jax.numpy.vstack(tup, dtype=None)[source]#

Stack arrays in sequence vertically (row wise).

LAX-backend implementation of numpy.vstack().

Original docstring below.

This is equivalent to concatenation along the first axis after 1-D arrays of shape (N,) have been reshaped to (1,N). Rebuilds arrays divided by vsplit.

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.

np.row_stack is an alias for vstack. They are the same function.

  • tup (sequence of ndarrays) – The arrays must have the same shape along all but the first axis. 1-D arrays must have the same length.

  • dtype (str or dtype) – If provided, the destination array will have this dtype. Cannot be provided together with out.


stacked – The array formed by stacking the given arrays, will be at least 2-D.

Return type: