mindspore.ops.Stack

class mindspore.ops.Stack(*args, **kwargs)[source]

Stacks a list of tensors in specified axis.

Stacks the list of input tensors with the same rank R, output is a tensor of rank (R+1).

Given input tensors of shape \((x_1, x_2, ..., x_R)\). Set the number of input tensors as N. If \(0 \le axis\), the shape of the output tensor is \((x_1, x_2, ..., x_{axis}, N, x_{axis+1}, ..., x_R)\).

Parameters: axis (int) – Dimension to stack. Default: 0. Negative values wrap around. The range is [-(R+1), R+1).

Inputs:

input_x (Union[tuple, list]) - A Tuple or list of Tensor objects with the same shape and type.

Outputs:

Tensor. A stacked Tensor with the same type as input_x.

Raises

TypeError – If the data types of elements in input_x are not the same.
ValueError – If the length of input_x is not greater than 1; or if axis is out of the range [-(R+1), R+1); or if the shapes of elements in input_x are not the same.

Supported Platforms:: Ascend GPU CPU

Examples

>>> data1 = Tensor(np.array([0, 1]).astype(np.float32))
>>> data2 = Tensor(np.array([2, 3]).astype(np.float32))
>>> stack = ops.Stack()
>>> output = stack([data1, data2])
>>> print(output)
[[0. 1.]
 [2. 3.]]