Remote Client

NVIDIA TAO Release 30.2202

The remote client allows someone to create model experiments using the command line instead of relying on API calls.

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pip3 install -y nvidia-tao-client

The remote client does not currently support the following features:

  • User authentication

  • Protect stored experiments among users

Below is a detectnet_v2 example of shared storage content.

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shared └── users     ├── 1a40ddb6-d389-4c39-9b40-eaa948ee508d     │   ├── metadata.json     │   ├── datasets     │   │   ├── 78cff931-e867-4e9c-b8a7-30fa243e433c     │   │   │   ├── metadata.json     │   │   │   ├── specs     │   │   │   │   └── convert.json     │   │   │   ├── images     │   │   │   │ ├── 000000.jpg     │   │   │   │ └── …     │   │   │   ├── labels     │   │   │   │   ├── 000000.txt     │   │   │   │   └── …     │   │   │   ├── 444fed7a-ac3f-4499-8a57-0234a43c752d     │   │   │   │ ├── status.json     │   │   │   │   └── …   │   │   │   └── tfrecords     │   │   │       └── …     │   │   └── …     │   └── models     │       ├── cdf387d2-067e-4935-be9d-7facbc851f60     │       │   ├── metadata.json     │       │   ├── specs     │       │   │   ├── train.json     │       │   │   └── …     │       │   ├── 444fed7a-ac3f-4499-8a57-0234a43c754e     │     │   │ ├── status.json     │     │   │   └── …     │       │   └── experiment_dir_unpruned     │       │       └── …     │       └── …     └── …

The command line is composed of:

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$ tao-client <network> <action> <args>

For example:

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$ tao-client detectnet-v2 dataset-convert --id 042559ec-ab3e-438d-9c94-2cab38f76efc

Note

You can always use –help argument to retrieve the command usage information.

To list supported networks:

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$ tao-client –help

To list supported detectnet-v2 actions:

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$ tao-client detectnet-v2 –help

To list detectnet-v2 dataset-convert arguments:

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$ tao-client detectnet-v2 dataset-convert --help

For an example that demonstrates the Object Detection workflow, please find tutorial notebook api_tutorials/client/detectnet_v2.ipynb from resource archive: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/resources/cv_samples

For an example that demonstrates the TTS finetuning workkflow, please find tutorial notebook api_tutorials/client/tts.ipynb from resource archive: https://catalog.ngc.nvidia.com/orgs/nvidia/teams/tao/resources/texttospeech_notebook

© Copyright 2022, NVIDIA.. Last updated on Jun 3, 2022.