NVIDIA TAO Toolkit v4.0
NVIDIA TAO Release tlt.40

Remote Client

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

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pip3 install -y nvidia-tao-client

Below is a detectnet_v2 example of shared storage content.

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

The command line depends on the following environment variables:

  • BASE_URL

  • USER

  • TOKEN

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

The tutorial notebooks provide examples that demonstrate the various workflows.

  1. Download the resource using the NGC CLI.

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    ngc registry resource download-version "nvidia/tao/tao-getting-started:4.0.0"


  2. Find tutorial notebooks (.ipynb files).

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    cd tao-getting-started_v4.0.0/notebooks/tao_api_starter_kit/client


  3. Serve these Notebook examples using Jupyter.

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    pip3 install jupyter notebook jupyter notebook --ip 0.0.0.0


© Copyright 2022, NVIDIA.. Last updated on Mar 23, 2023.