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PyTorch

Learn everything about PyTorch, one of the most deep learning framework these days

Counting Tensor Elements with `torch.numel()` in PyTorch

Updated: Dec 14, 2024
PyTorch is a comprehensive library for machine learning that provides significant flexibility and performance. It's built to handle tensors efficiently, which serve as the core data structure similar to numpy's ndarrays. As a developer......

Saving and Loading Models with `torch.save()` and `torch.load()` in PyTorch

Updated: Dec 14, 2024
PyTorch is a powerful library for deep learning that is widely used for building and training neural networks. One of the benefits of PyTorch is that it offers simple and efficient functions for saving and loading models. This is......

Move Your Tensors to GPU with `torch.to()` in PyTorch

Updated: Dec 14, 2024
In high-performance machine learning and deep learning applications, one of the most significant optimizations comes from leveraging the computational power of Graphics Processing Units (GPUs). PyTorch, a popular deep learning library,......

A Guide to Checking CUDA Availability with `torch.cuda.is_available()` in PyTorch

Updated: Dec 14, 2024
IntroductionPyTorch is a popular open-source machine learning library that offers various tools to train and deploy neural networks. One of its valuable features is the ability to leverage CUDA-enabled GPUs to accelerate computations.......

Backpropagation Simplified with `torch.autograd.backward()` in PyTorch

Updated: Dec 14, 2024
In the realm of neural networks, backpropagation is the essential algorithm for training neural networks via gradient descent. It efficiently computes the gradient of the loss function with respect to the weights of the network. PyTorch, a......

An Introduction to Automatic Differentiation with `torch.autograd.grad()` in PyTorch

Updated: Dec 14, 2024
Automatic differentiation is a key feature in modern machine learning frameworks as it allows for efficient computation of gradients. In deep learning, these gradients are essential for optimization algorithms. PyTorch, a popular deep......

How to Identify Finite Values Using `torch.isfinite()` in PyTorch

Updated: Dec 14, 2024
PyTorch is a popular open-source machine learning library primarily used for applications such as computer vision and natural language processing. One of its many useful features is the ability to easily manipulate tensors, which are......

Mastering Greater-Than Comparisons with `torch.gt()` in PyTorch

Updated: Dec 14, 2024
In the realm of deep learning and neural networks, PyTorch stands out as a highly flexible and popular library. One fundamental aspect of PyTorch that every developer should be familiar with is the use of comparison operations.......

Element-Wise Equality Checks with `torch.eq()` in PyTorch

Updated: Dec 14, 2024
PyTorch is a highly versatile library for machine learning and deep learning that supports tensor computations with strong GPU acceleration. One of the many useful methods provided by PyTorch is torch.eq(). This function performs......

Computing the Norm of a Tensor with `torch.norm()` in PyTorch

Updated: Dec 14, 2024
In modern deep learning applications, tensors are essential data structures. They serve as dynamic, multidimensional arrays that form the basis of operations in libraries like PyTorch. When working with tensors, one common mathematical......

Find the Indices of the Largest Values with `torch.argmax()` in PyTorch

Updated: Dec 14, 2024
PyTorch is an open-source machine learning library that provides a flexible platform for deep learning research and development. One of the powerful utilities it offers is torch.argmax(), a function that is used to find the indices of the......

Discovering Maximum Values with `torch.max()` in PyTorch

Updated: Dec 14, 2024
PyTorch is a popular open-source machine learning library that provides a seamless path from research prototyping to production deployment. One of its most frequently used capabilities is handling tensor operations with ease and......