mindspore.ops.sequence_mask

mindspore.ops.sequence_mask(lengths, maxlen=None)[source]

Returns a mask tensor representing the first N positions of each cell.

If lengths has shape [d_1, d_2, …, d_n], then the resulting tensor mask has type dtype and shape [d_1, d_2, …, d_n, maxlen], with mask[i_1, i_2, …, i_n, j] = (j < lengths[i_1, i_2, …, i_n])

Inputs:

  • lengths (Tensor) - Tensor to calculate the mask for. All values in this tensor should be less than or equal to maxlen. Values greater than maxlen will be treated as maxlen. Must be type int32 or int64.

  • maxlen (int) - size of the last dimension of returned tensor. Must be positive and same type as elements in lengths.

Outputs:

One mask tensor of shape lengths.shape + (maxlen,).

Raises

  • TypeError – If lengths is not a Tensor.

  • TypeError – If maxlen is not an int.

  • TypeError – If dtype of lengths is neither int32 nor int64.

Supported Platforms:

GPU

Examples

>>> x = Tensor(np.array([[1, 3], [2, 0]]))
>>> output = C.sequence_mask(x, 3)
>>> print(output)
[[[True, False, False],
  [True, True, True]],
 [[True, True, False],
  [False, False, False]]]