Product & software
PyTorch
PyTorch is a framework for tensor computation and machine learning. It provides building blocks for defining models, computing gradients, and training neural networks, along with an ecosystem of libraries and deployment-related tools.
At a glance
- Primary focus
- Tensor computation and model training
- Category
- machine learning
Overview
PyTorch is a framework for tensor computation and machine learning. It provides building blocks for defining models, computing gradients, and training neural networks, along with an ecosystem of libraries and deployment-related tools.
How it is used
A typical training workflow loads data, computes model predictions, evaluates a loss, and updates parameters through automatic differentiation. Tensors are the central data structure used throughout that process.
A useful distinction
A framework supplies computation and training tools; it does not determine whether a dataset or model is appropriate. Evaluation, data quality, and deployment constraints remain separate engineering tasks.
Sources and review
MOOR's explanatory text is supported by the following source links.
- PyTorch: official overview — PyTorch
- PyTorch: documentation and further reading — PyTorch