(glossary)= # PyTorch Glossary This glossary provides definitions for terms commonly used in PyTorch documentation. ```{glossary} ATen Short for "A Tensor Library". The foundational tensor and mathematical operation library on which all else is built. Compound Kernel Opposed to {term}`Device Kernel`s, Compound kernels are usually device-agnostic and belong to {term}`Compound Operation`s. Compound Operation A Compound Operation is composed of other {term}`Operation`s. Its {term}`Kernel` is usually device-agnostic. Normally it doesn't have its own derivative functions defined. Instead, AutoGrad automatically computes its derivative based on operations it uses. Composite Operation Same as {term}`Compound Operation`. Custom Operation An {term}`Operation` defined by users, usually a {term}`Compound Operation`. For example, this [tutorial](https://pytorch.org/docs/stable/notes/extending.html) details how to create Custom Operations. Device Kernel Device-specific {term}`Kernel` of a {term}`Leaf Operation`. JIT Just-In-Time Compilation. Kernel Implementation of a PyTorch {term}`Operation`, specifying what should be done when an operation executes. Leaf Operation An {term}`Operation` that's considered a basic operation, as opposed to a {term}`Compound Operation`. Leaf Operation always has dispatch functions defined, usually has a derivative function defined as well. Native Operation An {term}`Operation` that comes natively with PyTorch ATen, for example `aten::matmul`. Non-Leaf Operation Same as {term}`Compound Operation`. Operation A unit of work. For example, the work of matrix multiplication is an operation called `aten::matmul`. Scripting Using `torch.jit.script` on a function to inspect source code and compile it as {term}`TorchScript` code. TorchScript Deprecated. An interface to the TorchScript {term}`JIT` compiler and interpreter. Tracing Using `torch.jit.trace` on a function to get an executable that can be optimized using just-in-time compilation. ```