I am trying to install tensorflow in anaconda with python 2.7 in Win10, by conda installation:
conda install -c conda-forge tensorflow=1.1.0
Then, I get the error message:
- python 2.7*
- tensorflow 1.1.0* -> python 3.5*
Use 'conda info <package>' to see the dependencies for each package.
Does the message mean I need to use python 3.5?
Yes.
TensorFlow only supports version 3.5.x of Python on Windows. Note that Python 3.5.x comes with the pip3 package manager, which is the program you'll use to install TensorFlow.
There are instructions for installing TF with Anaconda on Win10 on that page.
Related
Since I'm moving away from pandas DataFrames to TensorFlow datasets, I'd like to use tensorflow-data-validation instead of the more traditional pandas-profiling when it comes to data exploration and validation.
However, pip install tensorflow-data-validation gives the following error:
ERROR: Could not find a version that satisfies the requirement tensorflow-data-validation (from versions: none)
ERROR: No matching distribution found for tensorflow-data-validation
What could be the problem? This old GitHub issue explains how this could be due to the Python version, but Apache Beam (on which tensorflow-data-validation presumably relies) is now fully compatible with Python 3, so it must be something else.
My environment is as follows:
Python 3.9.2
TensorFlow 2.6.0
Debian GNU/Linux 11 (bullseye)
pip 21.3
I got the same error when using Python 3.9. After downgrading to Python 3.8, pip install tensorflow-data-validation ran successfully.
Regarding your comment about Apache Beam, it looks like the Python SDK currently supports Python 3.8 (and earlier) but not yet Python 3.9.
My environment:
Python 3.8.10
TensorFlow 2.8.0
macOS Monterey (12.0.1)
pip 21.1.1
Try this
pip install --upgrade --force-reinstall tensorflow-data-validation[all]
It might be a version compatibility issue with tensorflow==2.6.0.
Try
pip install tensorflow-data-validation==1.3.0
I was able to install the tensorflow_data_validation library successfully, via the below command in my Google Colab file.
!pip install -U tensorflow \
tensorflow-data-validation \
apache-beam[gcp]
I am trying to install tensorflow-gpu 1.15 using Conda for an easy install of CUDA and cuDNN. The problem is that checking the compatibility chart of the official web I need python 3.6, CUDA 10.0 and cuDNN 7.4.
Searching the Conda rep via conda search cudnn it says that there isn't cuDNN 7.4. Is there any other way to install the required packages? Or maybe tensorflow 1.15 also works with other combinations of versions?
As a side note, python 3.6, tensorflow-gpu 1.15 and CUDA 10 install correctly, but it seems I can't use the GPU correctly without cuDNN.
I just recently started using Conda, so maybe there is a straight forward way to do this that I don't realize. My Conda version is 4.9.1 (miniconda version).
---update---
Just in case I add the error while trying conda create -n myenv -c conda-forge tensorflow-gpu=1.15:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found to be incompatible with each other:
Output in format: Requested package -> Available versions
Package _tflow_select conflicts for:
_tflow_select==2.1.0=gpu
tensorflow==1.15.0 -> _tflow_select[version='2.1.0|2.3.0|2.2.0',build='gpu|mkl|eigen']
Note that strict channel priority may have removed packages required for satisfiability.
I am not sure if that is the problem, but I installed the following way
conda create -n tensorflow1.15 python=3.5
conda activate tensorflow1.15
conda install cudatoolkit=10.0
conda install cudnn=7.3.1
pip3 install tensorflow-gpu==1.15
And it seems to works perfectly with the GPU. I didn't know that cuDNN 7.3.1 worked like 7.4. The best way is to install tensorflow with conda, but it give me an error of trying to install tensorflow-gpu=2.X.
Also maybe it's interesting to say that you can search CUDA and similar official installers with conda search -c nvidia <packageName>.
I would let conda handle all the dependencies itself by installing tensorflow via conda, not pip. The GPU version of tensorflow is available e.g. in the popular conda-forge channel:
conda create -n myenv -c conda-forge tensorflow-gpu=1.15
The best setup for TensorFlow 1.15 is to follow this guide here: https://tensorflow-object-detection-api-tutorial.readthedocs.io/en/tensorflow-1.14/install.html#tf-install. The CUDA version which is recommended is 10.0 and the cudNN version 7.6.5
Attention to the protobuf version which will be installed, if you execute the gpu version it's 4.21.1, but you have to rewrite it with the command: pip install --upgrade tensorflow-gpu==1.15 "protobuf<4.0". If you use the cpu version its recommended to use this version here:(https://github.com/protocolbuffers/protobuf/releases/tag/v3.4.0) to avoid errors.Just download the protoc-3.4.0-win32.zip (windows)
Hope that helps.
I recently installed python with the version 3.8.3 and upgraded pip to 20.1.1. According to enter link description here, conda install -c conda-forge tensorflow should work. However, I get this result
Solving environment: failed with repodata from current_repodata.json, will retry with next repodata source.
Collecting package metadata (repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed
UnsatisfiableError: The following specifications were found
to be incompatible with the existing python installation in your environment:
Specifications:
- tensorflow -> python[version='3.5.*|3.6.*|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|>=3.7,<3.8.0a0|3.7.*']
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.
since I use
(base) C:\Users\ivan>python --version
Python 3.8.3
(base) C:\Users\ivan>pip --version
pip 20.1.1 from C:\Users\ivan\anaconda3\lib\site-packages\pip (python 3.8)
I wonder if it is possible to solve this issue without downgrading. For users of anaconda 2020.07, python 3.8 is used by default. Downgrading it will break anaconda.
People have reported problems using tensorflow with python 3.8, it is best to use 3.7. You are incorrect about breaking Anaconda. Here is what to do.
In Anaconda home page click on environments. At the bottom left of the page click on create. A window will appear. Give the new environment a name (say python3.7). In the drop down menu select 3.7. Now a new environment is created using python 3.7. Now in the conda terminal type conda activate python3.7. Then use conda to install tensorflow. It will install version 2.1.1, the cuda toolkit version 10.1.243 and cudnn version 7.6.5. Note conda can only install tensorflow up to version 2.1.1. If you want tensorflow 2.2 install it with pip using pip install tensorflow ==2.2.0. after you have installed 2.1. The cuda toolkit and cudnn work with version 2.2. Now use pip or conda to install any other packages you need in your python3.7 environment and you should be good to go!
I am trying to install "Tensorflow" on windows using conda environment.
Please note that -
I am installing tensorflow along with pytorch in the same environment.
I am getting "Remove Error": 'setuptools' is a dependency of conda and cannot be removed from
conda's operating environment.
I getting this error with both of these commands
pip install tensorflow
conda install tensorflow
A snap of the error can be seen below.
I sorted this issue by fixing the installation of the "httptools".
I recently found that many of the conda supports of have been migrated to conda forge.
HENCE, BEFORE INSTALLING THE TENSORFLOW. I INSTALLED THE "httptool" using the following command in the anaconda prompt.
conda install -c conda-forge httptools
Now everything works really fine.
I am trying to install Tensorflow and Horovod
pip install tensorflow
HOROVOD_WITH_TENSORFLOW=1 pip install horovod
Then I ran a sample code
import tensorflow as tf
import horovod.tensorflow as hvd
When I run this code, I get the error
ImportError: Extension horovod.tensorflow has not been built. If this is not expected, reinstall Horovod with HOROVOD_WITH_TENSORFLOW=1 to debug the build error.
If you need to install tensorflow and horovod , you can use the following steps:
1)Create a conda environment to avoid the mismatch of package versions.
conda create -n test_hvd -c intel python=3.6
2)Activate the environment
source activate test_hvd
(You can use any name instead of test_hvd, which is an environment name.)
3)Install tensorflow in the activated environment:
pip install https://storage.googleapis.com/intel-optimized-tensorflow/tensorflow-1.10.0-cp36-cp36m-linux_x86_64.whl
4)Finally install horovod
pip install --no-cache-dir horovod
Note: 1. Kindly confirm if you are using the latest versions of GCC (gcc (GCC) 6.4.0 works fine).
These steps are tested on Linux OS
Hope this helps!