I am trying to run this statement in MacOS.
conda install -c conda-forge tensorflow
It just stuck at the
Solving Environment:
Never finish.
$ conda --version
conda 4.5.12
Nothing worked untill i ran this in conda terminal:
conda upgrade conda
Note that this was for poppler (conda install -c conda-forge poppler)
On win10 I waited about 5-6 minutes but it depends of the number of installed python packages and your internet connection.
Also you can install it via Anaconda Navigator
One can also resolve the "Solving environment" issue by using the mamba package manager.
I installed tensorflow-gpu==2.6.2 on Linux (CentOS Stream 8) using the following commands
conda create --name deeplearning python=3.8
conda activate deeplearning
conda install -c conda-forge mamba
mamba install -c conda-forge tensorflow-gpu
To check the successful usage of GPU, simply run either of the commands
python -c "import tensorflow as tf;print('\n\n\n====================== \n GPU Devices: ',tf.config.list_physical_devices('GPU'), '\n======================')"
python -c "import tensorflow as tf;print('\n\n\n====================== \n', tf.reduce_sum(tf.random.normal([1000, 1000])), '\n======================' )"
References
Conda Forge blog post
mamba install instead of conda install
The same error happens with me .I've tried to install tensorboard with anaconda prompt but it was stuck on the environment solving .So i've added these paths to my environment variables:
C:\Anaconda3
C:\Anaconda3\Library\mingw-w64\bin
C:\Anaconda3\Library\usr\bin
C:\Anaconda3\Library\bin
C:\Anaconda3\Scripts
and it worked well.
Follow the instruction by nekomatic.
I left it running for 1 hour. Yes. it is finally finished.
But now I got the conflicts
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- anaconda==2018.12=py37_0 -> bleach==3.0.2=py37_0
- anaconda==2018.12=py37_0 -> html5lib==1.0.1=py37_0
- anaconda==2018.12=py37_0 -> numexpr==2.6.8=py37h7413580_0
- anaconda==2018.12=py37_0 -> scikit-learn==0.20.1=py37h27c97d8_0
- tensorflow
Use "conda info <package>" to see the dependencies for each package.
Related
On my Mac M1 (Monterey) I have created a new virtual environment with
virtualenv --python=/opt/homebrew/bin/python3.8 ~/.virtualenvs/datascience_env
to link it with specific Python 3.8 version. Now I'm trying to install tensorflow. The following command (issued in the virtual environment):
(datascience_env)% pip install tensorflow
causes the following error:
ERROR: Could not find a version that satisfies the requirement tensorflow (from versions: none)
ERROR: No matching distribution found for tensorflow
Just to be sure, I also did:
(datascience_env)% python -c "import sys; print(sys.version)" or python -c "import struct; print(struct.calcsize('P')*8)"
and the output confirms the 3.8 version:
3.8.14 (default, Sep 6 2022, 23:17:06)
[Clang 13.1.6 (clang-1316.0.21.2.5)]
I've finally opted for a simpler solution. I followed here the procedure to install Tensorflow on Mac M1 with miniforge. Works like a charm. In summary the steps are install miniforge, then:
conda config --set auto_activate_base false
conda create --name mytfenv python=3.8
conda activate mytfenv
conda install -c apple tensorflow-deps
pip install tensorflow-macos
pip install tensorflow-metal
conda install -c conda-forge -y pandas jupyter
I have been trying to install TensorFlow on my Macbook Air with a M1 chip.
Using Python 3.9.7.
Originally was on MacOS 11, but subsequently upgraded to 12.01
At first, I tried these instructions [https://towardsdatascience.com/installing-tensorflow-on-the-m1-mac-410bb36b776] but got stuck when trying to execute
pip3 install --upgrade --force --no-dependencies https://github.com/apple/tensorflow_macos/releases/download/v0.1alpha3/tensorflow_addons_macos-0.1a3-cp38-cp38-macosx_11_0_arm64.whl https://github.com/apple/tensorflow_macos/releases/download/v0.1alpha3/tensorflow_macos-0.1a3-cp38-cp38-macosx_11_0_arm64.whl
ERROR: tensorflow_addons_macos-0.1a3-cp38-cp38-macosx_11_0_arm64.whl is not a supported wheel on this platform.
So I tried to follow these instructions [https://www.tensorflow.org/install/source#macos_1] to compile TensorFlow, but when I try
bazel build //tensorflow/tools/pip_package:build_pip_package
I get these errors:
ERROR: /Users/scottbrown/tensorflow/tensorflow/lite/python/BUILD:62:10: Target '//tensorflow/lite/python:tflite_convert' depends on toolchain '#local_config_cc//:cc-compiler-darwin', which cannot be found: error loading package '#local_config_cc//': cannot load '#local_config_cc_toolchains//:osx_archs.bzl': no such file'
ERROR: Analysis of target '//tensorflow/tools/pip_package:build_pip_package' failed; build aborted: Analysis failed
When I try
pip3 install tensorflow-macos
I get this error:
Building wheel for h5py (pyproject.toml) ... error
ERROR: Command errored out with exit status 1:
command: /opt/homebrew/opt/python#3.9/bin/python3.9 /opt/homebrew/lib/python3.9/site-packages/pip/_vendor/pep517/in_process/_in_process.py build_wheel /var/folders/gz/28jpdfcd3b3g4pm7zl0wmrkh0000gn/T/tmpz_m057zj
cwd: /private/var/folders/gz/28jpdfcd3b3g4pm7zl0wmrkh0000gn/T/pip-install-kz29fkw2/h5py_0747e63c821445b6944ecb4fc6b2d1e1
I'm basing my answer on the article from Prabhat Kumar Sahu:
How to install Tensorflow on M1 Mac the easy way
Set up environment
Make sure you have homebrew, xcode, and miniforge installed.
create a virtual environment
conda create --name mlp python=3.8
activate environment
conda activate mlp
Install tensorflow for mac-os
(sets up the wheel files etc.)
conda install -c apple tensorflow-deps
pip install tensorflow-macos
pip install tensorflow-metal
That's it. You should have the environment all ready to go. Look at Prabhat's article for a sample Jupyter Notebook test for an example of how to benchmark/test your environment.
Hey guys I had the same issue but I fixed it with the following instructions :
NOTE: If using conda environment built against pre-macOS 11 SDK use:
SYSTEM_VERSION_COMPAT=0 python -m pip install tensorflow-macos
otherwise, you will get errors like: “not a supported wheel on this platform”
STEPS :
OS Requirements macOS 12.0+ (latest beta)
Currently Not Supported
Multi-GPU support
Acceleration for Intel GPUs
V1 TensorFlow Networks
Installation Instructions
Step 1: Environment setup
CPU TYPE x86: AMD
Create virtual environment (recommended):
python3 -m venv ~/tensorflow-metal
source ~/tensorflow-metal/bin/activate
python -m pip install -U pip
NOTE: python version 3.8 required
CPU TYPE : arm64 : Apple Silicon
Download and install Conda env:
chmod +x ~/Downloads/Miniforge3-MacOSX-arm64.sh
sh ~/Downloads/Miniforge3-MacOSX-arm64.sh
source ~/miniforge3/bin/activate
OR
conda env create --file=environment.yml --name tf_m1
and then activate tf_m1
Install the TensorFlow dependencies:
conda install -c apple tensorflow-deps
When upgrading to new base TensorFlow version, we recommend:
uninstall existing tensorflow-macos and tensorflow-metal
python -m pip uninstall tensorflow-macos
python -m pip uninstall tensorflow-metal
Upgrade tensorflow-deps
conda install -c apple tensorflow-deps --force-reinstall
or point to specific conda environment
conda install -c apple tensorflow-deps --force-reinstall -n my_env
tensorflow-deps versions are following base TensorFlow versions so:
For v2.5:
conda install -c apple tensorflow-deps==2.5.0
For v2.6:
conda install -c apple tensorflow-deps==2.6.0
NOTE: Python versions 3.8 and 3.9 supported
Step 2: Install base TensorFlow
python -m pip install tensorflow-macos
NOTE: If using conda environment built against pre-macOS 11 SDK use:
SYSTEM_VERSION_COMPAT=0 python -m pip install tensorflow-macos
otherwise you will get errors like: “not a supported wheel on this
platform
Step 3: Install tensorflow-metal plugin
python -m pip install tensorflow-metal
I am using Anaconda 3 and would like to install keras-tuner in the tensorflow environment.
I've tried
conda install -c conda-forge keras-tuner
in the Anaconda Prompt (see https://anaconda.org/conda-forge/keras-tuner) which worked fine. However, the package has been installed in the base environment (and not in the tensorflow environment).
How can I choose the environment in which I want to install keras-tuner?
I use tensorflow 2.1.0 on a Windows machine
There are multiple ways of doing it.
activating the target environment and running the same command.
You can install a conda package also without activating the environment. Just use
conda install -n <env_name> <package> or conda install -p <path/to/env> <package>
I'm using Miniconda 3, and I'm trying to build a minimal Conda environment containing pandas. However, when I try to load the pandas module, Jupyter gives me the following error:
The kernel appears to have died. It will restart automatically.
When doing the same thing via Python in the Terminal, Python crashes.
I have created a minimal Conda environment, which can be reproduced via the code below.
conda create -n testenv
conda activate testenv
conda install python
conda install pandas
conda install jupyter
The problem doesn't occur anymore when I follow up with a full Anaconda install, via conda install anaconda.
Any ideas as to how this problem can be resolved without installing Anaconda?
I figured out what the problem was. What I should have mentioned is that I built a global channel list according to Bioconda recommendation, using
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
This makes conda-forge the highest-priority channel. For reasons I don't understand, conda-forge builds a dependency hell. (I noticed the guys at conda-forge: https://github.com/conda-forge/pandas-feedstock/issues/63).
For now, install using conda install -c defaults pandas.
This is the error :
Solving environment: failed
UnsatisfiableError: The following specifications were found to be in conflict:
- numba -> numpy[version='>=1.14,<1.15.0a0']
- tensorflow
Use "conda info " to see the dependencies for each package.
You have to run the conda info tensorflow and conda info numba to see each dependencies for each package and then you have to install those package like conda install package=version to fix the problem.
First create a conda environment if you would like using
conda create -n my_env python=3.6
Here "my_env" is the name of my environment
Then activate your environment using
source activate my_env #(for mac)
conda activate my_env #(for windows)
Once the Environment is active. you can now install the packages you need as follows:I am showing you the packages which i work upon on virtual environment and this will take care of most of your dependencies
conda update conda
conda upgrade conda
conda upgrade anaconda
conda update numpy
conda install tensorflow
Hope this will solve your problem or else try to upgrade numpy using pip:
pip install --upgrade numpy