mars.tensor.identity(n, dtype=None, sparse=False, gpu=None, chunk_size=None)[source]#

Return the identity tensor.

The identity tensor is a square array with ones on the main diagonal.

  • n (int) – Number of rows (and columns) in n x n output.

  • dtype (data-type, optional) – Data-type of the output. Defaults to float.

  • sparse (bool, optional) – Create sparse tensor if True, False as default

  • gpu (bool, optional) – Allocate the tensor on GPU if True, False as default

  • chunks (int or tuple of int or tuple of ints, optional) – Desired chunk size on each dimension


outn x n array with its main diagonal set to one, and all other elements 0.

Return type



>>> import mars.tensor as mt
>>> mt.identity(3).execute()
array([[ 1.,  0.,  0.],
       [ 0.,  1.,  0.],
       [ 0.,  0.,  1.]])