mars.tensor.stack¶

mars.tensor.
stack
(tensors, axis=0, out=None)[source]¶ Join a sequence of tensors along a new axis.
The axis parameter specifies the index of the new axis in the dimensions of the result. For example, if
axis=0
it will be the first dimension and ifaxis=1
it will be the last dimension. Parameters
tensors (sequence of array_like) – Each tensor must have the same shape.
axis (int, optional) – The axis in the result tensor along which the input tensors are stacked.
out (Tensor, optional) – If provided, the destination to place the result. The shape must be correct, matching that of what stack would have returned if no out argument were specified.
 Returns
stacked – The stacked tensor has one more dimension than the input tensors.
 Return type
Tensor
See also
concatenate
Join a sequence of tensors along an existing axis.
split
Split tensor into a list of multiple subtensors of equal size.
block
Assemble tensors from blocks.
Examples
>>> import mars.tensor as mt
>>> arrays = [mt.random.randn(3, 4) for _ in range(10)] >>> mt.stack(arrays, axis=0).shape (10, 3, 4)
>>> mt.stack(arrays, axis=1).shape (3, 10, 4)
>>> mt.stack(arrays, axis=2).shape (3, 4, 10)
>>> a = mt.array([1, 2, 3]) >>> b = mt.array([2, 3, 4]) >>> mt.stack((a, b)).execute() array([[1, 2, 3], [2, 3, 4]])
>>> mt.stack((a, b), axis=1).execute() array([[1, 2], [2, 3], [3, 4]])