Reputation: 852
I would like to install the libaray Keras for machine learning in Python (https://keras.io/). I use Anaconda (as an Administrator) and I tried the following command.
(base) C:\Users\wi9632>conda install keras
And here is the output with the error message:
Collecting package metadata (current_repodata.json): done
Solving environment: failed with initial frozen solve. Retrying with flexible solve.
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:
- keras -> python[version='>=3.5,<3.6.0a0|>=3.6,<3.7.0a0']
Your python: python=3.8.5
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.
Can you tell me what I have to do in order to install Keras? If I understand correctly, the version of my Python environment is to new? I'd appreciate every comment.
Does nobody have an idea what I can do? I'd be quite happy about it.
Update: I tried it by using the command:
conda install -c conda-forge keras (see https://anaconda.org/conda-forge/keras) and I tried to install the packages by using the GUI of Anaconda. Both yielded the same error message.
Upvotes: 1
Views: 9473
Reputation: 568
The problem seems to be with conda
rather than with keras
, see here. Using pip
instead of conda
might resolve your problem.
However, I'd discourage using keras
anyway as now using tf.keras
is the recommended way of working with Keras, see here:
Keras 2.3.0 is the first release of multi-backend Keras that supports TensorFlow 2.0. It maintains compatibility with TensorFlow 1.14, 1.13, as well as Theano and CNTK.
This release brings the API in sync with the tf.keras API as of TensorFlow 2.0. However note that it does not support most TensorFlow 2.0 features, in particular eager execution. If you need these features, use tf.keras.
This is also the last major release of multi-backend Keras. Going forward, we recommend that users consider switching their Keras code to tf.keras in TensorFlow 2.0.
So if conda install tensorflow
works for you, just replace any appearance of keras
with tf.keras
in your code. This way, there is no need to install keras
separately.
Upvotes: 3