# tensorop <img style=”float: centre;” src=”tensorop_logo.png”>
[](https://badge.fury.io/py/tensorop)
A Library which contains handy modules for convenience in Machine Learning and improved Kaggle support. Based on Pytorch. It’s currently under development. Same API as Pytorch and Numpy. Main aim is to bring all functionalities that DL frameworks may lack for some reason but are essentially required for research/implementation purposes.
## Installation Installation via Pypi ` $ pip install tensorop ` Using with git ` $ git clone https://github.com/prajjwal1/tensorop $ cd tensorop `
## Requirements - Pytorch >= 0.4
## Components (with Docs) - [tensor_func](https://prajjwal1.github.io/tensorop/torch_func/) - [np_utils](https://prajjwal1.github.io/tensorop/np_utils/) - [optimizers](https://prajjwal1.github.io/tensorop/optimizers/) - [Training](https://prajjwal1.github.io/tensorop/train/) - [Models](https://prajjwal1.github.io/tensorop/models/) - [loss_function](https://prajjwal1.github.io/tensorop/loss_function/) - [Kaggle](https://prajjwal1.github.io/tensorop/kaggle/) - [Utilities](https://prajjwal1.github.io/tensorop/utils/)
1 maintainer
Metadata
1 maintainer
Release files for tensorop 0.0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| tensorop-0.0.6.1-py2-none-any.whl | Python 2 | none | any | Details for tensorop-0.0.6.1-py2-none-any.whl |
Release files / tensorop-0.0.6.1-py2-none-any.whl
| Download URL | tensorop-0.0.6.1-py2-none-any.whl |
|---|---|
| Size | 9.0 kB |
| Tags | Python 2 |
|
SHA-256 checksum How to use checksums |
dfc663c1e7ffec437f6769787f56a4ebb693b23bef6754d6c638b1b0dab653e2
|
|
BLAKE2b-256 checksum How to use checksums |
987763d1887370863447920a8d286a7e0e28804820ce119d1d49cbbe26a4c502
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/1.11.0 pkginfo/1.4.2 requests/2.18.4 setuptools/39.0.1 requests-toolbelt/0.8.0 tqdm/4.26.0 CPython/3.6.5
|
Security for tensorop 0.0.6.1
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
No provenance found
None of the files in this release were uploaded with provenance metadata.
A note on package security
PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.
To learn more about protecting yourself from malicious actors, visit our package security documentation.
](https://badge.fury.io/py/tensorop){kind=link}