33f8bda2c:/# python -m pip --verbose --no-cache-dir install --upgrade tensorflow tensorflow-probability &> /tmp/python-pip-install-verbose.txt
(venv) root@0aa33f8bda2c:/# python -m pip list
Package Version
---------------------------- --------
absl-py 2.1.0
astunparse 1.6.3
cachetools 5.3.3
certifi 2024.2.2
charset-normalizer 3.3.2
cloudpickle 3.0.0
decorator 5.1.1
dm-tree 0.1.8
flatbuffers 23.5.26
gast 0.4.0
google-auth 2.28.1
google-auth-oauthlib 1.0.0
google-pasta 0.2.0
grpcio 1.62.0
h5py 3.10.0
idna 3.6
importlib-metadata 7.0.1
keras 2.13.1
libclang 16.0.6
Markdown 3.5.2
MarkupSafe 2.1.5
numpy 1.24.3
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 23.2
pip 24.0
protobuf 4.25.3
pyasn1 0.5.1
pyasn1-modules 0.3.0
requests 2.31.0
requests-oauthlib 1.3.1
rsa 4.9
setuptools 69.1.1
six 1.16.0
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
typing_extensions 4.5.0
urllib3 2.2.1
Werkzeug 3.0.1
wheel 0.42.0
wrapt 1.16.0
zipp 3.17.0
(venv) root@0aa33f8bda2c:/# python -m pip list | grep tensor
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(venv) root@0aa33f8bda2c:/#
python-pip-install-verbose.txt
uv v0.1.13:
(venv) root@0aa33f8bda2c:/# deactivate
root@0aa33f8bda2c:/# python -m venv /uv-venv && . /uv-venv/bin/activate
(uv-venv) root@0aa33f8bda2c:/# python -m pip --quiet install --upgrade pip setuptools wheel uv
(uv-venv) root@0aa33f8bda2c:/# uv --version
uv 0.1.13
(uv-venv) root@0aa33f8bda2c:/# uv pip --verbose --no-cache install --upgrade tensorflow tensorflow-probability &> /tmp/uv-pip-install-verbose.txt
(uv-venv) root@0aa33f8bda2c:/# uv pip list
Package Version
---------------------------- --------
absl-py 2.1.0
astunparse 1.6.3
cachetools 5.3.3
certifi 2024.2.2
charset-normalizer 3.3.2
cloudpickle 3.0.0
decorator 5.1.1
dm-tree 0.1.8
flatbuffers 23.5.26
gast 0.4.0
google-auth 2.28.1
google-auth-oauthlib 1.0.0
google-pasta 0.2.0
grpcio 1.62.0
h5py 3.10.0
idna 3.6
importlib-metadata 7.0.1
keras 2.13.1
libclang 16.0.6
markdown 3.5.2
markupsafe 2.1.5
numpy 1.24.3
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 23.2
pip 24.0
protobuf 4.25.3
pyasn1 0.5.1
pyasn1-modules 0.3.0
requests 2.31.0
requests-oauthlib 1.3.1
rsa 4.9
setuptools 69.1.1
six 1.16.0
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
typing-extensions 4.5.0
urllib3 2.2.1
uv 0.1.13
werkzeug 3.0.1
wheel 0.42.0
wrapt 1.16.0
zipp 3.17.0
(uv-venv) root@0aa33f8bda2c:/# uv pip list | grep tensor
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(uv-venv) root@0aa33f8bda2c:/#
When trying to add tensorflow[and-cuda]==2.16.1, uv reports that nvidia-cublas-cu12==12.3.4.1 does not exist, even though it's right here: https://pypi.org/project/nvidia-cublas-cu12/12.3.4.1/
Here's a more minimal reproducer of the problem, using pyhf at https://github.com/scikit-hep/pyhf/commit/08755e45ed134cbe6e5e6e238b7b5011700080b3 and
$ uv --version
uv 0.1.39
At this commit, pyhf's 'tensorflow' extra is the following
tensorflow = [
# python == 3.8
"tensorflow>=2.7.0; python_version < '3.9' and platform_machine != 'arm64'", # c.f. PR #1962, #2452
"tensorflow-macos>=2.7.0; python_version < '3.9' and platform_machine == 'arm64' and platform_system == 'Darwin'", # c.f. PR #2119, #2452
"tensorflow-probability>=0.11.0; python_version < '3.9'", # c.f. PR #1657, #2452
# python >= 3.9
"tensorflow-probability[tf]>=0.24.0; python_version >= '3.9'" # c.f. PR #2452
]
so on Python 3.8 (Linux) running
uv pip install '.[tensorflow]'
should be the same as running
uv pip install . 'tensorflow>=2.7.0' 'tensorflow-probability>=0.11.0'
yet these result in different environments, where I (as the developer) can say that the second environment is the expected solve.
uv v0.1.39 with tensorflow extra (failure case):
$ docker run --rm -ti -v /tmp:/tmp python:3.8 /bin/bash
root@4935323db0ed:/# curl -LsSf https://astral.sh/uv/install.sh | sh
downloading uv 0.1.39 x86_64-unknown-linux-gnu
installing to /root/.cargo/bin
uv
everything's installed!
To add $HOME/.cargo/bin to your PATH, either restart your shell or run:
source $HOME/.cargo/env
root@4935323db0ed:/# . ~/.cargo/env
root@4935323db0ed:/# uv venv && . .venv/bin/activate
Using Python 3.8.19 interpreter at: usr/local/bin/python3
Creating virtualenv at: .venv
(.venv) root@4935323db0ed:/# git clone --single-branch https://github.com/scikit-hep/pyhf.git && cd pyhf && git reset --hard 08755e45ed134cbe6e5e6e238b7b5011700080b3
(.venv) root@4935323db0ed:/pyhf# uv --version
uv 0.1.39
(.venv) root@4935323db0ed:/pyhf# uv pip --verbose --no-cache install '.[tensorflow]' &> /tmp/uv-pip-install-tensorflow-extra-verbose.txt
(.venv) root@4935323db0ed:/pyhf# uv pip list
Package Version
---------------------------- ------------
absl-py 2.1.0
astunparse 1.6.3
attrs 23.2.0
cachetools 5.3.3
certifi 2024.2.2
charset-normalizer 3.3.2
click 8.1.7
cloudpickle 3.0.0
decorator 5.1.1
dm-tree 0.1.8
flatbuffers 24.3.25
gast 0.4.0
google-auth 2.29.0
google-auth-oauthlib 0.4.6
google-pasta 0.2.0
grpcio 1.62.2
h5py 3.11.0
idna 3.7
importlib-metadata 7.1.0
importlib-resources 6.4.0
jsonpatch 1.33
jsonpointer 2.4
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
keras 2.11.0
libclang 18.1.1
markdown 3.6
markupsafe 2.1.5
numpy 1.24.4
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 24.0
pkgutil-resolve-name 1.3.10
protobuf 3.19.6
pyasn1 0.6.0
pyasn1-modules 0.4.0
pyhf 0.7.1.dev238
pyyaml 6.0.1
referencing 0.35.0
requests 2.31.0
requests-oauthlib 2.0.0
rpds-py 0.18.0
rsa 4.9
scipy 1.10.1
setuptools 69.5.1
six 1.16.0
tensorboard 2.11.2
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorflow 2.11.1
tensorflow-estimator 2.11.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
tqdm 4.66.2
typing-extensions 4.5.0
urllib3 2.2.1
werkzeug 3.0.2
wheel 0.43.0
wrapt 1.16.0
zipp 3.18.1
(.venv) root@4935323db0ed:/pyhf# uv pip list | grep tensorflow
tensorflow 2.11.1
tensorflow-estimator 2.11.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(.venv) root@4935323db0ed:/pyhf# python -c 'import tensorflow; import tensorflow_probability'
2024-04-30 07:01:07.319640: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations: AVX2 AVX_VNNI FMA
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-04-30 07:01:07.399553: I tensorflow/core/util/port.cc:104] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-04-30 07:01:07.402137: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libcudart.so.11.0'; dlerror: libcudart.so.11.0: cannot open shared object file: No such file or directory
2024-04-30 07:01:07.402156: I tensorflow/compiler/xla/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
2024-04-30 07:01:09.446572: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer.so.7'; dlerror: libnvinfer.so.7: cannot open shared object file: No such file or directory
2024-04-30 07:01:09.446619: W tensorflow/compiler/xla/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'libnvinfer_plugin.so.7'; dlerror: libnvinfer_plugin.so.7: cannot open shared object file: No such file or directory
2024-04-30 07:01:09.446626: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Cannot dlopen some TensorRT libraries. If you would like to use Nvidia GPU with TensorRT, please make sure the missing libraries mentioned above are installed properly.
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/__init__.py", line 20, in <module>
from tensorflow_probability import substrates
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/substrates/__init__.py", line 17, in <module>
from tensorflow_probability.python.internal import all_util
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/python/__init__.py", line 138, in <module>
dir(globals()[pkg_name]) # Forces loading the package from its lazy loader.
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/python/internal/lazy_loader.py", line 57, in __dir__
module = self._load()
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/python/internal/lazy_loader.py", line 37, in _load
self._on_first_access()
File "/.venv/lib/python3.8/site-packages/tensorflow_probability/python/__init__.py", line 59, in _validate_tf_environment
raise ImportError(
ImportError: This version of TensorFlow Probability requires TensorFlow version >= 2.13; Detected an installation of version 2.11.1. Please upgrade TensorFlow to proceed.
(.venv) root@4935323db0ed:/pyhf#
uv-pip-install-tensorflow-extra-verbose.txt
uv v0.1.39 with tensorflow,tfp on command line (success case):
$ docker run --rm -ti -v /tmp:/tmp python:3.8 /bin/bash
root@edbb84aa61db:/# curl -LsSf https://astral.sh/uv/install.sh | sh
downloading uv 0.1.39 x86_64-unknown-linux-gnu
installing to /root/.cargo/bin
uv
everything's installed!
To add $HOME/.cargo/bin to your PATH, either restart your shell or run:
source $HOME/.cargo/env
root@edbb84aa61db:/# . ~/.cargo/env
root@edbb84aa61db:/# uv venv && . .venv/bin/activate
Using Python 3.8.19 interpreter at: usr/local/bin/python3
Creating virtualenv at: .venv
(.venv) root@edbb84aa61db:/# git clone --single-branch https://github.com/scikit-hep/pyhf.git && cd pyhf && git reset --hard 08755e45ed134cbe6e5e6e238b7b5011700080b3
(.venv) root@edbb84aa61db:/pyhf# uv pip --verbose --no-cache install . 'tensorflow>=2.7.0' 'tensorflow-probability>=0.11.0' &> /tmp/uv-pip-install-tensorflow-command-line-verbose.txt
(.venv) root@edbb84aa61db:/pyhf# uv pip list
Package Version
---------------------------- ------------
absl-py 2.1.0
astunparse 1.6.3
attrs 23.2.0
cachetools 5.3.3
certifi 2024.2.2
charset-normalizer 3.3.2
click 8.1.7
cloudpickle 3.0.0
decorator 5.1.1
dm-tree 0.1.8
flatbuffers 24.3.25
gast 0.4.0
google-auth 2.29.0
google-auth-oauthlib 1.0.0
google-pasta 0.2.0
grpcio 1.62.2
h5py 3.11.0
idna 3.7
importlib-metadata 7.1.0
importlib-resources 6.4.0
jsonpatch 1.33
jsonpointer 2.4
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
keras 2.13.1
libclang 18.1.1
markdown 3.6
markupsafe 2.1.5
numpy 1.24.3
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 24.0
pkgutil-resolve-name 1.3.10
protobuf 4.25.3
pyasn1 0.6.0
pyasn1-modules 0.4.0
pyhf 0.7.1.dev238
pyyaml 6.0.1
referencing 0.35.0
requests 2.31.0
requests-oauthlib 2.0.0
rpds-py 0.18.0
rsa 4.9
scipy 1.10.1
setuptools 69.5.1
six 1.16.0
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
tqdm 4.66.2
typing-extensions 4.5.0
urllib3 2.2.1
werkzeug 3.0.2
wheel 0.43.0
wrapt 1.16.0
zipp 3.18.1
(.venv) root@edbb84aa61db:/pyhf# uv pip list | grep tensorflow
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(.venv) root@edbb84aa61db:/pyhf# python -c 'import tensorflow; import tensorflow_probability'
2024-04-30 07:08:21.163407: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-04-30 07:08:21.164774: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 07:08:21.192250: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 07:08:21.192613: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-04-30 07:08:23.284477: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
(.venv) root@edbb84aa61db:/pyhf#
uv-pip-install-tensorflow-command-line-verbose.txt
pip (success case):
$ docker run --rm -ti -v /tmp:/tmp python:3.8 /bin/bash
root@0c9ba727a892:/# python -m venv .venv && . .venv/bin/activate
(.venv) root@0c9ba727a892:/# python -m pip --quiet install --upgrade pip setuptools wheel
(.venv) root@0c9ba727a892:/# git clone --single-branch https://github.com/scikit-hep/pyhf.git && cd pyhf && git reset --hard 08755e45ed134cbe6e5e6e238b7b5011700080b3
(.venv) root@0c9ba727a892:/pyhf# python -m pip --verbose --no-cache-dir install --upgrade '.[tensorflow]' &> /tmp/python-pip-install-tensorflow-extra-verbose.txt
(.venv) root@0c9ba727a892:/pyhf# python -m pip list
Package Version
---------------------------- ------------
absl-py 2.1.0
astunparse 1.6.3
attrs 23.2.0
cachetools 5.3.3
certifi 2024.2.2
charset-normalizer 3.3.2
click 8.1.7
cloudpickle 3.0.0
decorator 5.1.1
dm-tree 0.1.8
flatbuffers 24.3.25
gast 0.4.0
google-auth 2.29.0
google-auth-oauthlib 1.0.0
google-pasta 0.2.0
grpcio 1.62.2
h5py 3.11.0
idna 3.7
importlib_metadata 7.1.0
importlib_resources 6.4.0
jsonpatch 1.33
jsonpointer 2.4
jsonschema 4.21.1
jsonschema-specifications 2023.12.1
keras 2.13.1
libclang 18.1.1
Markdown 3.6
MarkupSafe 2.1.5
numpy 1.24.3
oauthlib 3.2.2
opt-einsum 3.3.0
packaging 24.0
pip 24.0
pkgutil_resolve_name 1.3.10
protobuf 4.25.3
pyasn1 0.6.0
pyasn1_modules 0.4.0
pyhf 0.7.1.dev238
PyYAML 6.0.1
referencing 0.35.0
requests 2.31.0
requests-oauthlib 2.0.0
rpds-py 0.18.0
rsa 4.9
scipy 1.10.1
setuptools 69.5.1
six 1.16.0
tensorboard 2.13.0
tensorboard-data-server 0.7.2
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
termcolor 2.4.0
tqdm 4.66.2
typing_extensions 4.5.0
urllib3 2.2.1
Werkzeug 3.0.2
wheel 0.43.0
wrapt 1.16.0
zipp 3.18.1
(.venv) root@0c9ba727a892:/pyhf# python -m pip list | grep tensorflow
tensorflow 2.13.1
tensorflow-estimator 2.13.0
tensorflow-io-gcs-filesystem 0.34.0
tensorflow-probability 0.21.0
(.venv) root@0c9ba727a892:/pyhf# python -c 'import tensorflow; import tensorflow_probability'
2024-04-30 07:14:14.122645: I tensorflow/core/util/port.cc:110] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.
2024-04-30 07:14:14.124300: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 07:14:14.155920: I tensorflow/tsl/cuda/cudart_stub.cc:28] Could not find cuda drivers on your machine, GPU will not be used.
2024-04-30 07:14:14.156250: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.
To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.
2024-04-30 07:14:14.749372: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
(.venv) root@0c9ba727a892:/pyhf#
python-pip-install-tensorflow-extra-verbose.txt