I am currently working on project,where I use pytorch as deep learning environment. I have serious problem, that .... "When I use anaconda jupyter notebook terminal to run my *.py files. Then, it run properly. But, when I use the same environment within vs-code via python_interpretor, I can not get result and give me error "torch module can not found".
Can anyone have solution?. Actually, I see the packages using "conda list" and it includes torchvision inside environment. I also tried to install torch in base environment But, it does not work.
Please give me some solution. Thank you for your consideration.
Related
I am on Ubuntu 20.04 and have both Python2 and Python3 installed natively. I have also installed Python through miniforge, a variant of miniconda. In VSCode I have both the MS Python extension and Pylance installed.
I use the miniforge python for my coding. This works perfectly fine in PyCharm.
However in VSCode, when I try to execute the same file I get errors. After investigating it seems that VSCode is picking native Python2 - even though I have the miniforge Python selected. In this picture it can be seen that the status bar at the bottom states Python interpreter selected is Python3. But the output window shows that the python interpreter is Python2.
A more confusing thing is when I use VSCode for Jupyter notebook files then it picks up the interpreter correctly and I have no issues.
I have checked both User and Workspace settings, and they all point to Python3. How can I fix this for standard .py files?
I prefer VSCode to PyCharm, but will need to use PyCharm till this is resolved.
It seems that your system console cannot see python3. You need to put the python3 in the PATH variable, before python2. Like:
PATH=path/to/python3:path/to/python2:$PATH
Also, make sure that the environment containing python3 is activated before command prompt appears. It can be done in bash_profile by adding a line like
conda activate my_env_with_python3
Try changing the settings "Python:Python path", "Python:default interpreter path" and "Python:conda path" also.
I have just bumped into something similar. The Run code option resulted in the file being run with the default interpreter instead of the venv-based one with necessary packages installed.
The fix was simply to use "Run python file" instead:
The run-code behavior must be customizable, something is mentioned e.g. here: Run Code vs Run Python File in Terminal for VSCODE but I didn't bother.
i installed simpleitk in anaconda using command
conda install -c simpleitk simpleitk then followed link https://github.com/SimpleITK/SimpleITKCondaRecipe to build it but it's not connecting to itk.org to build.
import SimpleITK as sitk on jupyter notebook is working but sitk.show() is not working. moreover when i tried to follow the commands from http://insightsoftwareconsortium.github.io/SimpleITK-Notebooks/Python_html/00_Setup.html,
from downloaddata import fetch_data, fetch_data_all not working.
even the command fetch_data_all(os.path.join('..','Data'), os.path.join('..','Data','manifest.json')) is not working. i am very new to simpleitk and don't know whether it is due to build not processed. please tell me how to solve my problems. i have been trying from many days, pl help me. moreover how to make imagej as default for simpleitk. i know lots of questions but i would be greatful if solved.
You seem to be having multiple problems, all of which have to do with installing a working environment and less specific to SimpleITK.
You installed SimpleITK using the conda install command, so there was no need to build it using the conda build command. Check that you have it installed correctly and see which version you have:
import SimpleITK as sitk
print(sitk.Version())
The functions fetch_data and fetch_data_all are part of a module found in the SimpleITK notebooks repository. To use the code from that repository you will need to clone it using git:
git clone https://github.com/InsightSoftwareConsortium/SimpleITK-Notebooks.git
Then you can run the notebooks or copy the relevant modules to your directory and work with them there.
The sitk.Show() command assumes that you have the ImageJ/Fiji program installed which is likely why it is not working (I am guessing here as you did not provide sufficient detail).
I followed these instructions:
http://ipython.org/install.html
Used last way to install (downloading source and "python setup.py install").
After that, console ipython worked fine, but trying to run notebook gave me error.
I always searched errors in Google and it always was a missing package.
Notebook probably depends on external packages.
After manually installing 2 packages it still gave me error.
Gave up and uninstalled everything (including Python itself).
Is there any way to manually download and install the notebook?
Do you know of any finite number of files/packages I have to download and install so the notebook will run just fine?
Thank you.
As you are using Windows, I suggest you to install Winpython.
It includes all the libraries and tools (e.g. IPython) you will need in the same executable. So you only need to download the desired version and then you can pass that version using a USB stick to the computer without internet.
I am running IPython Notebook on Enthought's Canopy 64 bit distribution, Ubuntu 14.04.
I've tried install libtiff, but when I import it in IPython Notebook, the kernel always dies at the import statement. What could possibly be causing this? Canopy is my default Python distribution, my paths all seem like they're set up appropriately, although I'm convinced that something in my Python setup is borked.
Any advice is appreciated.
EDIT: I'll be more specific. Output of sys.path:
['',
'/home/joe/Enthought/Canopy_64bit/User/src/svn',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python27.zip',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/plat-linux2',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/lib-tk',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/lib-old',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/lib-dynload',
'/home/joe/Enthought/Canopy_64bit/User/lib/python2.7/site-packages',
'/home/joe/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/PIL',
'/home/joe/opencv-2.4.9',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/site-packages',
'/home/joe/Canopy/appdata/canopy-1.4.1.1975.rh5-x86_64/lib/python2.7/site-packages/IPython/extensions']
As for how to install Python packages, I assume I go to ~/Enthought/Canopy_64bit/User/lib/python2.7/site-packages and run pip, setup.py, or a shell script, per the specific package's instructions. Is that correct? The article that I linked has the following line: "To install a package which is not available in the Canopy / EPD repository, follow standard Python installation procedures from the OS command line.", which seems to imply that I install per package instructions.
In .bashrc, I have the following:
VIRTUAL_ENV_DISABLE_PROMPT=1 source /home/joe/Enthought/Canopy_64bit/User/bin/activate
export PYTHONHOME=/home/joe/Enthought/Canopy_64bit/User/bin
export PATH=/home/joe/Enthought/Canopy_64bit/User/bin
export PYTHONPATH=/home/joe/Enthought/Canopy_64bit/User/bin
From what I understand of the linked articles, this means I'm setting Canopy User as my default Python distribution. I'm sure I'm doing something a bit over my head here, but I can't understand what else I need to do to fix this issue.
Worse yet, now I'm getting an "ImportError: No module named site" with these .bashrc settings, when trying to start IPython notebook or python from the command line. I can run only from the Canopy GUI.
Closing this. I made it harder than necessary.
It turns out, the PYTHONHOME and PYTHONPATH .bashrc variables were causing some conflicts. Commenting them out seems to have resolved the issue.
Installing outside packages does, indeed, happen from the home (~) directory.
Background
I use Anaconda's IPython on my mac and it's a great tool for data exploration and debugging. However, when I wish to use IPython for my programs that require virtualenv (e.g. a Django web app), I don't want to have to reinstall IPython every time.
Question
Is there a way to use my local IPython while also using the rest of my virtualenv packages? (i.e. just make IPython the exception to virtualenv packages so that the local IPython setup is available no matter what) If so, how would you do this on a mac? My guess is that it would be some nifty .bash_profile changes, but my limited knowledge with it hasn't been fruitful. Thanks.
Example Usage
Right now if I'm debugging a program, I'd use the following:
import pdb
pdb.set_trace() # insert this to pause program and explore at command line
This would bring it to the command line (that I wish was IPython)
If you have a module in your local Python and not in the virtualenv, it will still be available in the virtualenv. Unless you shadow it with another virtualenv version. Did you try to launch your local IPython from a running virtualenv that didn't have an IPython? It should work.
Will, I assume you are using Anaconda's "conda" package manager? (Which combines the features of pip and virtualenv). If so you should be aware that many parts of it does not work completely like the tools it is replacing. E.g. if you are using conda create -n myenv to create your virtual environment, this is different from the "normal" virtualenv in a number of ways. In particular, there is no "global/default" packages: Even the default installation is essentially an environment ("root") like all other environments.
To obtain the usual virtualenv behavior, you can create your environments by cloning the root environment: conda create -n myenv --clone root. However, unlike for regular virtualenv, if you make changes to the default installation (the "root" environment in conda) these changes are not reflected in the environments that were created by cloning the root environment.
An alternative to cloning the root is to keep an updated list of "default packages" that you want to be available in new environments. This is managed by the create_default_packages option in the condarc file.
In summary: Don't treat your conda environments like regular python virtualenvs - even though they appear deceptively similar in many regards. Hopefully at some point the two implementations will converge.