# mars.tensor.concatenate¶

mars.tensor.concatenate(tensors, axis=0)[source]

Join a sequence of arrays along an existing axis.

Parameters
• a1 (sequence of array_like) – The tensors must have the same shape, except in the dimension corresponding to axis (the first, by default).

• a2 (sequence of array_like) – The tensors must have the same shape, except in the dimension corresponding to axis (the first, by default).

• .. (sequence of array_like) – The tensors must have the same shape, except in the dimension corresponding to axis (the first, by default).

• axis (int, optional) – The axis along which the tensors will be joined. Default is 0.

Returns

res – The concatenated tensor.

Return type

Tensor

array_split

Split a tensor into multiple sub-arrays of equal or near-equal size.

split

Split tensor into a list of multiple sub-tensors of equal size.

hsplit

Split tensor into multiple sub-tensors horizontally (column wise)

vsplit

Split tensor into multiple sub-tensors vertically (row wise)

dsplit

Split tensor into multiple sub-tensors along the 3rd axis (depth).

stack

Stack a sequence of tensors along a new axis.

hstack

Stack tensors in sequence horizontally (column wise)

vstack

Stack tensors in sequence vertically (row wise)

dstack

Stack tensors in sequence depth wise (along third dimension)

Examples

>>> import mars.tensor as mt

>>> a = mt.array([[1, 2], [3, 4]])
>>> b = mt.array([[5, 6]])
>>> mt.concatenate((a, b), axis=0).execute()
array([[1, 2],
[3, 4],
[5, 6]])
>>> mt.concatenate((a, b.T), axis=1).execute()
array([[1, 2, 5],
[3, 4, 6]])