Agent skill · NVIDIA
dali-dynamic-mode
DALI imperative dynamic mode (`nvidia.dali.experimental.dynamic`, ndd): use when working on ndd code or migrating pipelines; skip pipeline-only tasks.
What it needs
About 8k tokens when loaded.
What this skill does
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, @pipelinedef, pipe.build(), or pipe.run(). Treat readers as stateful: create them once, reuse them across epochs, and pass batchsize to nextepoch(...). Pass explicit batchsize 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. Use .torch() to convert a tensor or batch to a PyTorch tensor. Use pad=True for batches with variable shapes. 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(). Introduction Dynamic mode is DALI's imperative Python API. It lets code call DALI operators directly from normal Python control flow instead of building and running a pipeline graph. Core Data Types Tensor -- single sample Supports dlpack, cudaarrayinterface, array, arithmetic operators. Batch -- collection of samples (variable shapes OK) Batch has no getitem -- batch[i] raises TypeError because indexing is ambiguous (sample selection vs. per-sample slicing). …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills NVIDIA/dali-dynamic-mode