Metadata-Version: 2.1
Name: azureml-ngc-tools
Version: 0.1.3
Summary: AzureML integration with NGC
Home-page: UNKNOWN
License: BSD
Description: # AzureML NVIDIA GPU Cloud tools
        
        The code contained within this repository allows pulling the images from NVIDIA GPU Cloud (NGC).
        
        ## Installation
        
        To install this package type 
        
        `pip install azureml-ngc-tools`
        
        Alternatively, clone this repository and use python to install.
        
        ```
        git clone https://github.com/.../azureml-ngc-tools.git
        python setup.py install
        ```
        
        ## Configuration
        
        Two configuration files are required:
        
        1. A `json` file that contains the parameters to log in to AzureML Workspace and create Compute Target. **All the parameters shown below need to be provided.**
        
        ```
        {
            "azureml_user":
            {
                "subscription_id": "<YOUR-SUBSCRIPTION-ID>",
                "resource_group": "<YOUR-RESOURCE-GROUP>",
                "workspace_name": "<YOUR-WORKSPACE-NAME>"
            },
            "aml_compute":
            {
                "ct_name":"<NAME-OF-YOUR-COMPUTE-TARGET>",
                "exp_name":"<NAME-OF-YOUR-EXPERIMENT>",
                "vm_name":"<SIZE-OF-THE-AZUREML-VM>",
                "admin_name":"<ADMINISTRATOR-NAME>",
                "min_nodes":<MINIMUM-NUMBER-OF-NODES>,
                "max_nodes":<MAXIMUM-NUMBER-OF-NODES>,
                "vm_priority": "<dedicated|lowpriority>",
                "idle_seconds_before_scaledown":<NUMBER-OF-SECONDS-TO-SCALE-DOWN>,
                "python_interpreter":"<PATH-TO-PYTHON-INTERPRETER>",
                "conda_packages":[<LIST-OF-ADDITIONAL-CONDA-OR-PIP-PACKAGES>],
                "environment_name":"<NAME-OF-ENVIRONMENT>",
                "docker_enabled":<true|false>,
                "user_managed_dependencies":<true|false>,
                "jupyter_port":<JUPYTER-PORT-FOR-FORWARDING>
            }
        }
        
        ```
        
        An example (fictitious):
        
        ```
        {
            "azureml_user":
            {
                "subscription_id": "ef4455fa-3e35-433c-a410-76d7a8a9e793",
                "resource_group": "sample-rg",
                "workspace_name": "sample-ws"
            },
            "aml_compute":
            {
                "ct_name":"sample-ct",
                "exp_name":"sample-exp",
                "vm_name":"Standard_NC6s_v3",
                "admin_name": "sample",
                "min_nodes":0,
                "max_nodes":1,
                "vm_priority": "dedicated",
                "idle_seconds_before_scaledown":300,
                "python_interpreter":"/usr/bin/python",
                "conda_packages":["matplotlib","jupyterlab"],
                "environment_name":"sample_env",
                "docker_enabled":true,
                "user_managed_dependencies":true,
                "jupyter_port":9000
            }
        }
        
        ```
        
        2. A `json` file that contains information about the content you want to download from NGC. **The `base_dockerfile` parameter shown below needs to be provided.**
        
        ```
        {
            "base_dockerfile":"<URI-TO-NGC-CONTAINER>",
            "additional_content":
            [
                <ADDITIONAL CONTENT>
            ]
        }
        ```
        
        An example:
        
        ```
        {
            "base_dockerfile":"nvcr.io/nvidia/clara-train-sdk:v3.0",
            "additional_content":
            [
                {
                    "url":"https://api.ngc.nvidia.com/v2/resources/nvidia/med/getting_started/versions/1/zip",
                    "filename":"clarasdk.zip",
                    "localdirectory":"clara",
                    "computedirectory":"clara",
                    "zipped":true
                }
            ]
        }
        ```
        
        ## Usage
        Assuming that the AzureML config file is `user_config.json` and the NGC config file is `ngc_app.json`, and both of the files are located in the same folder, to create the cluster run the following code
        
        `azureml-ngc-tools --login user_config.json --app ngc_app.json`
Keywords: azureml,ngc,gpu
Platform: UNKNOWN
Requires-Python: >=3.5
Description-Content-Type: text/markdown
