#!/usr/bin/env python # -*- coding: utf-8 -*- # Copyright 1999-2020 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, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import numpy as np from ...core import ExecutableTuple from ..datasource import tensor as astensor [docs]def atleast_1d(*tensors): """ Convert inputs to tensors with at least one dimension. Scalar inputs are converted to 1-dimensional tensors, whilst higher-dimensional inputs are preserved. Parameters ---------- tensors1, tensors2, ... : array_like One or more input tensors. Returns ------- ret : Tensor An tensor, or list of tensors, each with ``a.ndim >= 1``. Copies are made only if necessary. See Also -------- atleast_2d, atleast_3d Examples -------- >>> import mars.tensor as mt >>> mt.atleast_1d(1.0).execute() array([ 1.]) >>> x = mt.arange(9.0).reshape(3,3) >>> mt.atleast_1d(x).execute() array([[ 0., 1., 2.], [ 3., 4., 5.], [ 6., 7., 8.]]) >>> mt.atleast_1d(x) is x True >>> mt.atleast_1d(1, [3, 4]).execute() [array([1]), array([3, 4])] """ new_tensors = [] for x in tensors: x = astensor(x) if x.ndim == 0: x = x[np.newaxis] new_tensors.append(x) if len(new_tensors) == 1: return new_tensors[0] return ExecutableTuple(new_tensors)