# Source code for mars.tensor.base.atleast_2d

```#!/usr/bin/env python
# -*- coding: utf-8 -*-
# Copyright 1999-2021 Alibaba Group Holding Ltd.
#
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#
# Unless required by applicable law or agreed to in writing, software
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and

import numpy as np

from ...core import ExecutableTuple
from ..datasource import tensor as astensor

[docs]def atleast_2d(*tensors):
"""
View inputs as tensors with at least two dimensions.

Parameters
----------
tensors1, tensors2, ... : array_like
One or more array-like sequences.  Non-tensor inputs are converted
to tensors.  Tensors that already have two or more dimensions are
preserved.

Returns
-------
res, res2, ... : Tensor
A tensor, or list of tensors, each with ``a.ndim >= 2``.
Copies are avoided where possible, and views with two or more
dimensions are returned.

--------
atleast_1d, atleast_3d

Examples
--------
>>> import mars.tensor as mt

>>> mt.atleast_2d(3.0).execute()
array([[ 3.]])

>>> x = mt.arange(3.0)
>>> mt.atleast_2d(x).execute()
array([[ 0.,  1.,  2.]])

>>> mt.atleast_2d(1, [1, 2], [[1, 2]]).execute()
[array([[1]]), array([[1, 2]]), array([[1, 2]])]

"""
new_tensors = []
for x in tensors:
x = astensor(x)
if x.ndim == 0:
x = x[np.newaxis, np.newaxis]
elif x.ndim == 1:
x = x[np.newaxis, :]

new_tensors.append(x)

if len(new_tensors) == 1:
return new_tensors[0]
return ExecutableTuple(new_tensors)
```