I want to install tensorflow-text with version of 2.8.x.
First when I use:
pip install tensorflow-text',
I can only installed the version of 2.6.x.
And then when I use:
pip install -U "tensorflow-text==2.8.*" ,
it said that:
ERROR: Could not find a version that satisfies the requirement
tensorflow-text==2.8.* (from versions: 0.1.0rc2, 0.1.0, 1.0.0b2,
1.15.0rc0, 1.15.1, 2.0.0rc0, 2.0.1, 2.1.0rc0, 2.2.0rc2, 2.2.0, 2.2.1, 2.3.0rc1, 2.3.0, 2.4.0b0, 2.4.0rc0, 2.4.0rc1, 2.4.1, 2.4.2, 2.4.3, 2.5.0rc0, 2.5.0, 2.6.0rc0, 2.6.0) ERROR: No matching distribution found for tensorflow-text==2.8.*
Related
I am using a MacBook Pro M1 and try to install the package dmol-book, which has tensorflow-dependency, via pip3 install dmol-book==1.3.2 .
It throws the following error:
ERROR: Ignored the following versions that require a different python version: 1.0.1 Requires-Python >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3,!=3.4.*,<3.9; 1.1.0 Requires-Python >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,<3.9; 1.1.1 Requires-Python >=2.7,!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,<3.9
ERROR: Could not find a version that satisfies the requirement tensorflow>=2.7 (from dmol-book) (from versions: none)
ERROR: No matching distribution found for tensorflow>=2.7
I have installed tensorflow via
pip3 install tensorflow-macos
pip3 install tensorflow-metal
I can use tensorflow within python3:
>>> import tensorflow
>>> tensorflow.__version__
'2.11.0'
>>> tensorflow.__file__
'/Users/username/.pyenv/versions/3.10.7/envs/venv/lib/python3.10/site-packages/tensorflow/__init__.py'
but pip3 list does not list tensorflow, only
tensorboard 2.11.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.8.1
tensorboardX 2.5.1
tensorflow-estimator 2.11.0
tensorflow-macos 2.11.0
tensorflow-metal 0.7.0
tensorstore 0.1.28
tensorflow also shows up as a directory in the original virtual environment directory, that I created:
/Users/username/pathtovirtualenv/venv/lib/python3.10/site-packages/tensorflow
Can someone help me to resolve this issue?
Thanks in advance!
I think its because it does not find a version that satisfies the requirement as mentioned.
Colab does not allow to downgrade TensorFlow and says that only versions 2 is available.
here is code and output:
!pip install tensorflow-gpu==1.15.2
import tensorflow as tf
print(tf.__version__)
output:
Looking in indexes: https://pypi.org/simple, https://us-python.pkg.dev/colab-wheels/public/simple/
ERROR: Could not find a version that satisfies the requirement tensorflow-gpu==1.15.2 (from versions: 2.2.0, 2.2.1, 2.2.2, 2.2.3, 2.3.0, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.0, 2.4.1, 2.4.2, 2.4.3, 2.4.4, 2.5.0, 2.5.1, 2.5.2, 2.5.3, 2.6.0, 2.6.1, 2.6.2, 2.6.3, 2.6.4, 2.6.5, 2.7.0rc0, 2.7.0rc1, 2.7.0, 2.7.1, 2.7.2, 2.7.3, 2.7.4, 2.8.0rc0, 2.8.0rc1, 2.8.0, 2.8.1, 2.8.2, 2.8.3, 2.8.4, 2.9.0rc0, 2.9.0rc1, 2.9.0rc2, 2.9.0, 2.9.1, 2.9.2, 2.9.3, 2.10.0rc0, 2.10.0rc1, 2.10.0rc2, 2.10.0rc3, 2.10.0, 2.10.1, 2.11.0rc0, 2.11.0rc1, 2.11.0rc2, 2.11.0)
ERROR: No matching distribution found for tensorflow-gpu==1.15.2
2.9.2
I tried this code by creating some new projects in Colab but I got no new results
To downgrade tensorflow in google colab you must downgrade the version of python because python3.8 is not compatible with tensorflow1.x. So, Downgrade the version of python to python3.7 and install tensorflow1.x. This will work.
1.At first, Install python==3.7 version.
!sudo apt-get update -y
!sudo apt-get install python3.7
#change alternatives
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.8 1
!sudo update-alternatives --install /usr/bin/python3 python3 /usr/bin/python3.7 2
#check python version
!python --version
The above code will install python3.7 version, but it is not mapped to colab kernel, so we must map newly installed python.
# install pip for python==3.7
!sudo apt-get install python3.7-distutils
!wget https://bootstrap.pypa.io/get-pip.py
!python get-pip.py
# install colab dependencies
!python -m pip install ipython ipython_genutils ipykernel jupyter_console prompt_toolkit httplib2 astor
# link to the old google package
!ln -s /usr/local/lib/python3.8/dist-packages/google \
/usr/local/lib/python3.7/dist-packages/google
Let's check version of python again, it will be python==3.7.16:
!python --version
Now, it's time to install tensorflow 1.x.
!pip install tensorflow==1.x
I hope that it will help to fix your issue.Thank you!
I have been finished install Tensorflow env step by step from "https://developer.apple.com/metal/tensorflow-plugin/"
Tf is working!numpy is working! scipy is working!
but when i import sklearn package, have an error message like this:
ImportError: dlopen(/Users/mecilmeng/miniforge3/envs/tf/lib/python3.9/site-packages/scipy/spatial/qhull.cpython-39-darwin.so, 0x0002): Library not loaded: #rpath/liblapack.3.dylib
Referenced from: /Users/mecilmeng/miniforge3/envs/tf/lib/python3.9/site-packages/scipy/spatial/qhull.cpython-39-darwin.so
Reason: tried: '/Users/mecilmeng/miniforge3/envs/tf/lib/liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/lib/liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/lib/python3.9/site-packages/scipy/spatial/../../../../liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/lib/liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/lib/liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/lib/python3.9/site-packages/scipy/spatial/../../../../liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/bin/../lib/liblapack.3.dylib' (no such file), '/Users/mecilmeng/miniforge3/envs/tf/bin/../lib/liblapack.3.dylib' (no such file), '/usr/local/lib/liblapack.3.dylib' (no such file), '/usr/lib/liblapack.3.dylib' (no such file)
How to fix it?
pip list
Package Version
------------------------ -------------------
absl-py 0.10.0
aiohttp 3.8.1
aiosignal 1.2.0
anyio 3.5.0
appnope 0.1.2
argon2-cffi 20.1.0
astunparse 1.6.3
async-generator 1.10
async-timeout 4.0.1
attrs 21.4.0
Babel 2.9.1
backcall 0.2.0
beniget 0.3.0
bleach 4.1.0
blinker 1.4
Bottleneck 1.3.2
brotlipy 0.7.0
cached-property 1.5.2
cachetools 4.2.2
certifi 2021.10.8
cffi 1.15.0
charset-normalizer 2.0.4
click 8.0.3
cryptography 3.4.7
cycler 0.11.0
Cython 0.29.28
debugpy 1.5.1
decorator 5.1.1
defusedxml 0.7.1
dill 0.3.4
entrypoints 0.3
flatbuffers 2.0
fonttools 4.25.0
frozenlist 1.2.0
gast 0.4.0
google-auth 1.33.0
google-auth-oauthlib 0.4.1
google-pasta 0.2.0
googleapis-common-protos 1.54.0
grpcio 1.42.0
h5py 3.1.0
idna 3.3
importlib-metadata 4.8.2
ipykernel 6.4.1
ipython 7.31.1
ipython-genutils 0.2.0
jedi 0.18.1
Jinja2 3.0.2
joblib 1.1.0
json5 0.9.6
jsonschema 3.2.0
jupyter-client 7.1.2
jupyter-core 4.9.1
jupyter-server 1.13.5
jupyterlab 3.2.1
jupyterlab-pygments 0.1.2
jupyterlab-server 2.10.3
keras 2.8.0
Keras-Preprocessing 1.1.2
kiwisolver 1.3.1
libclang 13.0.0
Markdown 3.3.4
MarkupSafe 2.0.1
matplotlib 3.5.0
matplotlib-inline 0.1.2
mistune 0.8.4
multidict 5.2.0
munkres 1.1.4
nbclassic 0.2.6
nbclient 0.5.3
nbconvert 6.3.0
nbformat 5.1.3
nest-asyncio 1.5.1
networkx 2.6.3
notebook 6.4.6
numexpr 2.8.1
numpy 1.22.2
oauthlib 3.1.1
opencv-python 4.5.5.62
opt-einsum 3.3.0
packaging 21.3
pandas 1.3.5
pandocfilters 1.5.0
parso 0.8.3
pexpect 4.8.0
pickleshare 0.7.5
Pillow 9.0.1
pip 21.2.4
ply 3.11
prometheus-client 0.13.1
promise 2.3
prompt-toolkit 3.0.20
protobuf 3.19.1
ptyprocess 0.7.0
pyasn1 0.4.8
pyasn1-modules 0.2.8
pybind11 2.9.1
pycparser 2.21
Pygments 2.11.2
PyJWT 2.1.0
pyOpenSSL 21.0.0
pyparsing 3.0.4
pyrsistent 0.18.0
PySocks 1.7.1
python-dateutil 2.8.2
pythran 0.9.11
pytz 2021.3
pyzmq 22.3.0
requests 2.27.1
requests-oauthlib 1.3.0
rsa 4.7.2
scikit-learn 1.0.2
scipy 1.7.1
Send2Trash 1.8.0
setuptools 58.0.4
six 1.15.0
sklearn 0.0
sniffio 1.2.0
tensorboard 2.8.0
tensorboard-data-server 0.6.1
tensorboard-plugin-wit 1.6.0
tensorflow-datasets 4.5.2
tensorflow-macos 2.8.0
tensorflow-metadata 1.6.0
tensorflow-metal 0.3.0
termcolor 1.1.0
terminado 0.13.1
testpath 0.5.0
tf-estimator-nightly 2.8.0.dev2021122109
threadpoolctl 2.2.0
tornado 6.1
tqdm 4.62.3
traitlets 5.1.1
typing-extensions 3.7.4.3
urllib3 1.26.8
wcwidth 0.2.5
webencodings 0.5.1
websocket-client 0.58.0
Werkzeug 2.0.2
wheel 0.35.1
wrapt 1.12.1
yarl 1.6.3
zipp 3.7.0
You can install using Rosetta2 Mode.
To work in Rosetta Mode:
If Rosetta 2 is not installed by default in your M1 Mac, then open the pre-installed Terminal app and run the following command:
/usr/sbin/softwareupdate --install-rosetta --agree-to-license
Rosetta allows us to use apps built for Mac with intel chip.
Several CLI tools do not have native versions built for the new M1 architecture.
Enabling them on your native M1 Mac terminal can be frustrating.
Follow these steps to enable Rosetta:
Select the app(Terminal) in the Finder.
Right click on the app(Terminal) and select Get Info.
In General, check the Open using Rosetta check-box.
Close the Terminal Info.
Now when you quit the terminal and open it again.
If you haven't installed Rosetta yet, then it would prompt you to install it.
If the popup shows up, then click on Install button, then enter your user name and password to allow installation to proceed.
Close the Terminal and open again.
Now we have a special terminal that can install tools with Rosetta translation.
To verify that you are using a Rosetta terminal, run the following command and it should output i386:
arch
The native terminal without Rosetta would output arm64 for the above command.
Moving forward, all commands we ask you to execute should be done in Rosetta enabled terminal.
Uninstall arm64 brew
If you have installed brew in the past from the native terminal, it is likely that you have an arm64 build of brew. Having two different builds of brew can cause major problems as the packages with different builds will not be compatible with each other.
To avoid this problem you need to uninstall your current installation of arm64 brew.
You can check which build you have by running the following command:
which brew
If your installation of brew is the Intel build, then the command should output /usr/local/bin/brew. If that is the case you can skip installing brew and just update your current installation by running brew update.
If your output is /opt/homebrew then your installation of brew is the arm64 build.
You need to uninstall the arm64 build of brew by running the following command from the native terminal:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/uninstall.sh)"
Install Intel brew
Install Homebrew, which is the package manager:
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
Once done, run the below command to ensure that we make use of the HEAD revision:
git -C $(brew --repository homebrew/core) checkout master
Now verify the installation of the brew command:
which brew
The command should output /usr/local/bin/brew, which is the expected path.
In Colab notebook, I did:
!pip install pandas==1.4.1
but returned:
ERROR: Could not find a version that satisfies the requirement pandas==1.4.1 (from versions: 0.1, 0.2, 0.3.0, 0.4.0, 0.4.1, 0.4.2, 0.4.3, 0.5.0, 0.6.0, 0.6.1, 0.7.0, 0.7.1, 0.7.2, 0.7.3, 0.8.0, 0.8.1, 0.9.0, 0.9.1, 0.10.0, 0.10.1, 0.11.0, 0.12.0, 0.13.0, 0.13.1, 0.14.0, 0.14.1, 0.15.0, 0.15.1, 0.15.2, 0.16.0, 0.16.1, 0.16.2, 0.17.0, 0.17.1, 0.18.0, 0.18.1, 0.19.0, 0.19.1, 0.19.2, 0.20.0, 0.20.1, 0.20.2, 0.20.3, 0.21.0, 0.21.1, 0.22.0, 0.23.0, 0.23.1, 0.23.2, 0.23.3, 0.23.4, 0.24.0, 0.24.1, 0.24.2, 0.25.0, 0.25.1, 0.25.2, 0.25.3, 1.0.0, 1.0.1, 1.0.2, 1.0.3, 1.0.4, 1.0.5, 1.1.0, 1.1.1, 1.1.2, 1.1.3, 1.1.4, 1.1.5, 1.2.0, 1.2.1, 1.2.2, 1.2.3, 1.2.4, 1.2.5, 1.3.0, 1.3.1, 1.3.2, 1.3.3, 1.3.4, 1.3.5)
ERROR: No matching distribution found for pandas==1.4.1
Any idea how to upgrade to pandas==1.4.1 in colab?
pandas 1.4+ requires Python >= 3.8. From the list of available versions I can guess you use Python 3.7 or lower.
Upgrade Python or use lower version of pandas. Just pip install pandas should find compatible version.
I'm going over these example from google-cloud Coursera courses, and although they worked till a few weeks ago, I can't install tf.transform or apache_beam on Datalab anymore.
https://github.com/GoogleCloudPlatform/training-data-analyst/blob/master/courses/machine_learning/feateng/tftransform.ipynb
https://github.com/GoogleCloudPlatform/training-data-analyst/blob/master/courses/machine_learning/deepdive/06_structured/4_preproc_tft.ipynb
When installing tensorflow_transform I get the following errors:
%bash
pip install --upgrade --force tensorflow_transform==0.6.0
twisted 18.7.0 requires PyHamcrest>=1.9.0, which is not installed.
datalab 1.1.3 has requirement six==1.10.0, but you'll have six 1.11.0 which is incompatible.
gapic-google-cloud-pubsub-v1 0.15.4 has requirement oauth2client<4.0dev,>=2.0.0, but you'll have oauth2client 4.1.2 which is incompatible.
proto-google-cloud-pubsub-v1 0.15.4 has requirement oauth2client<4.0dev,>=2.0.0, but you'll have oauth2client 4.1.2 which is incompatible.
apache-airflow 1.9.0 has requirement bleach==2.1.2, but you'll have bleach 1.5.0 which is incompatible.
apache-airflow 1.9.0 has requirement funcsigs==1.0.0, but you'll have funcsigs 1.0.2 which is incompatible.
google-cloud-monitoring 0.28.0 has requirement google-cloud-core<0.29dev,>=0.28.0, but you'll have google-cloud-core 0.25.0 which is incompatible.
proto-google-cloud-datastore-v1 0.90.4 has requirement oauth2client<4.0dev,>=2.0.0, but you'll have oauth2client 4.1.2 which is incompatible.
pandas-gbq 0.3.0 has requirement google-cloud-bigquery>=0.28.0, but you'll have google-cloud-bigquery 0.25.0 which is incompatible.
googledatastore 7.0.1 has requirement httplib2<0.10,>=0.9.1, but you'll have httplib2 0.11.3 which is incompatible.
googledatastore 7.0.1 has requirement oauth2client<4.0.0,>=2.0.1, but you'll have oauth2client 4.1.2 which is incompatible.
Cannot uninstall 'dill'. It is a distutils installed project and thus we cannot accurately determine which files belong to it which would lead to only a partial uninstall.
The tensorflow version on my Datalab instance was 1.4.
I had to add this one line of code to update tensorflow to 1.10.1
%bash
pip install --upgrade --force-reinstall pip==10.0.1
pip install tensorflow==1.10.1
pip install tensorflow_transform
my environment:
apache-airflow==1.9.0
apache-beam==2.6.0
tensorflow==1.10.1
tensorflow-metadata==0.9.0
tensorflow-tensorboard==0.4.0rc3
tensorflow-transform==0.8.0
The current version of Datalab uses TensorFlow 1.8, so please change the notebook cell in question to:
%bash
pip uninstall -y google-cloud-dataflow
pip install --upgrade --force tensorflow_transform==0.8.0 apache-beam[gcp]
I've updated and checked in the two notebooks linked above.
Another problem might be that you are using Python 2. Datalab by default now uses Python 3 and your pip install (above) happens in Python 3 even if the kernel is Python 2 because %%bash opens up a new shell in which the conda activate of Python 2 has not happened.
To make sure the pip install happens in Python 2, change your pip install of apache-beam[gcp] as follows:
%%bash
source activate py2env
conda install -y dill pytz # do this for all the distutils complaints
pip uninstall -y google-cloud-dataflow
pip install --upgrade --force tensorflow_transform==0.8.0 apache-beam[gcp]