Tag: Pytorch
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What is nn.Conv2d for in Pytorch?
nn.Conv2d is a class in the PyTorch deep learning framework that represents a 2-dimensional convolutional layer. Convolutional layers are a fundamental building block in Convolutional Neural Networks (CNNs), which are widely used for image processing, computer vision, and other tasks involving grid-like input data. The nn.Conv2d class is part of the torch.nn module, which provides […]
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In Pytorch what is nn.Embedding for and how is it different from One Hot Encding for representing categorical data
In PyTorch, nn.Embedding is a class that provides a simple lookup table that maps integers (usually representing discrete items like words, tokens, or categories) to continuous vectors. It is primarily used for working with categorical data in deep learning models, particularly in natural language processing tasks. nn.Embedding is often used to convert discrete tokens (e.g., […]
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What is the PyTorch permute() function for?
In PyTorch, the permute() function is used to rearrange the dimensions of a tensor according to a specified order. This can be useful in various deep learning scenarios, such as when you need to change the dimension order of your input data to match the expected input format of a model. The function takes a […]
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Pairwise Squared Euclidean Distance Loss function used in “Taming Transformers for high resolution images” paper explained
The code snippet using PyTorch library below is found in the Taming Transformers paper: This code snippet is performing a vectorized calculation to compute pairwise squared Euclidean distances between two sets of vectors: z_flattened and the rows of self.embedding.weight. Let’s break down the code: Now let’s analyze the calculations: Finally, the code adds the three […]
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What is tensor.detach() used for in PyTorch?
Let’s take a closer look at the detach() function in PyTorch, which plays a helpful role when working with Tensors. The detach() function creates a new Tensor that shares the same data as the original one but without the attached computation history. This essentially separates the new Tensor from the computation graph, making it independent […]
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What does the tensor.view() function do in PyTorch and how is it different from permute?
In PyTorch, the view() function is a tensor operation used to reshape a tensor without changing its underlying data. It allows you to change the dimensions of a tensor to fit your desired shape while preserving the original data and maintaining the same number of elements. This is especially useful when you need to change […]
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Convert a photo from 2D to 3D model with color with PIFu
This is a short tutorial on how you can convert and train Pifu to convert a 2D photo to a 3D Model with color. Pifu is the predecessor to PIFuHD. PIFU in theory can be trained to create 3D Models for any type of object, not just humans, but of course, you will need to […]
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How to turn 2D photos into a 3D model using Nvidia Kaolin and PyTorch – A 3D Deep Learning Tutorial
If you have read my last article on GANverse3D, then you will probably have heard about the DIB-R paper, which I mentioned a few times. This was a key paper for 3D Deep Learning from 2019. The DIB-R paper introduced an improved differential renderer as a tool to solve one of the most fashionable problems […]