mars.tensor.
atleast_3d
View inputs as tensors with at least three dimensions.
tensors1 (array_like) – One or more tensor-like sequences. Non-tensor inputs are converted to tensors. Tensors that already have three or more dimensions are preserved.
tensors2 (array_like) – One or more tensor-like sequences. Non-tensor inputs are converted to tensors. Tensors that already have three or more dimensions are preserved.
.. (array_like) – One or more tensor-like sequences. Non-tensor inputs are converted to tensors. Tensors that already have three or more dimensions are preserved.
res1, res2, … – A tensor, or list of tensors, each with a.ndim >= 3. Copies are avoided where possible, and views with three or more dimensions are returned. For example, a 1-D tensor of shape (N,) becomes a view of shape (1, N, 1), and a 2-D tensor of shape (M, N) becomes a view of shape (M, N, 1).
a.ndim >= 3
(N,)
(1, N, 1)
(M, N)
(M, N, 1)
Tensor
See also
atleast_1d, atleast_2d
atleast_1d
atleast_2d
Examples
>>> import mars.tensor as mt
>>> mt.atleast_3d(3.0).execute() array([[[ 3.]]])
>>> x = mt.arange(3.0) >>> mt.atleast_3d(x).shape (1, 3, 1)
>>> x = mt.arange(12.0).reshape(4,3) >>> mt.atleast_3d(x).shape (4, 3, 1)
>>> for arr in mt.atleast_3d([1, 2], [[1, 2]], [[[1, 2]]]).execute(): ... print(arr, arr.shape) ... [[[1] [2]]] (1, 2, 1) [[[1] [2]]] (1, 2, 1) [[[1 2]]] (1, 1, 2)