Description
Builds tensor computations and dynamic neural networks in Python. It helps machine-learning, scientific, and data projects train models, run inference, use automatic differentiation, and accelerate workloads on supported hardware.
Machine-learning workloads can consume significant CPU, memory, GPU, and energy. Validate datasets, model outputs, privacy, and resource limits before using results in real decisions.