dataflow-example-ml-inference/metadata.json at main · st81/dataflow-example-ml-inference · GitHub

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{
    "name": "Dataflow example ml inference.",
    "description": "This example pipeline runs a model inference on a dataset using a trained model.",
    "parameters": [
        {
            "name": "dataset_csv_path",
            "label": "Dataset CSV path",
            "helpText": "The path to the dataset CSV file. Must be a GCS path.",
            "isOptional": false
        },
        {
            "name": "dataset_img_root",
            "label": "Dataset image root",
            "helpText": "The root path to the dataset images. Must be a GCS path.",
            "isOptional": false
        },
        {
            "name": "model_checkpoint_path",
            "label": "Model checkpoint path",
            "helpText": "The path to the model checkpoint file. Must be a GCS path.",
            "isOptional": false
        },
        {
            "name": "device",
            "label": "Device",
            "helpText": "The device to run the model on.",
            "isOptional": true
        },
        {
            "name": "output_table_id",
            "label": "Output table ID",
            "helpText": "BigQuery output table ID.",
            "isOptional": false
        },
        {
            "name": "autoscaling_algorithm",
            "label": "Autoscaling algorithm",
            "helpText": "The autoscaling algorithm to use.",
            "isOptional": true
        },
        {
            "name": "dataflow_service_option",
            "label": "Dataflow service option",
            "helpText": "The Dataflow service option to use.",
            "isOptional": true
        },
        {
            "name": "disk_size_gb",
            "label": "Disk size GB",
            "helpText": "The disk size in GB to use.",
            "isOptional": true
        }
    ]
}