PipelineDataset Class

Acts as an adapter for Dataset and Pipeline.

Note

This class is deprecated. Learn how to use dataset with pipeline, see https://aka.ms/pipeline-with-dataset.

This is an internal class. You should not create this class directly but rather call the as_* instance methods on the Dataset or the OutputDatasetConfig classes.

Act as an adapter for Dataset and Pipeline.

This is an internal class. You should not create this class directly but rather call the as_* instance methods on the Dataset or the OutputDatasetConfig classes.

Inheritance
builtins.object
PipelineDataset

Constructor

PipelineDataset(dataset=None, name=None, bind_mode='mount', path_on_compute=None, overwrite=False, parameter_name=None)

Parameters

dataset
Dataset
default value: None

The dataset that will be used as the input to the step.

name
str
default value: None

The name of the input in the pipeline.

bind_mode
str
default value: mount

How the dataset should be made available, either mount or download.

path_on_compute
str
default value: None

The path on the compute where the data will be made available.

overwrite
bool
default value: False

Whether to overwrite existing data or not.

parameter_name
str
default value: None

The parameter name of the dataset. This is used for published pipeline.

dataset
Union[<xref:azureml.core.Datase> or AbstractDataset, OutputDatasetConfig]
Required

The dataset that will be used as the input to the step.

name
str
Required

The name of the input in the pipeline.

bind_mode
str
Required

How the dataset should be made available, either mount or download.

path_on_compute
str
Required

The path on the compute where the data will be made available.

overwrite
bool
Required

Whether to overwrite existing data or not.

Methods

create

Create a PipelineDataset from an Azure Machine Learning Dataset.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

default_name

Get the default port name of a dataset/dataset definition.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

is_dataset

Determine whether the input is a dataset or a dataset definition.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

validate_dataset

Validate the state of the dataset.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

It will log a warning if the dataset is deprecated and throws an error if the datasaet is archived.

create

Create a PipelineDataset from an Azure Machine Learning Dataset.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

static create(dataset, name=None, parameter_name=None)

Parameters

dataset
Union[Dataset, DatasetConsumptionConfig, PipelineDataset]
Required

The dataset to create the PipelineDataset from.

name
str
default value: None

The name of the input dataset. If None, a name will be derived based on the type of the input.

parameter_name
str
default value: None

The pipeline parameter name.

Returns

The created PipelineDataset.

Return type

default_name

Get the default port name of a dataset/dataset definition.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

static default_name(dataset)

Parameters

dataset
object
Required

The dataset to calculate the name from.

Returns

The name.

Return type

str

is_dataset

Determine whether the input is a dataset or a dataset definition.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

static is_dataset(dset)

Parameters

dset
object
Required

The input.

Returns

Whether input is a dataset or a dataset definition.

Return type

validate_dataset

Validate the state of the dataset.

Note

This method is deprecated. Learn how to use dataset with pipeline, see

https://aka.ms/pipeline-with-dataset.

It will log a warning if the dataset is deprecated and throws an error if the datasaet is archived.

static validate_dataset(dset)

Parameters

dset
Union[Dataset, DatasetConsumptionConfig]
Required

The dataset to be verified.

Attributes

bind_mode

Get how the dataset should be made available.

Returns

The bind mode.

Return type

str

dataset

Get the dataset this input is binded to.

Returns

The dataset.

Return type

Union[Dataset, <xref:azureml.data.abstract_dataset.AbstractDataset,azureml.data.output_dataset_config.OutputDatasetConfig>]

dataset_id

Get the dataset ID.

Returns

The dataset ID.

Return type

str

dataset_version

Get the dataset definition's version.

Returns

The dataset version.

Return type

str

name

Get the name of the input.

Returns

The name.

Return type

str

overwrite

Get value indicating whether to overwrite existing data.

Returns

Overwrite or not.

Return type

parameter_name

Get the pipeline parameter name of this pipeline dataset.

Returns

The parameter name.

Return type

str

path_on_compute

Get the path where the data will be made available on the compute.

Returns

The path on compute.

Return type

str

saved_dataset_id

Return the saved ID of the dataset in the PipelineDataset.

Returns

The saved ID of the dataset.

Return type

str

workspace

Get the workspace the dataset belongs to.

Returns

The workspace.

Return type