![]() ![]() When I run pipenv graph, however, I do see TensorFlow installed: tensorflow=2.4.1 I get the same error when I run the recommended pipenv lock -clear. Hint: try $ pipenv lock -pre if it is a pre-release dependency.ĮRROR: Could not find a version that matches tensorflow (from -r /var/folders/ym/2b7pw1yn0v71ybqwb07t4vw00000gn/T/pipenv_jovmhf7requirements/pipenv-f853nmkj-constraints.txt (line 2)) You likely have a mismatch in your sub-dependencies.įirst try clearing your dependency cache with $ pipenv lock -clear, then try the original command again.Īlternatively, you can use $ pipenv install -skip-lock to bypass this mechanism, then run $ pipenv graph to inspect the situation. : Warning: Your dependencies could not be resolved. : raise ResolutionFailure(message=str(e)) : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/utils.py", line 833, in resolve : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/utils.py", line 1108, in actually_resolve_deps : results, hashes, markers_lookup, resolver, skipped = actually_resolve_deps( : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/utils.py", line 1395, in resolve_deps : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/resolver.py", line 684, in resolve : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/resolver.py", line 702, in resolve_packages : resolve_packages(pre, clear, verbose, system, write, requirements_dir, packages, dev) : File "/Users//Library/Python/3.8/lib/python/site-packages/pipenv/resolver.py", line 741, in _main Pipfile.lock (73f34e) out of date, updating to (afb705). % pipenv install tensorflowĪdding tensorflow to Pipfile's. To activate this project's virtualenv, run pipenv shell.Īlternatively, run a command inside the virtualenv with pipenv run.īut it failed for TensorFlow. Installing dependencies from Pipfile.lock (73f34e). Virtualenv location: /Users//.local/share/virtualenvs/jupyter-l45QZahtĪdding jupyterlab to Pipfile's. ✔ Successfully created virtual environment! Seeder FromAppData(download=False, pip=bundle, setuptools=bundle, wheel=bundle, via=copy, app_data_dir=/Users//Library/Application Support/virtualenv)Īdded seed packages: pip=21.0.1, setuptools=52.0.0, wheel=0.36.2Īctivators BashActivator,CShellActivator,FishActivator,PowerShellActivator,PythonActivator,XonshActivator ⠦ Creating virtual environment.created virtual environment CPython3.8.2.final.0-64 in 410msĬreator CPython3macOsFramework(dest=/Users//.local/share/virtualenvs/jupyter-l45QZaht, clear=False, no_vcs_ignore=False, global=False) Using /usr/bin/python3 (3.8.2) to create virtualenv. % pipenv install jupyterlabĬreating a virtualenv for this project. Then try it by running pipenv, and it works. Over at, I follow their install command: % pip install -user pipenv When I reopen the terminal and run pip, it works as expected. This is strange, why does it say that it installed pip 21, then tells me I am using pip 19?Īnyway, to finish I add Python's bin folder to the path with vim. You should consider upgrading via the '/Applications/Xcode.app/Contents/Developer/usr/bin/python3 -m pip install -upgrade pip' command. WARNING: You are using pip version 19.2.3 however, version 21.0.1 is available. WARNING: The scripts pip, pip3 and pip3.8 are installed in '/Users//Library/Python/3.8/bin' which is not on PATH.Ĭonsider adding this directory to PATH or, if you prefer to suppress this warning, use -no-warn-script-location. ![]() Instead I had to run python3 get-pip.py: % python3 get-pip.pyĭefaulting to user installation because normal site-packages is not writeableĭownloading pip-21.0.1-p圓-none-any.whl (1.5 MB) However, running python get-pip.py returned this error: ERROR: This script does not work on Python 2.7 The minimum supported Python version is 3.6. ![]() ![]() Installing pipįirst I had to install pip. If you're interested, you can read my notes of how I ended up with this solution. 1.20.* is known to not play well with TensorFlow. The only difference is, it forces numpy to use 1.19.5 instead of 1.20.*. Instead of using the provided yml, you should use this yml: name: apple_tensorflow ![]()
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