mindspore.dataset.text.SlidingWindow

class mindspore.dataset.text.SlidingWindow(width, axis=0)

Construct a tensor from given data (only support 1-D for now), where each element in the dimension axis is a slice of data starting at the corresponding position, with a specified width.

Parameters

• width (int) – The width of the window. It must be an integer and greater than zero.

• axis (int, optional) – The axis along which the sliding window is computed. Default: 0.

Raises

• TypeError – If width is not of type int.

• ValueError – If value of width is not positive.

• TypeError – If axis is not of type int.

Supported Platforms:

CPU

Examples

>>> import mindspore.dataset as ds
>>> import mindspore.dataset.text as text
>>>
>>> # Use the transform in dataset pipeline mode
>>> numpy_slices_dataset = ds.NumpySlicesDataset(data=[[1, 2, 3, 4, 5]], column_names=["col1"])
>>> # Data before
>>> # |     col1     |
>>> # +--------------+
>>> # | [[1, 2, 3, 4, 5]] |
>>> # +--------------+
>>> numpy_slices_dataset = numpy_slices_dataset.map(operations=text.SlidingWindow(3, 0))
>>> for item in numpy_slices_dataset.create_dict_iterator(num_epochs=1, output_numpy=True):
...     print(item["col1"])
[[1 2 3] [2 3 4] [3 4 5]]
>>> # Data after
>>> # |     col1     |
>>> # +--------------+
>>> # |  [[1, 2, 3], |
>>> # |   [2, 3, 4], |
>>> # |   [3, 4, 5]] |
>>> # +--------------+
>>>
>>> # Use the transform in eager mode
>>> data = ["happy", "birthday", "to", "you"]
>>> output = text.SlidingWindow(2, 0)(data)
>>> print(output)
[['happy' 'birthday'] ['birthday' 'to'] ['to' 'you']]

Tutorial Examples:

• Illustration of text transforms