Python Interview Questions

Overview

Python Interview Questions

  1. Clone the code to your computer.
  2. You need to understand the code in main.py and modify the content in if __name__ =='__main__': to execute the get_key method in Algo.
  3. If the code is executed correctly, there will be content output, otherwise there will be no output.

Tip: Currently only x86 Linux is supported, you may need to use docker to get environment support.

Tip2: The author has no money to pay for the cloud service, please try again on the 1st of next month.

Owner
ClassmateLin
ClassmateLin
CondenseNet V2: Sparse Feature Reactivation for Deep Networks

CondenseNetV2 This repository is the official Pytorch implementation for "CondenseNet V2: Sparse Feature Reactivation for Deep Networks" paper by Le Y

Haojun Jiang 74 Dec 12, 2022
Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021)

Reducing Information Bottleneck for Weakly Supervised Semantic Segmentation (NeurIPS 2021) The implementation of Reducing Infromation Bottleneck for W

Jungbeom Lee 81 Dec 16, 2022
PyTorch implementation for paper "Full-Body Visual Self-Modeling of Robot Morphologies".

Full-Body Visual Self-Modeling of Robot Morphologies Boyuan Chen, Robert Kwiatkowskig, Carl Vondrick, Hod Lipson Columbia University Project Website |

Boyuan Chen 32 Jan 02, 2023
Self-Supervised Methods for Noise-Removal

SSMNR | Self-Supervised Methods for Noise Removal Image denoising is the task of removing noise from an image, which can be formulated as the task of

1 Jan 16, 2022
PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluation of Visual Stories via Semantic Consistency"

Improving Generation and Evaluation of Visual Stories via Semantic Consistency PyTorch code for the NAACL 2021 paper "Improving Generation and Evaluat

Adyasha Maharana 28 Dec 08, 2022
EvoJAX is a scalable, general purpose, hardware-accelerated neuroevolution toolkit

EvoJAX: Hardware-Accelerated Neuroevolution EvoJAX is a scalable, general purpose, hardware-accelerated neuroevolution toolkit. Built on top of the JA

Google 598 Jan 07, 2023
Implementation for paper "Towards the Generalization of Contrastive Self-Supervised Learning"

Contrastive Self-Supervised Learning on CIFAR-10 Paper "Towards the Generalization of Contrastive Self-Supervised Learning", Weiran Huang, Mingyang Yi

Weiran Huang 13 Nov 30, 2022
This toolkit provides codes to download and pre-process the SLUE datasets, train the baseline models, and evaluate SLUE tasks.

slue-toolkit We introduce Spoken Language Understanding Evaluation (SLUE) benchmark. This toolkit provides codes to download and pre-process the SLUE

ASAPP Research 39 Sep 21, 2022
Implementation of Uformer, Attention-based Unet, in Pytorch

Uformer - Pytorch Implementation of Uformer, Attention-based Unet, in Pytorch. It will only offer the concat-cross-skip connection. This repository wi

Phil Wang 72 Dec 19, 2022
ML models and internal tensors 3D visualizer

The free Zetane Viewer is a tool to help understand and accelerate discovery in machine learning and artificial neural networks. It can be used to ope

Zetane Systems 787 Dec 30, 2022
Hummingbird compiles trained ML models into tensor computation for faster inference.

Hummingbird Introduction Hummingbird is a library for compiling trained traditional ML models into tensor computations. Hummingbird allows users to se

Microsoft 3.1k Dec 30, 2022
Weakly Supervised Scene Text Detection using Deep Reinforcement Learning

Weakly Supervised Scene Text Detection using Deep Reinforcement Learning This repository contains the setup for all experiments performed in our Paper

Emanuel Metzenthin 3 Dec 16, 2022
A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal

A lightweight library designed to accelerate the process of training PyTorch models by providing a minimal, but extensible training loop which is flexible enough to handle the majority of use cases,

Chris Hughes 110 Dec 23, 2022
PyTorch implementation for the visual prior component (i.e. perception module) of the Visually Grounded Physics Learner [Li et al., 2020].

VGPL-Visual-Prior PyTorch implementation for the visual prior component (i.e. perception module) of the Visually Grounded Physics Learner (VGPL). Give

Toru 8 Dec 29, 2022
PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images

wrist-d PyTorch Implementation for Fracture Detection in Wrist Bone X-ray Images note: Paper: Under Review at MPDI Diagnostics Submission Date: Novemb

Fatih UYSAL 5 Oct 12, 2022
Fit Fast, Explain Fast

FastExplain Fit Fast, Explain Fast Installing pip install fast-explain About FastExplain FastExplain provides an out-of-the-box tool for analysts to

8 Dec 15, 2022
Improving Object Detection by Label Assignment Distillation

Improving Object Detection by Label Assignment Distillation This is the official implementation of the WACV 2022 paper Improving Object Detection by L

Cybercore Co. Ltd 51 Dec 08, 2022
Implementation of the Paper: "Parameterized Hypercomplex Graph Neural Networks for Graph Classification" by Tuan Le, Marco Bertolini, Frank Noé and Djork-Arné Clevert

Parameterized Hypercomplex Graph Neural Networks (PHC-GNNs) PHC-GNNs (Le et al., 2021): https://arxiv.org/abs/2103.16584 PHM Linear Layer Illustration

Bayer AG 26 Aug 11, 2022
CharacterGAN: Few-Shot Keypoint Character Animation and Reposing

CharacterGAN Implementation of the paper "CharacterGAN: Few-Shot Keypoint Character Animation and Reposing" by Tobias Hinz, Matthew Fisher, Oliver Wan

Tobias Hinz 181 Dec 27, 2022
Run PowerShell command without invoking powershell.exe

PowerLessShell PowerLessShell rely on MSBuild.exe to remotely execute PowerShell scripts and commands without spawning powershell.exe. You can also ex

Mr.Un1k0d3r 1.2k Jan 03, 2023