maxframe.tensor.atleast_3d

maxframe.tensor.atleast_3d(*tensors)

View inputs as tensors with at least three dimensions.

Parameters:

• 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.

Returns:

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).

Return type:

Tensor

See also

atleast_1d, atleast_2d

Examples

>>> import maxframe.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)