dali-dynamic-mode

DALI Dynamic Mode Purpose Guide AI agents in writing, reviewing, and migrating code that uses DALI's imperative dynamic-mode API, nvidia.dali.experimental.dynamic ( ndd ). Instructions Import dynamic mode as nvidia.dali.experimental.dynamic as ndd and write code as direct ndd calls in ordinary Python; do not use pipeline-mode APIs such as Pipeline , @pipeline_def , pipe.build() , or pipe.run() . Treat readers as stateful: create them once, reuse them across epochs, and pass batch_size to next_epoch(...) . Pass explicit batch_size to random ops; there is no pipeline-level batch size to inherit. Use dynamic-mode API conventions: device="gpu" instead of pipeline-mode "mixed" , Batch.tensors[...] for sample selection, and Batch.slice[...] for per-sample slicing. Prerequisites To run or validate code, NVIDIA DALI must be installed with dynamic mode importable as nvidia.dali.experimental.dynamic . GPU decode or GPU operators require a CUDA-capable DALI build and an available NVIDIA GPU/driver. Framework conversion examples require the target framework installed, such as PyTorch for .torch() . Show more Installs 516 Repository nvidia/skills GitHub Stars 1.3K First Seen May 20, 2026 Security Audits Gen Agent Trust Hub Pass Socket Pass Snyk Pass