Remote Client - NVIDIA Docs

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

Installation

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            pip3 install -y nvidia-tao-client

Storage Topology

Below is a Dino example of shared storage content:

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            shared
└── orgs
    ├── org_name
        ├── datasets
        │   ├── 23776785-f9e7-43a4-97c8-7954c892160f
        │   │   ├── jobs_metadata
        │   │   ├── metadata.json
        │   │   └── metadata_lock.lock
        │   ├── afa1d60b-5c70-425a-ae1b-583487064f68
        │   │   ├── jobs_lock.lock
        │   │   ├── jobs_metadata
        │   │   │   ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b.json
        │   │   │   └── 4bf19b39-a78d-4331-8bc1-2f83396bc05b_lock.lock
        │   │   ├── jobs.yaml
        │   │   ├── metadata.json
        │   │   └── metadata_lock.lock
        │   └── …
        ├── experiments
        │   └── 7ec1aaea-1bae-45df-b4eb-aae780a566cc
        │   │   ├── jobs_lock.lock
        │   │   ├── jobs_metadata
        │   │   │   ├── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be.json
        │   │   │   └── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be_lock.lock
        │   │   ├── jobs.yaml
        │   │   ├── metadata.json
        │   │   └── metadata_lock.lock
        │   └── …
        ├── users
        │   └── 5f931ba3-d448-54fe-955c-a63795b01c98
        │   │   ├── jobs
        │   │   │   ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b
        │   │   │   │   └── status.json
        │   │   │   └── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be
        │   │   │       └── status.json
        │   │   ├── logs
        │   │   │   └── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be.txt
        │   │   ├── metadata.json
        │   │   ├── metadata_lock.lock
        │   │   ├── metadata_token.json
        │   │   ├── metadata_token_lock.lock
        │   │   └── specs
        │   │       ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b-convert_efficientdet_tf2-spec.json
        │   │       ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b-convert_efficientdet_tf2-spec_lock.lock
        │   │       ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b_lock.lock
        │   │       ├── 4bf19b39-a78d-4331-8bc1-2f83396bc05b.yaml
        │   │       ├── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be_lock.lock
        │   │       ├── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be-train-spec.json
        │   │       ├── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be-train-spec_lock.lock
        │   │       └── 794cc10b-458d-4fe7-bfd9-3c5598fbf1be.yaml
        │   └── …
        └── workspaces
            ├── 49d30d91-1515-4adb-813c-65cadb47d2f9
            │   ├── jobs_metadata
            │   ├── metadata.json
            │   └── metadata_lock.lock
            └── …

CLI Specs

User authentication is based on the NGC API KEY and can be done with the following command:

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            BASE_URL=https://IP_of_machine_deployed/api/v1

NGC_API_KEY=zZYtczM5amdtdDcwNjk0cnA2bGU2bXQ3bnQ6NmQ4NjNhMDItMTdmZS00Y2QxLWI2ZjktNmE5M2YxZTc0OGyS

$ tao-client login --ngc-api-key $NGC_API_KEY --ngc-org-name ea-tlt

After authentication, the command line syntax is:

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

For example:

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            $ tao-client dino experiment-run-action --action train --id 042559ec-ab3e-438d-9c94-2cab38f76efc --specs '<json_loadable_specs_string_from_get_spec_action>'

Note

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

To list supported networks:

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            $ tao-client -–help

To list supported Dino actions:

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            $ tao-client dino --help

Examples

The tutorial notebooks provide examples that demonstrate the various workflows.

Download the resource using the NGC CLI.

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            ngc registry resource download-version "nvidia/tao/tao-getting-started:5.5.0"

Find tutorial notebooks (.ipynb files).

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            cd tao-getting-started_v5.5.0/notebooks/tao_api_starter_kit/client

Instead of using NGC, the tutorial notebooks can be downloaded from the machine where TAO API is deployed. You can obtain them using:

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            wget https://<ip_of_hosted_machine>:<nginx_service_forwarded_port>/tao_api_notebooks.zip
unzip tao_api_notebooks.zip
cd cli

Serve these Notebook examples using Jupyter.

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            pip3 install jupyter notebook
jupyter notebook --ip 0.0.0.0