I'm working on the Kaggle competition, 'Feedback Essay Evaluation'.
The competition rules require me to submit the notebook on Kaggle's notebook with internet acccess disabled.
I need to use the NLTK library for one of my feature extraction algorithms, but when I submit the notebook it throws this error:
LookupError:
**********************************************************************
Resource omw-1.4 not found.
Please use the NLTK Downloader to obtain the resource:
>>> import nltk
>>> nltk.download('omw-1.4')
For more information see: https://www.nltk.org/data.html
Attempted to load corpora/omw-1.4
Searched in:
- '/root/nltk_data'
- '/opt/conda/nltk_data'
- '/opt/conda/share/nltk_data'
- '/opt/conda/lib/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data'
I have tried to download the nltk packages and uploading them to the input dataset of Kaggle, but the kernel doesn't recognize the package. I tried overwriting and linking it to the uploaded package but it doesn't work.
How can I download omw-1.4 with internet access disabled?
Related
Question: How can I download an older version of PyTorch geometric in google colab?
Context: I am trying to use/load a pytorch-geometric graph and am getting the error message: "RuntimeError: The 'data' object was created by an older version of PyG. If this error occurred while loading an already existing dataset, remove the 'processed/' directory in the dataset's root folder and try again." This graph was generated during summer 2021.
I am using PyTorch and the following code to import Pytorch geometric, but am still getting the error when using older versions.
#import torch
!pip install torch==1.8.0
import torch
torch.__version__
!pip install torch-scatter torch-sparse torch-cluster torch-spline-conv torch-geometric -f https://data.pyg.org/whl/torch-1.8.0+cpu.html
I am not sure whether I am using the correct older version of pytorch-geometric (I don't really know how to check whether this is correct). Any insight to would be greatly appreciated:
How to download older version of pytorch geometric?
What is causing this error?
Thanks in advance.
You may not need to downgrade: If G is a graph data object giving this error you can simply convert it as follows.
from torch_geometric.data import Data
G = Data(**G.__dict__)
I'm not sure if you still need it but I just ran into the same problem and here's what I found:
It seems like there isn't a compatibility document but you can check the version history here and find the corresponding release for the one nearest to the time when your pytorch version was released, of course this doesn't guarantee compatibility but I think you have a pretty good chance?
For the additional packages e.g. torch-scatter, you can find the corresponding versions here and install from the .whl files.
I am using the Sphinx autodoc and napoleon extensions to generate the documentation for my project (Qtools). This works well on my local machines. I am using Sphinx 3.1.2 (or higher). However, when I build the documentation on Read the Docs (RTD), only text added directly to the reStructuredText files that form the source of the documentation is processed. The docstrings that are supposed to be pulled in by autodoc do not appear in the HTML documentation generated by RTD. So for example in docs\source\section2_rsdoc.rst I have:
Response spectra
================
The response spectrum class
---------------------------
.. autoclass:: qtools.ResponseSpectrum
:members:
Response spectrum creation
--------------------------
.. autofunction:: qtools.calcrs
.. autofunction:: qtools.calcrs_cmp
.. autofunction:: qtools.loadrs
See also :func:`qtools.convert2rs` (converts a power spectrum into a response spectrum).
This results in:
Response spectra
The response spectrum class
Response spectrum creation
See also qtools.convert2rs (converts a power spectrum into a response spectrum).
In other words, all directives are apparently ignored, and hyperlinks to other functions are not added. I have examined several basic guidance documents such as this one, but I cannot figure out what I am doing wrong. RTD builds the documentation without any errors or warnings. In RTD advanced settings I have:
Documentation type: Sphinx HTML
Requirements file: requirements.txt
Python interpreter: CPython 3.x
Install Project: no
Use system packages: no
Python configuration file: blank
Enable PDF build: no
Enable EPUB build: no
I haven't touched any other settings.
In conf.py I have tried the following variations of line 15: sys.path.insert(0, os.path.abspath('.')), sys.path.insert(0, os.path.abspath('../..')) and the current sys.path.insert(0, os.path.abspath('../../..')). None of those made any difference.
I would be grateful for any help!
RTD builds the documentation without any errors or warnings
This is slightly incorrect. As you can see in the build logs, autodoc is emitting numerous warnings like this one:
WARNING: autodoc: failed to import class 'ResponseSpectrum' from module 'qtools'; the following exception was raised:
No module named 'qtools'
This has happened for all your variations of sys.path.insert, as you can see in some past builds.
Trying to make it work this way is tricky, since Read the Docs does some magic to guess the directory where your documentation is located, and also the working directory changes between commands.
Instead, there are two options:
Locate where the conf.py is located (see How do you properly determine the current script directory?) and work out a relative package from there.
Invest some time into making your code installable using up-to-date Python packaging standards, for example putting all your sources inside a qtools directory, and creating an appropriate pyproject.toml file using flit.
I'm using the current bundled binaries from https://github.com/excelsior-oss/xds (as of 12/6/2020) with just the most basic Hello World MOD file:
MODULE HelloWorld;
FROM STextIO IMPORT WriteLn, WriteString;
BEGIN
WriteString("Hello, World!");
WriteLn;
END HelloWorld.
xc HelloWorld.mod works fine for compiling it to object. However, I'm not clear on the exact syntax for xlink on a standalone MOD file. xlink HelloWorld.obj will at least get it to try with my object file, but as the error shows, it doesn't know the entrypoint. I've tried setting the entry point with the /ENTRY switch, but no luck doing it by module name. I've also tried setting the /SYS to console, but again, no luck there.
I feel there's some trivial linker option or program directive needed, but I'm just not finding it via Google...
To build a binary, use: xc =a =make HelloWorld.mod
The above is found in https://github.com/excelsior-oss/xds/blob/master/Sources/Doc/Comp/src/usage.tex .
It is unfortunate that XDS did not put PDFs of their documentation on github. I suggest building the documentation from their LaTeX files.
Edit: I since learnt that the Wayback Machine has archived the XDS documentation here: https://web.archive.org/web/20060705213825/http://www.excelsior-usa.com/xdsdoc.html
In my notebook I get some data from URL, perform some analysis and do some plotting.
I want also create a html animation using FuncAnimation of matplotlib.animation.
So in the preamble I do
import matplotlib.animation as manim
plt.rcParams["animation.html"] = "html5"
%matplotlib inline
(something else... def init()..., def animate(i)...) then
anima = manim.FuncAnimation(fig,
animate,
init_func=init,
frames=len(ypos)-d0,
interval=200,
repeat=False,
blit=True)
To visualise, I then call
FFMpegWriter = manim.writers['ffmpeg']
writer = FFMpegWriter(fps=15)
link = anima.to_html5_video()
from IPython.core.display import display, HTML
display(HTML(link))
because I want the clip to show up as a neat html video in the notebook
Whereas this works well on my machine, on Watson-Studio I get the following error:
RuntimeError: Requested MovieWriter (ffmpeg) not available
I've checked that ffmpeg is available in the form of a Python package
(!pip freeze --isolated | grep ffmpeg gives ffmpeg-python==0.2.0)
The question is: how can I tell matplotlib.animation.writers to use the codec in ffmpeg-python?
Many thanks to all responders and supporters
We currently don't have ffmpeg pre-installed in Watson Studio on Cloud. The package ffmpeg-python that you mention is just a Python wrapper, but it won't work without the actual ffmpeg.
You can install ffmpeg from conda:
!conda install ffmpeg
Once you have the full list of additional packages that your notebook needs, I recommend to create a custom environment. Then you don't have to put install commands into the actual notebook.
The customization might look like this:
dependencies:
- ffmpeg=4.2.2
- pip
- pip:
- ffmpeg-python==0.2.0
I want to embed the HTML output of Jupyter, in my own web page. The reason for this is primarily, so that I can use Jupyter from my own webapp - and also access my research notebooks from anywhere in the world - via the internet.
A typical use case scenario would be that I click on a button on my page, and an iframe will be inserted in my page; Jupyter will then be launched at the backend (if not already running), and the output of Jupyter will be 'piped' to the iframe - so that I can use Jupyter from within my page.
The naive solution it appeared, was to use <iframe>, but there were two problems:
The iframe cross domain policy problem
Jupyter generated a one time authentication token when first launched
Is there anyway I can overcome these issues, so I can embed the output of Jupyter in my own web page?
you need to check nbconvert - https://github.com/jupyter/nbconvert
there you have 2 options.
to use command line to run notebook and then to let some web server
to server .html
to use python, and nbconvert library
here is short code :
if you want to show already generated:
from nbconvert.preprocessors import ExecutePreprocessor
import nbformat
from nbconvert import HTMLExporter
from nbconvert.preprocessors.execute import CellExecutionError
src_notebook = nbformat.reads(ff.read(), as_version=4) #where ff is file opened with some open("path to notebook file")
html_exporter = HTMLExporter()
html_exporter.template_file = 'basic' #basic will skip generating body and html tags.... use "all" to gen all..
(body, resources) = html_exporter.from_notebook_node(src_notebook)
print(body) #body have html output
if you want also to run notebook, then :
from nbconvert.preprocessors import ExecutePreprocessor
import nbformat
from nbconvert import HTMLExporter
from nbconvert.preprocessors.execute import CellExecutionError
src_notebook = nbformat.reads(ff.read(), as_version=4) #where ff is file opened with some open("path to notebook file")
ep = ExecutePreprocessor(timeout=50, kernel_name='python3')
ep.preprocess(src_notebook, {})
html_exporter = HTMLExporter()
html_exporter.template_file = 'basic' #basic will skip generating body and html tags.... use "all" to gen all..
(body, resources) = html_exporter.from_notebook_node(src_notebook)
print(body) #body have html output
You can directly do that using the html_embed pre-processor:
$ jupyter nbconvert --to html_embed Annex.ipynb
[NbConvertApp] Converting notebook Annex.ipynb to html_embed
/usr/local/lib/python3.6/site-packages/nbconvert/filters/datatypefilter.py:41: UserWarning: Your element with mimetype(s) dict_keys(['image/pdf']) is not able to be represented.
mimetypes=output.keys())
[NbConvertApp] Writing 2624499 bytes to Annex.html
Strangely, I could not find a direct reference in the manual from nbconvert.
You can use ipython nbconvert - -to html notebook.ipynb to obtain the html code for the same.
Here is a guide on how to do it Blogging with the IPython notebook - see here
If your website is writing in python the use python embed docs
Also this Tutorial - see here
or use kyso.io
Here is how to embed Jupyter using Kyso platform - see here
(disclaimer - I’m a founder of kyso)