A new convnet that beats transformers — Hello There!! Today we are going to implement the famous ConvNext in PyTorch proposed in A ConvNet for the 2020s . Code is here, an interactive version of this article can be downloaded from here. Let’s get started! The paper proposes a new convolution-based architecture that not only surpasses Transformer-based…

transformers go brum brum Hi guys! Today we are going to implement Training data-efficient image transformers & distillation through attention a new method to perform knowledge distillation on Vision Transformers called DeiT. You will soon see how elegant and simple this new approach is. Code is here, an interactive version…

Hi guys, happy new year! Today we are going to implement the famous Vi(sion) T(ransformer) proposed in AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE. Code is here, an interactive version of this article can be downloaded from here. ViT is available on my new computer…

Hello There! Code is here Today we will see how to load a Pytorch model with linear memory consumption. Loading a model takes 2x memory space. Let’s see why: First, we need a model: Upon creation, the model takes 1x memory, where x is its size At some…

DropPath is available in glasses my computer vision library — Code is here an interactive version of this article can be downloaded from here. Introduction Today we are going to implement Stochastic Depth also known as Drop Path in PyTorch! Stochastic Depth introduced by Gao Huang et al is a technique to “deactivate” some layers during training. We’ll stick with DropPath. …

What the hell are those + implementation in PyTorch — An interactive version is available here All these blocks have been implemented in my library glasses Keeping track of names in modern Deep Learning is hard. Today we’ll see different blocks used in modern CNN architecture such as ResNet, MobileNet, EfficientNet, and their implementation in PyTorch! Before we do anything…

An interactive version of this article can be found here DropBlock is available on glasses in my computer vision library! Introduction Today we are going to implement DropBlock in PyTorch! DropBlock introduced by Ghiasi et al is a regularization technique specifical crafter for images that empirically works better than Dropout. …

A deep learning approach — All the code can be found here. An interactive version of this article can be downloaded from here Today we are going to use deep learning to create a face unlock algorithm. To complete our puzzle, we need three main pieces. a find faces algorithm a way to embed the…

torchserve to the rescue! — All the code used in this article is here Recently, PyTorch has introduced its new production framework to properly serve models, called torchserve.So, without further due, let’s present today’s roadmap: Installation with Docker Export your model Define a handler Serve our model To showcase torchserve, we will serve a fully…