Pytorch cuda extension of grid_sample1d

Overview

Grid Sample 1d

pytorch cuda extension of grid sample 1d. Since pytorch only supports grid sample 2d/3d, I extend the 1d version for efficiency. The forward pass is 2~3x faster than pytorch grid sample.

setup

  • Pytorch == 1.7.1
  • CUDA == 10.1

Other versions of pytorch or cuda may work but I haven't test.

you can choose to manually build it or use JIT

Build

python setup.py install

JIT

comment import grid_sample1d_cuda as grid_sample1d in op.py

uncomment

grid_sample1d = load(
    'grid_sample1d_cuda', ['grid_sample1d_cuda.cpp', 'grid_sample1d_cuda_kernel.cu'], verbose=True)

in op.py

Usage

import torch
from grid_sample1d import GridSample1d

grid_sample1d = GridSample1d(padding_mode=True, align_corners=True)
N = 16
C = 256
L_in = 64
L_out = 128
input = torch.randn((N, C, L_in)).cuda()
grids = torch.randn((N, L_out)).cuda()
output = grid_sample1d(input, grids)

Options are

  • padding_mode: True for border padding, False for zero padding
  • align_corners: same with align_corners in torch.nn.functional.grid_sample

difference

In forward pass, calculation on the channel dim C is parallel, which is serial in torch.nn.functional.grid_sample. Parallel calculation on C may cause round off error in backward. But for now, I found it doesn't influence the forward pass.

Test

Accuracy Test

Since grid sample 1d is a special case of grid sample 2d in most cases (not true when padding_mode & align_corners are both False). I test the accuracy of the implemented grid sample based on torch.nn.functional.grid_sample.

import torch
import torch.nn.functional as F


def gridsample1d_by2d(input, grid, padding_mode, align_corners):
    shape = grid.shape
    input = input.unsqueeze(-1)  # batch_size * C * L_in * 1
    grid = grid.unsqueeze(1)  # batch_size * 1 * L_out
    grid = torch.stack([-torch.ones_like(grid), grid], dim=-1)
    z = F.grid_sample(input, grid, padding_mode=padding_mode, align_corners=align_corners)
    C = input.shape[1]
    out_shape = [shape[0], C, shape[1]]
    z = z.view(*out_shape)  # batch_size * C * L_out
    return z

It is recommended to test on your computer because I only test it on CUDA 10.1 GTX 1080Ti

python test/acc_benchmark.py

Both the forward and the backward results are identical except for align_corners=True, padding_mode=False. It may be caused by round off error when we sum series float numbers in different orders.

Deterministic Test

It is very important to do deterministic test since the associative law is no more applied for the calculation of float numbers on computers.

python test/check_deterministic.py

Note

When padding_mode & align_corners are both False, we cannot regard grid sample 1d as a special case of grid sample 2d in pytorch. I have checked the cuda kernel of grid_sample in Pytorch. When padding_mode & align_corners are both False, the output of torch.nn.functional.grid_sample will be half of the expected. Hope it can be fixed one day.

CPU support

Too lazy to support

speed & memory cost

Here are the speed test results on different size of input

references

Owner
lyricpoem
lyricpoem
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

Introduction QRec is a Python framework for recommender systems (Supported by Python 3.7.4 and Tensorflow 1.14+) in which a number of influential and

Yu 1.4k Jan 01, 2023
Byte-based multilingual transformer TTS for low-resource/few-shot language adaptation.

One model to speak them all 🌎 Audio Language Text ▷ Chinese 人人生而自由,在尊严和权利上一律平等。 ▷ English All human beings are born free and equal in dignity and rig

Mutian He 60 Nov 14, 2022
Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an

Mohamed Afham 152 Dec 23, 2022
《Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching》(CVPR 2020)

This contains the codes for cross-view geo-localization method described in: Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching, CVPR2020.

41 Oct 27, 2022
Yolo object detection - Yolo object detection with python

How to run download required files make build_image make download Docker versio

3 Jan 26, 2022
Listing arxiv - Personalized list of today's articles from ArXiv

Personalized list of today's articles from ArXiv Print and/or send to your gmail

Lilianne Nakazono 5 Jun 17, 2022
A Unified Framework and Analysis for Structured Knowledge Grounding

UnifiedSKG 📚 : Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Models Code for paper UnifiedSKG: Unifying and Mu

HKU NLP Group 370 Dec 21, 2022
Deep learning library featuring a higher-level API for TensorFlow.

TFLearn: Deep learning library featuring a higher-level API for TensorFlow. TFlearn is a modular and transparent deep learning library built on top of

TFLearn 9.6k Jan 02, 2023
img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation

img2pose: Face Alignment and Detection via 6DoF, Face Pose Estimation Figure 1: We estimate the 6DoF rigid transformation of a 3D face (rendered in si

Vítor Albiero 519 Dec 29, 2022
RE3: State Entropy Maximization with Random Encoders for Efficient Exploration

State Entropy Maximization with Random Encoders for Efficient Exploration (RE3) (ICML 2021) Code for State Entropy Maximization with Random Encoders f

Younggyo Seo 47 Nov 29, 2022
The Codebase for Causal Distillation for Language Models.

Causal Distillation for Language Models Zhengxuan Wu*,Atticus Geiger*, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D.

Zen 20 Dec 31, 2022
This is the code for ACL2021 paper A Unified Generative Framework for Aspect-Based Sentiment Analysis

This is the code for ACL2021 paper A Unified Generative Framework for Aspect-Based Sentiment Analysis Install the package in the requirements.txt, the

108 Dec 23, 2022
Learning based AI for playing multi-round Koi-Koi hanafuda card games. Have fun.

Koi-Koi AI Learning based AI for playing multi-round Koi-Koi hanafuda card games. Platform Python PyTorch PySimpleGUI (for the interface playing vs AI

Sanghai Guan 10 Nov 20, 2022
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].

Smooth ReLU in PyTorch Unofficial PyTorch reimplementation of the Smooth ReLU (SmeLU) activation function proposed in the paper Real World Large Scale

Christoph Reich 10 Jan 02, 2023
Official implementation for Multi-Modal Interaction Graph Convolutional Network for Temporal Language Localization in Videos

Multi-modal Interaction Graph Convolutioal Network for Temporal Language Localization in Videos Official implementation for Multi-Modal Interaction Gr

Zongmeng Zhang 15 Oct 18, 2022
Face Detection and Alignment using Multi-task Cascaded Convolutional Networks (MTCNN)

Face-Detection-with-MTCNN Face detection is a computer vision problem that involves finding faces in photos. It is a trivial problem for humans to sol

Chetan Hirapara 3 Oct 07, 2022
Half Instance Normalization Network for Image Restoration

HINet Half Instance Normalization Network for Image Restoration, based on https://github.com/megvii-model/HINet. Dependencies NumPy PyTorch, preferabl

Holy Wu 4 Jun 06, 2022
DIVeR: Deterministic Integration for Volume Rendering

DIVeR: Deterministic Integration for Volume Rendering This repo contains the training and evaluation code for DIVeR. Setup python 3.8 pytorch 1.9.0 py

64 Dec 27, 2022
A supplementary code for Editable Neural Networks, an ICLR 2020 submission.

Editable neural networks A supplementary code for Editable Neural Networks, an ICLR 2020 submission by Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Py

Anton Sinitsin 32 Nov 29, 2022
An Intelligent Self-driving Truck System For Highway Transportation

Inceptio Intelligent Truck System An Intelligent Self-driving Truck System For Highway Transportation Note The code is still in development. OS requir

InceptioResearch 11 Jul 13, 2022