dataset_consumption_config: Represent how to deliver the dataset to a compute target.

In azuremlsdk: Interface to the 'Azure Machine Learning' 'SDK'

Description

Represent how to deliver the dataset to a compute target.

Usage

dataset_consumption_config(
  name,
  dataset,
  mode = "direct",
  path_on_compute = NULL
)

Arguments

name	The name of the dataset in the run, which can be different to the registered name. The name will be registered as environment variable and can be used in data plane.
dataset	The dataset that will be consumed in the run.
mode	Defines how the dataset should be delivered to the compute target. There are three modes: 'direct': consume the dataset as dataset. 'download': download the dataset and consume the dataset as downloaded path. 'mount': mount the dataset and consume the dataset as mount path.
path_on_compute	The target path on the compute to make the data available at. The folder structure of the source data will be kept, however, we might add prefixes to this folder structure to avoid collision.

Value

The DatasetConsumptionConfig object.

Examples

est <- estimator(source_directory = ".",
                 entry_script = "train.R",
                 inputs = list(dataset_consumption_config('mydataset', dataset, mode = 'download')),
                 compute_target = compute_target)

See Also

estimator

azuremlsdk documentation built on Oct. 23, 2020, 8:22 p.m.