I am trying to install tensorflow-text through miniconda in Spyder. I have managed to install other modules in Spyder such as tensorflow itself, pandas, scikit-learn, etc. However, using the same command as all the other installations (with the specific package name replaced by tensorflow-text)
conda install spyder-kernels tensorflow-text -y
I continue to get the same error whenever I try to install tensorflow-text:
PackagesNotFoundError: The following packages are not available from current channels:
- tensorflow-text
followed by a suggestion to search for the package on anaconda.org. As such, I searched for the tensorflow-text package on the anaconda site and found one, albeit for linux, by rocketce. Attempting to run the commands listed under the tensorflow-text installation instructions on that webpage also yielded the same error.
At first, I tried to install tensorflow-text through pip and was able to successfully run the command
pip install -U tensorflow-text==2.10.0
which seemed to install tensorflow-text. But I could not figure out how to access it or if it was correctly installed. Specifically, I am looking to use tensorflow-text in the Spyder IDE. I was able to get tensorflow working in the IDE, but not the specific tensorflow-text.
I am using a Windows 10 system; I could not find anything on the anaconda site for Windows 10. I am rather inexperienced (if you could not already tell from the nature and description of the problem), so patience and clear explanations are appreciated. Thanks in advance!
I am trying to implement the XLNET on Google Collaboratory. But I get the following issue.
ImportError:
XLNetTokenizer requires the SentencePiece library but it was not found in your environment. Checkout the instructions on the
installation page of its repo: https://github.com/google/sentencepiece#installation and follow the ones
that match your environment.
I have also tried the following steps:
!pip install -U transformers
!pip install sentencepiece
from transformers import XLNetTokenizer
tokenizer = XLNetTokenizer.from_pretrained('xlnet-base-cased-spiece.model')
Thank you for your help in advance.
After the
!pip install transformers and
!pip install sentencepiece
please restart your runtime and then execute all other codes.
I got the same error in google colab. Restarting the runtime did it for me.
I am looking to download Gurobi in python but when I follow gurobi's instructions to do so, I get this error.
Python installation directory (hit ENTER to use c:\Python27):
The system cannot find the path specified.
[Hit ENTER to exit]
Please let me know if anyone has recently done this and can share some insight.
How exactly did you "download Gurobi in Python"? You can either install it via Anaconda:
conda config --add channels http://conda.anaconda.org/gurobi
conda install gurobi
Or you can start up any Python environment and run this from within the GUROBI_HOME installation directory:
python setup.py install
Check out this guide for more detailed instructions.
I know google colaboratory doesn't yet support an R kernel. What about rmagic? Can I use rpy2?
I tried :
!pip install rpy2==2.8.6
And got :
Collecting rpy2==2.8.6
Using cached https://files.pythonhosted.org/packages/32/54/d102eec14f9cabd0df60682a38bd45c36169a1ec8fb8a690bf436cb6d758/rpy2-2.8.6.tar.gz
Complete output from command python setup.py egg_info:
Error: Tried to guess R's HOME but no command 'R' in the PATH.
----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in /tmp/pip-install-3bSiiD/rpy2/
I'm guessing that it isn't working because R isn't installed on whatever cloud machine this notebook is running on, and that it probably isn't possible to install it. But I'm hoping I'm wrong and someone may know of a work around.
OK, I answered my own question. I thought for sure this would fail, but tried anyway:
!apt-get update
!apt-get install r-base
!pip install rpy2==2.8.6
And it worked!
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.