maxframe.tensor.concatenate#

maxframe.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

See also

stack: Stack a sequence of tensors along a new axis.
vstack: Stack tensors in sequence vertically (row wise)

Examples

>>> import maxframe.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]])

maxframe.tensor.concatenate#

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