I created a conda environment including Spyder and tensorflow in the dependencies and all installs went without errors.
When I activate the environment and launch python, I can import tensorflow and run code without any issues.
However when launching spyder from within the environment (Spyder shows on the bottom of the GUI that is part of that conda environment), and load tensorflow, it throws an error:
ModuleNotFoundError: No module named 'tensorflow_core.estimator'
and from then the Console gets stuck repeating the same error.
Why does spyder have issues importing a module that python in the same environment can import? How can I fix this?
I have tried re-installing spyder in the conda environment but the same issue prevails.
Try to uninstall tensorflow-estimator pip uninstall tensorflow-estimator and uninstall Tensorflow.
#After fresh installing tensorflow
pip install tensorflow
#Install tensorflow_estimator
pip install -U tensorflow_estimator
Try this workaround as well.
The tensorflow is installed by using "conda install tensorflow". by importing tensorflow with "import tensorflow" in spyder in same environment which tensorflow was installed, it give an error "ModuleNotFoundError: No module named 'tensorflow'".
For every one who is faced with this problem i suggest to check if they have already installed spyder in desired environment with "conda install spyder". I installed it and the problem fixed
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 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.
How do I install TensorFlow's tensorboard?
The steps to install Tensorflow are here: https://www.tensorflow.org/install/
For example, on Linux for CPU-only (no GPU), you would type this command:
pip install -U pip
pip install tensorflow
Since TensorFlow depends on TensorBoard, running the following command should not be necessary:
pip install tensorboard
Try typing which tensorboard in your terminal. It should exist if you installed with pip as mentioned in the tensorboard README (although the documentation doesn't tell you that you can now launch tensorboard without doing anything else).
You need to give it a log directory. If you are in the directory where you saved your graph, you can launch it from your terminal with something like:
tensorboard --logdir .
or more generally:
tensorboard --logdir /path/to/log/directory
for any log directory.
Then open your favorite web browser and type in localhost:6006 to connect.
That should get you started. As for logging anything useful in your training process, you need to use the TensorFlow Summary API. You can also use the TensorBoard callback in Keras.
If your Tensorflow install is located here:
/usr/local/lib/python2.7/dist-packages/tensorflow
then the python command to launch Tensorboard is:
$ python /usr/local/lib/python2.7/dist-packages/tensorflow/tensorboard/tensorboard.py --logdir=/home/user/Documents/.../logdir
The installation from pip allows you to use:
$ tensorboard --logdir=/home/user/Documents/.../logdir
It may be helpful to make an alias for it.
Install and find your tensorboard location:
pip install tensorboard
pip show tensorboard
Add the following alias in .bashrc:
alias tensorboard='python pathShownByPip/tensorboard/main.py'
Open another terminal or run exec bash.
For Windows users, cd into pathShownByPip\tensorboard and run python main.py from there.
For Python 3.x, use pip3 instead of pip, and don't forget to use python3 in the alias.
TensorBoard isn't a separate component. TensorBoard comes packaged with TensorFlow.
Adding this just for the sake of completeness of this question (some questions may get closed as duplicate of this one).
I usually use user mode for pip ie. pip install --user even if instructions assume root mode. That way, my tensorboard installation was in ~/.local/bin/tensorboard, and it was not in my path (which shouldn't be ideal either). So I was not able to access it.
In this case, running
sudo ln -s ~/.local/bin/tensorboard /usr/bin
should fix it.
pip install tensorflow.tensorboard # install tensorboard
pip show tensorflow.tensorboard
# Location: c:\users\<name>\appdata\roaming\python\python35\site-packages
# now just run tensorboard as:
python c:\users\<name>\appdata\roaming\python\python35\site-packages\tensorboard\main.py --logdir=<logidr>
If you're using the anaconda distribution of Python, then simply do:
$❯ conda install -c conda-forge tensorboard
or
$❯ conda install -c anaconda tensorboard
Also, you can have a look at various builds by search the packages repo by:
$❯ anaconda search -t conda tensorboard
which would list the channels and the corresponding builds, the supported OS, Python versions etc.,
The pip package you are looking for is tensorflow-tensorboard developed by Google.
If you installed TensorFlow using pip, then the location of TensorBoard can be retrieved by issuing the command which tensorboard on the terminal. You can then edit the TensorBoard file, if necessary.
It is better not to mix up the virtual environments or perform installation on the root directory. Steps I took for hassle free installation are as below. I used conda for installing all my dependencies instead of pip. I'm answering with extra details, because when I tried to install tensor board and tensor flow on my root env, it messed up.
Create a virtual env
conda create --name my_env python=3.6
Activate virtual environment
source activate my_env
Install basic required modules
conda install pandas
conda install tensorflow
Install tensor board
conda install -c condo-forge tensor board
Hope that helps
I have a local install of tensorflow 1.15.0 (with tensorboard obviously included) on MacOS.
For me, the path to the relevant file within my user directory is Library/Python/3.7/lib/python/site-packages/tensorboard/main.py. So, which does not work for me, but you have to look for the file named main.py, which is weird since it apparently is named something else for other users.