mindspore.dataset.transforms.Unique

class mindspore.dataset.transforms.Unique[source]

Perform the unique operation on the input tensor, only support transform one column each time.

Return 3 tensor: unique output tensor, index tensor, count tensor.

Output tensor contains all the unique elements of the input tensor in the same order that they occur in the input tensor.
Index tensor that contains the index of each element of the input tensor in the unique output tensor.
Count tensor that contains the count of each element of the output tensor in the input tensor.

Note

Call batch op before calling this function.

Raises: RuntimeError – If given Tensor has two columns.

Supported Platforms:: CPU

Examples

>>> import mindspore.dataset as ds
>>> import mindspore.dataset.transforms as transforms
>>> # Data before
>>> # |  x                 |
>>> # +--------------------+
>>> # | [[0,1,2], [1,2,3]] |
>>> # +--------------------+
>>> data = [[[0,1,2], [1,2,3]]]
>>> dataset = ds.NumpySlicesDataset(data, ["x"])
>>> dataset = dataset.map(operations=transforms.Unique(),
...                       input_columns=["x"],
...                       output_columns=["x", "y", "z"])
>>> # Data after
>>> # |  x      |  y              |z        |
>>> # +---------+-----------------+---------+
>>> # | [0,1,2,3] | [0,1,2,1,2,3] | [1,2,2,1]
>>> # +---------+-----------------+---------+