SplineConv implementation for Paddle.

Overview

SplineConv implementation for Paddle

This module implements the SplineConv operators from

Matthias Fey, Jan Eric Lenssen, Frank Weichert, Heinrich Müller: SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels (CVPR 2018).

It is in early development, and may have problems. Feel free to open an issue if you find one.

Requirements

It only needs paddle. It is tested on paddle >= 2.1.0, <= 2.2.0rc1, but should work for any recent paddle versions.

For development -- since we run tests against torch-spline-conv, you will need that.

Installation

pip install paddle-spline-conv

Usage

Here are some basic usage descriptions. See docstring in code for more detailed descriptions, types and shapes of parameters.

Currently only degree-1 splines are supported. But the basic operators have been ready, and adding more shouldn't be very hard. You are welcome to contribute for higher degree splines!

import paddle_spline_conv

# Stacked SplineConv layers implemented in SConv
g = paddle_spline_conv.nn.GraphData(x, edge_index, edge_attr)
# Input n_features and output n_features
sconv = paddle_spline_conv.nn.SConv(10, 40)
sconv(g)

# Standalone SplineConv layer
paddle_spline_conv.nn.SplineConv(
    in_channels: int,
    out_channels: int,
    dim: int,
    kernel_size: int,
    is_open_spline: bool = True,
    degree: int = 1,
    aggr: str = 'mean',
    root_weight: bool = True,
    bias: bool = True
)

# Standalone SplineConv functional API
paddle_spline_conv.functional.spline_conv(
    x: paddle.Tensor, edge_index: paddle.Tensor,
    pseudo: paddle.Tensor, weight: paddle.Tensor,
    kernel_size: paddle.Tensor, is_open_spline: paddle.Tensor,
    degree: int = 1, aggr: str = 'mean',
    root_weight: Optional[paddle.Tensor] = None,
    bias: Optional[paddle.Tensor] = None
)

# SplineConv-specific operators
paddle_spline_conv.ops.spline_basis
paddle_spline_conv.ops.spline_weighting
paddle_spline_conv.ops.basis_kernel_1d
Owner
北海若
Undergraduate, at SJTU & MSRA.
北海若
Fully-automated scripts for collecting AI-related papers

AI-Paper-collector Fully-automated scripts for collecting AI-related papers List of Conferences to crawel ACL: 21-19 (including findings) EMNLP: 21-19

Gordon Lee 776 Jan 08, 2023
A Runtime method overload decorator which should behave like a compiled language

strongtyping-pyoverload A Runtime method overload decorator which should behave like a compiled language there is a override decorator from typing whi

20 Oct 31, 2022
YouRefIt: Embodied Reference Understanding with Language and Gesture

YouRefIt: Embodied Reference Understanding with Language and Gesture YouRefIt: Embodied Reference Understanding with Language and Gesture by Yixin Che

16 Jul 11, 2022
Binary Passage Retriever (BPR) - an efficient passage retriever for open-domain question answering

BPR Binary Passage Retriever (BPR) is an efficient neural retrieval model for open-domain question answering. BPR integrates a learning-to-hash techni

Studio Ousia 147 Dec 07, 2022
Dilated Convolution for Semantic Image Segmentation

Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper

Fisher Yu 764 Dec 26, 2022
A curated (most recent) list of resources for Learning with Noisy Labels

A curated (most recent) list of resources for Learning with Noisy Labels

Jiaheng Wei 321 Jan 09, 2023
Semantic graph parser based on Categorial grammars

Lambekseq "Everyone who failed Greek or Latin hates it." This package is for proving theorems in Categorial grammars (CG) and constructing semantic gr

10 Aug 19, 2022
PSPNet in Chainer

PSPNet This is an unofficial implementation of Pyramid Scene Parsing Network (PSPNet) in Chainer. Training Requirement Python 3.4.4+ Chainer 3.0.0b1+

Shunta Saito 76 Dec 12, 2022
Datasets, Transforms and Models specific to Computer Vision

vision Datasets, Transforms and Models specific to Computer Vision Installation First install the nightly version of OneFlow python3 -m pip install on

OneFlow 68 Dec 07, 2022
Training, generation, and analysis code for Learning Particle Physics by Example: Location-Aware Generative Adversarial Networks for Physics

Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),

Deep Learning for HEP 57 Oct 22, 2022
Model-based reinforcement learning in TensorFlow

Bellman Website | Twitter | Documentation (latest) What does Bellman do? Bellman is a package for model-based reinforcement learning (MBRL) in Python,

46 Nov 09, 2022
The official code repo of "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound Classification and Detection"

Hierarchical Token Semantic Audio Transformer Introduction The Code Repository for "HTS-AT: A Hierarchical Token-Semantic Audio Transformer for Sound

Knut(Ke) Chen 134 Jan 01, 2023
Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology

Official repository for the ICLR 2021 paper Evaluating the Disentanglement of Deep Generative Models with Manifold Topology Sharon Zhou, Eric Zelikman

Stanford Machine Learning Group 34 Nov 16, 2022
Scikit-learn compatible estimation of general graphical models

skggm : Gaussian graphical models using the scikit-learn API In the last decade, learning networks that encode conditional independence relationships

213 Jan 02, 2023
Plugin adapted from Ultralytics to bring YOLOv5 into Napari

napari-yolov5 Plugin adapted from Ultralytics to bring YOLOv5 into Napari. Training and detection can be done using the GUI. Training dataset must be

2 May 05, 2022
PyTorch implementation of the ideas presented in the paper Interaction Grounded Learning (IGL)

Interaction Grounded Learning This repository contains a simple PyTorch implementation of the ideas presented in the paper Interaction Grounded Learni

Arthur Juliani 4 Aug 31, 2022
Pytorch Implementation of rpautrat/SuperPoint

SuperPoint-Pytorch (A Pure Pytorch Implementation) SuperPoint: Self-Supervised Interest Point Detection and Description Thanks This work is based on:

76 Dec 27, 2022
Code for "LoRA: Low-Rank Adaptation of Large Language Models"

LoRA: Low-Rank Adaptation of Large Language Models This repo contains the implementation of LoRA in GPT-2 and steps to replicate the results in our re

Microsoft 394 Jan 08, 2023
Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN

Single Image Super-Resolution (SISR) with SRResNet, EDSR and SRGAN Introduction Image super-resolution (SR) is the process of recovering high-resoluti

8 Apr 15, 2022
The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021)

The Official PyTorch Implementation of "LSGM: Score-based Generative Modeling in Latent Space" (NeurIPS 2021) Arash Vahdat*   ·   Karsten Kreis*   ·  

NVIDIA Research Projects 238 Jan 02, 2023