Simple gradient computation library in Python
Project description
NumGrad
Simple gradient computation library for Python.
Getting Started
pip install git+https://github.com/ctgk/numgrad.git
Inspired by tensorflow, numgrad
supports automatic differentiation in tensorflow v2 style using original numpy
and scipy
functions.
>>> import numgrad as ng
>>> import numpy as np # Original numpy
>>>
>>> # Pure numpy function
>>> def tanh(x):
... y = np.exp(-2 * x)
... return (1 - y) / (1 + y)
...
>>> x = ng.Variable(1)
>>> with ng.Graph() as g:
... # numgrad patches numpy functions automatically here
... y = tanh(x)
...
>>> g.gradient(y, [x])
(0.419974341614026,)
>>> (tanh(1.0001) - tanh(0.9999)) / 0.0002
0.41997434264973155
Build and Test
Contribute
Be sure to run the following command before developing
$ git clone https://github.com/ctgk/numgrad.git
$ cd numgrad
$ pre-commit install
Project details
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numgrad-0.1.1.tar.gz
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