## PyTorch torch.permute() function

**July 23, 2023**By:

**Frienzied Flame**

This concise article is about the torch.permute() function in PyTorch. The fundamentals The torch.permute() function is used to rearrange the dimensions of a tensor according to a given…

## PyTorch: Selecting Elements from a Tensor (3 Ways)

**July 23, 2023**By:

**Khue**

This pithy, straightforward article will walk you through three different ways to select elements from a tensor in PyTorch. Without any further ado, let’s get started! Indexing &…

## PyTorch: Squeezing and Unsqueezing Tensors

**July 22, 2023**By:

**Frienzied Flame**

Squeezing and unsqueezing a tensor are two operations that can change the shape of a tensor by adding or removing dimensions of size 1. This concise, straight-to-the-point article…

## Stacking Tensors in PyTorch: Tutorials & Examples

**July 22, 2023**By:

**Frienzied Flame**

This concise, practical article is about stacking tensors in PyTorch with the torch.stack(), torch.vstack(), and torch.hstack() functions. torch.stack() Syntax & Parameters torch.stack() is a PyTorch function that joins…

## How to Flatten a Tensor in PyTorch (2 Ways)

**July 14, 2023**By:

**Khue**

Flattening a tensor in PyTorch means reshaping it into a one-dimensional tensor (1D tensor). This concise, example-based article will show you a couple of different ways to do…

## PyTorch Tensor.view() method (with example)

**July 14, 2023**By:

**Khue**

This concise and straight-to-the-point article is about the Tensor.view() method in PyTorch. The fundamentals A view of a tensor is a new tensor that shares the same underlying…

## How to Reshape a Tensor in PyTorch (with Examples)

**July 14, 2023**By:

**Khue**

Overview In PyTorch, reshaping a tensor means changing its shape (the number of dimensions and the size of each dimension) while keeping the same data and the number…

## Using the torch.prod() and torch.cumprod() functions in PyTorch

**July 8, 2023**By:

**Khue**

The torch.prod() and torch.cumprod() functions in PyTorch are used to calculate the product and the cumulative product of elements in a tensor, respectively. torch.prod() Syntax: Where: Example: torch.cumprod()…

## PyTorch RuntimeError: mean(): could not infer output dtype

**July 8, 2023**By:

**Khue**

When working with PyTorch and using the torch.mean() function (or the torch.Torch.mean() method), you might encounter the following error: This error means that you are trying to use…

## PyTorch: Find the Sum and Mean of a Tensor

**July 8, 2023**By:

**Wolf**

In PyTorch, to find the sum and mean of a tensor, you can use the torch.sum() and torch.mean() functions, respectively. These functions can operate on the whole tensor…