For reference I am using conda 22.9.0, Python 3.9.13, scikit-learn 1.0.2 according to conda list and I am using Windows OS 64 bit.
The newest sklearn version it will acknowledge or allow me to have is v1.0.2.
Update: No error is displayed when I try to update via conda update scikit-learn, it simply says "# All requested packages already installed.".
Check if you have it installed or show the error message you get. You might wanna install it via conda install scikit-learn in your cmd
I installed the transformers in the Macbook Pro M1 Max
Following this, I installed the tokenizers with
pip install tokenizers
It showed
Collecting tokenizers
Using cached tokenizers-0.12.1-cp39-cp39-macosx_12_0_arm64.whl
Successfully installed tokenizers-0.12.1
It seems to use the correct architecture for the whl file
When I import it I get
'/Users/myname/miniforge3/envs/tf/lib/python3.9/site-packages/tokenizers/tokenizers.cpython-39-darwin.so' (mach-o file, but is an incompatible architecture (have 'x86_64', need 'arm64e'))
I see that this problem used to happen to others before. Any thoughts on how to fix this?
James Briggs method works but produces the following error
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for tokenizers
Failed to build tokenizers
ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects
The Issue
After installing Rust and Cargo, we must source the environment file. This is the missing step in the previous answer.
The Solution
The workaround to solving this is to type the following in the terminal, right after installing Rust:
source "$HOME/.cargo/env"
Then, you can install transformers with the following code snippet:
pip install transformers
If using Anaconda we switch to a terminal window and create a new ARM environment like so:
CONDA_SUBDIR=osx-arm64 conda create -n ml python=3.9 -c conda-forge
now get in to ml envoriment
conda activate ml
run inside the env
conda env config vars set CONDA_SUBDIR=osx-arm64
needs to restart env
conda deactivate
get into to env
conda activate ml
PyTorch Installation
To get started we need to install PyTorch v1.12. For now, this is only available as a nightly release.
pip3 install -U --pre torch torchvision torchaudio --extra-index-url https://download.pytorch.org/whl/nightly/cpu
Side note: The transformers library uses tokenizers built in Rust (it makes them faster). Because we are using this new ARM64 environment we may get ERROR: Failed building wheel for tokenizers. If so, we install Rust (in the same environment) with:
curl — proto ‘=https’ — tlsv1.2 -sSf https://sh.rustup.rs | sh
restart your env
conda deactivate
conda activate ml
than you can install transformer comes with tokenizers or only install tokenizers
pip install tokenizers or pip install transformer
thanks to James Briggs
You can try
conda install -c huggingface transformers
I got this error too. Solved it after a lot of trial & error.
The Problem: my brew was still running on Rosetta. Fixed that by uninstalling, cleaning and reinstalling. So everything seemed to run fine. Except this problem still kept cropping up
Until I discovered that pip is quite agressive in caching. So it caches the build even if the architecture changed. Solution: pip cache purge. Or remove the whole cache directory which you find with pip cache info
After testing most of the solutions provided I finally got it working by doing
brew install ffmpeg
sudo pip install tokenizers
🛠️🚀
I have a problem with importing TensorFlow. I have tried multiple versions of Numpy, Python, and TensorFlow and I still get the following error:
struct_pb2.TypeSpecProto.NDARRAY_SPEC
AttributeError: NDARRAY_SPEC
I have tried using conda and pip for installation and neither one works. I have no idea what might be the cause of this problem and it started happening about a week ago before that TensorFlow was working fine!
I believe you are using windows, and you have an incompatible version of tensorflow installed or you are missing a dependency. First make sure you have the following installed correct version of Visual C++ installed for your version of windows.
https://support.microsoft.com/en-us/topic/the-latest-supported-visual-c-downloads-2647da03-1eea-4433-9aff-95f26a218cc0
https://aka.ms/vs/16/release/vc_redist.x64.exe here is the direct link.
If it still doesn't work, enable longpaths,
https://superuser.com/questions/1119883/windows-10-enable-ntfs-long-paths-policy-option-missing
If you are having a clash with other packages, create a new conda environment first if you haven't already, and install tensorflow like this.
conda create -n tfenv
conda activate tfenv
conda install tensorflow
Then try to import tensorflow as tf again.
Recently, I upgraded to Anaconda3 2020.07 which uses python 3.8. In past versions of anaconda, tensorflow was installed successfully. Tensorflow failed to be installed successfully in this version.
I ran the command below;
conda install tensorflow-gpu
The error message that I received is shown below;
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- tensorflow-gpu -> python[version='3.5.*|3.6.*|3.7.*|>=3.7,<3.8.0a0|>=3.6,<3.7.0a0|>=3.5,<3.6.0a0|>=2.7,<2.8.0a0']
Your python: python=3.8
If python is on the left-most side of the chain, that's the version you've asked for.
When python appears to the right, that indicates that the thing on the left is somehow
not available for the python version you are constrained to. Note that conda will not
change your python version to a different minor version unless you explicitly specify
that.
The following specifications were found to be incompatible with your CUDA driver:
- feature:/win-64::__cuda==11.0=0
Your installed CUDA driver is: 11.0
Is there a conda command with the right parameters to get tensorflow installed successfully?
UPDATE:
TF is now compatible with Python 3.8
Tensorflow is not compatible with Python 3.8. See https://www.tensorflow.org/install/pip
You need to downgrade your python version :
conda install python=3.7
Create an environment with python 3.7 and then activate it:
conda create -n p37env python=3.7
conda activate p37env
And install tensorflow.
This worked for me, and found out the answer from the Anaconda user guide (under how to use a different python version: https://conda.io/projects/conda/en/latest/user-guide/getting-started.html#managing-python )
From the requirement page:
Python 3.8 support requires TensorFlow 2.2 or later.
So there is a verison of Tensorflow compatible with python 3.8.
The problem is that TensorFlow 2.2.0 is not available through conda on Windows, this should be the reason why you get PackagesNotFoundError when running
conda install tensorflow=2.2
EDIT 15/03/21
Tensorflow 2.3.0 is compatible with Windows
i think we have two options here
pip install tensorflow
or we can use another env of anaconda such as like this below
conda create -n tf tensorflow pydotplus jupyter
conda activate tf
Actually you can directly use pip inside anaconda prompt, after I tested it, I found the conda is capable with pypi, first run the anaconda prompt with administrator permission (in windows), then enter "conda update --all" to make sure all the packages are latest, finally enter "pip install tensorflow" to install (the new version of tensorflow already includes tensorflow-gpu).
Then using VS code to open an ipynb and run
import tensorflow as tf
tf.test.gpu_device_name()
everything looks good.
For more info please refer to Anaconda official docs: https://docs.anaconda.com/anaconda/ .
Latest development for tensorflow installation on anaconda.
https://anaconda.org/anaconda/tensorflow
https://anaconda.org/anaconda/tensorflow-gpu
9 days ago, Anaconda uploaded a new tensorflow v2.3 package. Anaconda3 2020.07 (uses python v3.8) users can easily upgrade to tensorflow v2.3 with the following commands;
conda install -c anaconda tensorflow
conda install -c anaconda tensorflow-gpu
I have personally tested that the installation worked successfully.
The other answers for this question have now become obsolete.
Expanding upon William's answer here with more explicit instructions and caveats. Pip is the recommended way to install latest version of tensorflow as per tensorflow's installation instructions -- "While the TensorFlow provided pip package is recommended, a community-supported Anaconda package is available."
Here is the code that uses pip to do the installation in a Conda environment:
conda create -n env_name python=3.8
conda activate env_name
conda install pandas scikit-learn matplotlib notebook ##installing usual Data Science packages that does include numpy and scipy
pip install tensorflow
python -c "import tensorflow as tf;print(tf.__version__)" ##checks tf version
In general, we should be careful while mixing two package managers (conda and pip). So, it is suggested that:
Only after conda has been used to install as many packages as possible
should pip be used to install any remaining software. If modifications
are needed to the environment, it is best to create a new environment
rather than running conda after pip.
For an example, if we would like to install seaborn in the just created env_name environment, we should:
conda create --name cloned_env --clone env_name
conda activate cloned_env
conda install seaborn
Once we check the cloned_env environment is working fine, we can delete the env_name environment.
I was running into the same issue in conda prompt for Python 3.8.5 and fixed it using a Python wheel instead. Here are the steps:
Open conda prompt and install pip if you don't have it already: python -m pip install --upgrade pip
python -m pip install --upgrade https://storage.googleapis.com/tensorflow/windows/gpu/tensorflow_gpu-2.4.0-cp38-cp38-win_amd64.whl
Note: If you need a CPU specific tensorflow, use this wheel: https://storage.googleapis.com/tensorflow/windows/cpu/tensorflow_cpu-2.4.0-cp38-cp38-win_amd64.whl
I just downgraded python to 3.7 as tf is not avialable to 3.8 version also I cannot use virtualenv for code that's why
The only working answer for me is:
conda install -c conda-forge tensorflow
It appears that tensorflow 2.5 on GPU has issues with spyder. So, I made new environment and installed tensorflow gpu as suggested by anaconda. Now I have to use either prompt or jupyter . At least it works
For macos users I suggest create an environment with python 3.7 and install tensorflow there.
You can run these commands too:
conda create -n new_env_name python=3.7
conda activate new_env_name
I had a similar problem in Anaconda Spyder. Here was my solution (In the Anaconda Console):
conda install pip
pip install tensorflow ==2.2.0
I'm following instructions to create a Tensorflow environment for a Machine Learning course, with python 3.5, ipython and jupyter.
I created a Tenserflow environment with python 3.5 using conda create -n tensorflow python=3.5. That worked.
Then I ran conda install -c conda-forge tensorflow. That also worked.
Then I installed ipython with conda install ipython, which also worked fine.
However, when I ran pip3 install jupyter, I got error message bash: pip3: command not found.
I found a few posts about variations on pip3 problems and (within the Tensorflow environment):
When I type pip --version, it tells me I have version 8.1.2
When I try locate pip3, I get WARNING: The locate database (/var/db/locate.database) does not exist
I tried using pip-3.2 as recommended in one of the other questions' solutions (which worked for that OP), and I get the same command not found error message.
I'm using OS X 10.8.5
pip is different from pip3. So you might need to install it if it can't be found. If it is installed run this:
sudo updatedb
this will update the locate function.
if you're using conda why do you want to install it with pip anyways?
Jupyter is the new version of ipython. running conda install ipython installs ipython (now jupyter).