This release is a pre-release and may not be stable for production use.
GPyTorch-QR
Gaussian process quantile regression using GPyTorch.
Installation
$ pip install gpytorch-qr
Documentation
The manual can be found online:
If you want to build the document yourself, get the source code and install with [doc] dependency.
Then, go to doc directory and build the document:
$ pip install .[doc]
$ cd doc
$ make html
Document will be generated in build/html directory. Open index.html to see the central page.
Developing
Installation
For development features, you must install the package by pip install -e .[dev].
Configuring git
Configure the local git filter (run once after cloning):
nbstripout --install --attributes .gitattributes
git config filter.nbstripout.clean "nbstripout"
git config filter.nbstripout.smudge cat
git config filter.nbstripout.required true
Testing notebook build
Set the GPYTORCH_N_EPOCHS environment variable to 1 for quickly test notebook build.
export GPYTORCHQR_N_EPOCHS=1
jupyter nbconvert --to notebook --execute --inplace examples/*.ipynb
jupyter nbconvert --to notebook --execute --inplace examples/**/*.ipynb
1 maintainer
Metadata
1 maintainer
Release files for gpytorch-qr 1.0.0rc0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gpytorch_qr-1.0.0rc0.tar.gz | 23.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gpytorch_qr-1.0.0rc0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 41.8 kB
Release files / gpytorch_qr-1.0.0rc0.tar.gz
| Download URL | gpytorch_qr-1.0.0rc0.tar.gz |
|---|---|
| Size | 23.1 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
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twine/7.0.0 CPython/3.12.14
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Release files / gpytorch_qr-1.0.0rc0-py3-none-any.whl
| Download URL | gpytorch_qr-1.0.0rc0-py3-none-any.whl |
|---|---|
| Size | 18.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.12.14
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