Stack tensors in sequence depth wise (along third axis).
This is equivalent to concatenation along the third axis after 2-D tensors of shape (M,N) have been reshaped to (M,N,1) and 1-D arrays of shape (N,) have been reshaped to (1,N,1). Rebuilds arrays divided by dsplit.
This function makes most sense for arrays with up to 3 dimensions. For instance, for pixel-data with a height (first axis), width (second axis), and r/g/b channels (third axis). The functions concatenate, stack and block provide more general stacking and concatenation operations.
tup (sequence of tensors) – The tensors must have the same shape along all but the third axis. 1-D or 2-D arrays must have the same shape.
stacked – The array formed by stacking the given tensors, will be at least 3-D.
- Return type
>>> import mars.tensor as mt
>>> a = mt.array((1,2,3)) >>> b = mt.array((2,3,4)) >>> mt.dstack((a,b)).execute() array([[[1, 2], [2, 3], [3, 4]]])
>>> a = mt.array([,,]) >>> b = mt.array([,,]) >>> mt.dstack((a,b)).execute() array([[[1, 2]], [[2, 3]], [[3, 4]]])