PyTorch, developed by Facebook, is a scientific computing library that emerged from the Lua-based Torch project. It is designed to be a Pythonic deep learning library, offering a simple and intuitive API, seamless integration with Python's core functions, and dynamic computational graphs. PyTorch supports ONNX, a vendor-neutral model representation, and TorchScript, a deferred execution "diagram mode" runtime. Key features include fast performance, dynamic computational graphs, and support for CUDA, which enhances network performance. PyTorch is widely used by Facebook and its subsidiaries for deep learning tasks, making it a popular choice for developers. Its ease of debugging, similar layer types to Torch, and fast execution make it a preferred choice for many.PyTorch, developed by Facebook, is a scientific computing library that emerged from the Lua-based Torch project. It is designed to be a Pythonic deep learning library, offering a simple and intuitive API, seamless integration with Python's core functions, and dynamic computational graphs. PyTorch supports ONNX, a vendor-neutral model representation, and TorchScript, a deferred execution "diagram mode" runtime. Key features include fast performance, dynamic computational graphs, and support for CUDA, which enhances network performance. PyTorch is widely used by Facebook and its subsidiaries for deep learning tasks, making it a popular choice for developers. Its ease of debugging, similar layer types to Torch, and fast execution make it a preferred choice for many.