
PyTorch
Dec 17, 2025 · PyTorch Foundation is the deep learning community home for the open source PyTorch framework and ecosystem.
Learn the Basics — PyTorch Tutorials 2.9.0+cu128 documentation
Learn the Basics || Quickstart || Tensors || Datasets & DataLoaders || Transforms || Build Model || Autograd || Optimization || Save & Load Model Learn the Basics # Created On: Feb 09, 2021 | …
torch.optim — PyTorch 2.9 documentation
Jun 13, 2025 · torch.optim # Created On: Jun 13, 2025 | Last Updated On: Aug 24, 2025 torch.optim is a package implementing various optimization algorithms. Most commonly used …
Why do I install pytorch with the names "~orch" and "~-rch" in …
Jun 20, 2024 · Why do I install pytorch with the names "~orch" and "~-rch" in the site-packages folder? hrdom (dom) June 20, 2024, 11:33am 1 hrdom (dom) June 20, 2024, 12:44pm
torch.utils.data — PyTorch 2.9 documentation
Jun 13, 2025 · torch.utils.data # Created On: Jun 13, 2025 | Last Updated On: Jun 13, 2025 At the heart of PyTorch data loading utility is the torch.utils.data.DataLoader class. It represents a …
PyTorch documentation — PyTorch 2.9 documentation
PyTorch documentation # PyTorch is an optimized tensor library for deep learning using GPUs and CPUs. Features described in this documentation are classified by release status: Stable …
torch.nn.functional — PyTorch 2.9 documentation
Jun 11, 2019 · torch.nn.parallel.data_parallel Evaluate module (input) in parallel across the GPUs given in device_ids.
What is torch.nn really? — PyTorch Tutorials 2.9.0+cu128 …
What is torch.nn really? # Created On: Dec 26, 2018 | Last Updated: Jan 24, 2025 | Last Verified: Nov 05, 2024 Authors: Jeremy Howard, fast.ai. Thanks to Rachel Thomas and Francisco …
Links for torch - download.pytorch.org
torch-2.6.0+cu126-cp310-cp310-linux_aarch64.whl torch-2.6.0+cu126-cp310-cp310-manylinux_2_28_x86_64.whl torch-2.6.0+cu126-cp310-cp310-win_amd64.whl torch …
torch.randn — PyTorch 2.9 documentation
torch.randn # torch.randn(*size, *, generator=None, out=None, dtype=None, layout=torch.strided, device=None, requires_grad=False, pin_memory=False) → Tensor # Returns a tensor filled …