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What is PyTorch? Nedir?

PyTorch is a popular deep learning framework developed by Facebook (Meta) used for research and production.

Release Year: 2016Facebook AI Research (Meta)

PyTorch was developed and open-sourced by Facebook AI Research (FAIR) in 2016. As the Python version of the Torch library, PyTorch quickly became popular among researchers with its dynamic computation graph (eager execution) approach. PyTorch's 'define-by-run' philosophy allows the computation graph to be built dynamically at runtime. This simplifies debugging and allows Python's standard control flow constructs (if, for, while) to be used directly in models. The autograd system provides powerful and flexible automatic differentiation. The PyTorch ecosystem is rich: torchvision (image processing), torchaudio (audio processing), torchtext (text processing), PyTorch Lightning (training loop abstraction), and Hugging Face Transformers (NLP models). torch.compile() introduced with PyTorch 2.0 improves model compilation performance. The vast majority of academic publications use PyTorch. Companies like Tesla, OpenAI, Microsoft, Meta, and Uber prefer PyTorch for AI projects. It has become the de facto standard framework for AI research.

Use Cases

AI research, Deep learning models, Computer vision, Natural language processing, Generative AI

Pros

Intuitive and Pythonic API, Dynamic computation graph, De facto standard in academia, Strong community and Hugging Face integration, Easy debugging

Cons

Weaker mobile/embedded deployment than TensorFlow, More complex production deployment, No built-in visualization like TensorBoard, Memory optimization requires attention