Skip to main content

Automatic differentiation and generation of Torch/Tensorflow operations with pystencils (https://i10git.cs.fau.de/pycodegen/pystencils)

Project description

PyPI version Documentation Status=================== Gitlab CI https://travis-ci.org/theHamsta/pystencils_autodiff.svg?branch=master https://codecov.io/gh/theHamsta/pystencils_autodiff/branch/master/graph/badge.svg

pystencils_autodiff

This repo adds automatic differentiation to pystencils.

Installation

Install via pip:

pip install pystencils-autodiff

or if you downloaded this repository using:

pip install -e .

Then, you can access the submodule pystencils.autodiff.

import pystencils.autodiff

Usage

Create a pystencils.AssignmentCollection with pystencils:

import sympy
import pystencils

z, y, x = pystencils.fields("z, y, x: [20,30]")

forward_assignments = pystencils.AssignmentCollection({
    z[0, 0]: x[0, 0] * sympy.log(x[0, 0] * y[0, 0])
})

print(forward_assignments)
Subexpressions:
Main Assignments:
     z[0,0]  x_C*log(x_C*y_C)

You can then obtain the corresponding backward assignments:

from pystencils.autodiff import AutoDiffOp, create_backward_assignments
backward_assignments = create_backward_assignments(forward_assignments)

print(backward_assignments)

You can see the derivatives with respective to the two inputs multiplied by the gradient diffz_C of the output z_C.

Subexpressions:
Main Assignments:
    \hat{x}[0,0]  diffz_C*(log(x_C*y_C) + 1)
    \hat{y}[0,0]  diffz_C*x_C/y_C

You can also use the class AutoDiffOp to obtain both the assignments (if you are curious) and auto-differentiable operations for Tensorflow…

op = AutoDiffOp(forward_assignments)
backward_assignments = op.backward_assignments

tensorflow_op = op.create_tensorflow_op(backend='tensorflow_native', use_cuda=True)

… or Torch:

torch_op = op.create_tensorflow_op(backend='torch_native', use_cuda=True)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for pystencils-autodiff, version 0.3.2
Filename, size File type Python version Upload date Hashes
Filename, size pystencils_autodiff-0.3.2.tar.gz (53.7 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page