xorbits._mars.tensor.base.atleast_2d 源代码
# Copyright 2022-2023 XProbe Inc.
# derived from copyright 1999-2021 Alibaba Group Holding Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
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import numpy as np
from ...core import ExecutableTuple
from ..datasource import tensor as astensor
[文档]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.
See Also
--------
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)