There is a command group 'az_ml v1 _model'. This group of commands could 'manage machine learning models'. The group of commands has global parameter '--debug' which means 'Increase logging verbosity to show all debug logs.'. The group of commands has global parameter '--help -h' which means 'Show this help message and exit.'. The group of commands has global parameter '--only-show-errors' which means 'Only show errors, suppressing warnings.'. The group of commands has global parameter '--output -o' which means 'Output format.'. The group of commands has global parameter '--query' which means 'JMESPath query string. See <a href="http://jmespath.org/">http://jmespath.org/</a> for more information and examples.'. The group of commands has global parameter '--subscription' which means 'Name or ID of subscription. You can configure the default subscription using `az account set -s NAME_OR_ID`.'. The group of commands has global parameter '--verbose' which means 'Increase logging verbosity. Use --debug for full debug logs.'. This group contains a child command 'az_ml v1 _model_register'.The syntax is: az ml model register --name
                     [--asset-path]
                     [--cc]
                     [--description]
                     [--experiment-name]
                     [--gb]
                     [--gc]
                     [--model-framework]
                     [--model-framework-version]
                     [--model-path]
                     [--output-metadata-file]
                     [--path]
                     [--property]
                     [--resource-group]
                     [--run-id]
                     [--run-metadata-file]
                     [--sample-input-dataset-id]
                     [--sample-output-dataset-id]
                     [--subscription-id]
                     [--tag]
                     [--workspace-name]
                     [-v]. The parameter '--name -n' is required. It is used to name of model to register.. The parameter '--asset-path' is optional. the cloud path where the experiement run stores the model file.. The parameter '--cc --cpu-cores' is optional. the default number of cpu cores to allocate for this model. can be a decimal.. The parameter '--description -d' is optional. description of the model.. The parameter '--experiment-name' is optional. the name of the experiment.. The parameter '--gb --memory-gb' is optional. the default amount of memory (in gb) to allocate for this model. can be a decimal.. The parameter '--gc --gpu-cores' is optional. the default number of gpus to allocate for this model.. The parameter '--model-framework' is optional. framework of the model to register. currently supported frameworks: tensorflow, scikitlearn, onnx, custom, multi.. The parameter '--model-framework-version' is optional. framework version of the model to register (e.g. 1.0.0, 2.4.1).. The parameter '--model-path -p' is optional. full path of the model file to register.. The parameter '--output-metadata-file -t' is optional. path to a json file where model registration metadata will be written. used as input for model deployment.. The parameter '--path' is optional. path to a project folder. default: current directory.. The parameter '--property' is optional. key/value property to add (e.g. key=value ). multiple properties can be specified with multiple --property options.. The parameter '--resource-group -g' is optional. resource group corresponding to the provided workspace.. The parameter '--run-id -r' is optional. the id for the experiment run where model is registered from.. The parameter '--run-metadata-file -f' is optional. path to a json file containing experiement run metadata.. The parameter '--sample-input-dataset-id' is optional. the id for the sample input dataset.. The parameter '--sample-output-dataset-id' is optional. the id for the sample output dataset.. The parameter '--subscription-id' is optional. specifies the subscription id.. The parameter '--tag' is optional. key/value tag to add (e.g. key=value ). multiple tags can be specified with multiple --tag options.. The parameter '--workspace-name -w' is optional. name of the workspace to register this model with.. The parameter '-v' is optional. verbosity flag.. 