mindspore.ops.GetNext

class mindspore.ops.GetNext(types, shapes, output_num, shared_name)[source]

Returns the next element in the dataset queue.

Note

The GetNext operation needs to be associated with network and it also depends on the ‘dataset’ interface, For example, please refer to mindspore.dataset.MnistDataset . it can’t be used directly as a single operation. For details, please refer to mindspore.connect_network_with_dataset source code.

Parameters

  • types (list[mindspore.dtype]) – The type of the outputs.

  • shapes (list[tuple[int]]) – The dimensionality of the outputs.

  • output_num (int) – The output number, length of types and shapes.

  • shared_name (str) – Queue name to fetch the data.

Inputs:

No inputs.

Outputs:

tuple[Tensor], the output of dataset. The shape is described in shapes and the type is described in types.

Supported Platforms:

Ascend GPU

Examples

>>> import mindspore
>>> from mindspore import ops
>>> from mindspore import dataset as ds
>>> from mindspore.common import dtype as mstype
>>> data_path = "/path/to/MNIST_Data/train/"
>>> train_dataset = ds.MnistDataset(data_path, num_samples=10)
>>> dataset_helper = mindspore.DatasetHelper(train_dataset, dataset_sink_mode=True)
>>> dataset = dataset_helper.iter.dataset
>>> dataset_types, dataset_shapes = dataset_helper.types_shapes()
>>> queue_name = dataset.__transfer_dataset__.queue_name
>>> get_next = ops.GetNext(dataset_types, dataset_shapes, len(dataset_types), queue_name)
>>> data, label = get_next()
>>> relu = ops.ReLU()
>>> result = relu(data.astype(mstype.float32))
>>> print(result.shape)
(28, 28, 1)