mindspore.numpy.dstack

mindspore.numpy.dstack(tup)[source]

Stacks tensors in sequence depth wise (along the third axis). This is equivalent to concatenation along the third axis. 1-D tensors \((N,)\) should be reshaped to \((1,N,1)\). 2-D tensors \((M,N)\) should be reshaped to \((M,N,1)\) before concatenation.

Parameters: tup (Union[Tensor, tuple, list]) – A sequence of tensors. The tensors must have the same shape along all but the third axis. 1-D or 2-D tensors must have the same shape.
Returns: Stacked Tensor, formed by stacking the given tensors.

Supported Platforms:: Ascend GPU CPU

Raises

TypeError – If tup is not Tensor, list or tuple.
ValueError – If tup is empty.

Examples

>>> import mindspore.numpy as np
>>> x1 = np.array([1, 2, 3]).astype('float32')
>>> x2 = np.array([4, 5, 6]).astype('float32')
>>> output = np.dstack((x1, x2))
>>> print(output)
[[[1. 4.]
  [2. 5.]
  [3. 6.]]]