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cudnn

CONTAINERS IMAGES RUN BUILD

CONTAINERS
cudnn:8.9
   Builds cudnn-89_jp60
   Requires L4T ['==36.*']
   Dependencies build-essential cuda:12.2
   Dependants tensorrt:8.6
   Dockerfile Dockerfile
   Images dustynv/cudnn:8.9-r36.2.0 (2023-12-05, 4.9GB)
cudnn:9.0
   Requires L4T ['==36.*']
   Dependencies build-essential cuda:12.4
   Dependants tensorrt:10.0
   Dockerfile Dockerfile
cudnn
   Requires L4T ['<36']
   Dependencies build-essential cuda
   Dependants audiocraft auto_awq:0.2.4 auto_gptq:0.7.1 awq:0.1.0 bitsandbytes bitsandbytes:builder ctranslate2:4.2.0 ctranslate2:4.2.0-builder ctranslate2:master ctranslate2:master-builder deepstream efficientvit exllama:0.0.14 exllama:0.0.15 faiss_lite faster-whisper flash-attention:2.5.6 flash-attention:2.5.6-builder flash-attention:2.5.7 flash-attention:2.5.7-builder gptq-for-llama gstreamer jetson-inference jetson-utils l4t-diffusion l4t-ml l4t-pytorch l4t-tensorflow:tf1 l4t-tensorflow:tf2 langchain langchain:samples llama-index llama_cpp:0.2.57 llava minigpt4 mlc:0.1.0 mlc:0.1.0-builder mlc:0.1.1 mlc:0.1.1-builder nanodb nanoowl nanosam nemo onnxruntime:1.11 onnxruntime:1.11-builder onnxruntime:1.16.3 onnxruntime:1.16.3-builder onnxruntime:1.17 onnxruntime:1.17-builder onnxruntime:1.19 onnxruntime:1.19-builder openai-triton openai-triton:builder opencv:4.5.0 opencv:4.5.0-builder opencv:4.8.1 opencv:4.8.1-builder opencv:4.9.0 opencv:4.9.0-builder optimum piper-tts pytorch:1.10 pytorch:1.9 pytorch:2.0 pytorch:2.0-builder pytorch:2.1 pytorch:2.1-builder pytorch:2.2 pytorch:2.2-builder pytorch:2.3 pytorch:2.3-builder raft ros:foxy-desktop ros:foxy-ros-base ros:foxy-ros-core ros:galactic-desktop ros:galactic-ros-base ros:galactic-ros-core ros:humble-desktop ros:humble-ros-base ros:humble-ros-core ros:iron-desktop ros:iron-ros-base ros:iron-ros-core ros:melodic-desktop ros:melodic-ros-base ros:melodic-ros-core ros:noetic-desktop ros:noetic-ros-base ros:noetic-ros-core sam stable-diffusion stable-diffusion-webui tam tensorflow tensorflow2 tensorrt tensorrt_llm:0.10.dev0 tensorrt_llm:0.10.dev0-builder tensorrt_llm:0.5 tensorrt_llm:0.5-builder text-generation-inference text-generation-webui:1.7 text-generation-webui:6a7cd01 text-generation-webui:main torch2trt torch_tensorrt torchaudio:0.10.0 torchaudio:0.10.0-builder torchaudio:0.9.0 torchaudio:0.9.0-builder torchaudio:2.0.1 torchaudio:2.0.1-builder torchaudio:2.1.0 torchaudio:2.1.0-builder torchaudio:2.2.2 torchaudio:2.2.2-builder torchaudio:2.3.0 torchaudio:2.3.0-builder torchvision:0.10.0 torchvision:0.11.1 torchvision:0.15.1 torchvision:0.16.2 torchvision:0.17.2 torchvision:0.18.0 transformers transformers:git transformers:nvgpt tritonserver tvm voicecraft whisper whisperx wyoming-piper:master wyoming-whisper:latest xformers:0.0.26 xformers:0.0.26-builder xtts zed
   Images dustynv/cudnn:8.9-r36.2.0 (2023-12-05, 4.9GB)
CONTAINER IMAGES
Repository/Tag Date Arch Size
  dustynv/cudnn:8.9-r36.2.0 2023-12-05 arm64 4.9GB

Container images are compatible with other minor versions of JetPack/L4T:
    • L4T R32.7 containers can run on other versions of L4T R32.7 (JetPack 4.6+)
    • L4T R35.x containers can run on other versions of L4T R35.x (JetPack 5.1+)

RUN CONTAINER

To start the container, you can use jetson-containers run and autotag, or manually put together a docker run command:

# automatically pull or build a compatible container image
jetson-containers run $(autotag cudnn)

# or explicitly specify one of the container images above
jetson-containers run dustynv/cudnn:8.9-r36.2.0

# or if using 'docker run' (specify image and mounts/ect)
sudo docker run --runtime nvidia -it --rm --network=host dustynv/cudnn:8.9-r36.2.0

jetson-containers run forwards arguments to docker run with some defaults added (like --runtime nvidia, mounts a /data cache, and detects devices)
autotag finds a container image that's compatible with your version of JetPack/L4T - either locally, pulled from a registry, or by building it.

To mount your own directories into the container, use the -v or --volume flags:

jetson-containers run -v /path/on/host:/path/in/container $(autotag cudnn)

To launch the container running a command, as opposed to an interactive shell:

jetson-containers run $(autotag cudnn) my_app --abc xyz

You can pass any options to it that you would to docker run, and it'll print out the full command that it constructs before executing it.

BUILD CONTAINER

If you use autotag as shown above, it'll ask to build the container for you if needed. To manually build it, first do the system setup, then run:

jetson-containers build cudnn

The dependencies from above will be built into the container, and it'll be tested during. Run it with --help for build options.