Source code for mars.tensor.arithmetic.square

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# 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
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# See the License for the specific language governing permissions and
# limitations under the License.

import numpy as np

from ... import opcodes as OperandDef
from ..utils import infer_dtype
from .core import TensorUnaryOp
from .utils import arithmetic_operand

class TensorSquare(TensorUnaryOp):
    _op_type_ = OperandDef.SQUARE
    _func_name = "square"

[docs]@infer_dtype(np.square) def square(x, out=None, where=None, **kwargs): """ Return the element-wise square of the input. Parameters ---------- x : array_like Input data. out : Tensor, None, or tuple of tensor and None, optional A location into which the result is stored. If provided, it must have a shape that the inputs broadcast to. If not provided or `None`, a freshly-allocated array is returned. A tuple (possible only as a keyword argument) must have length equal to the number of outputs. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs Returns ------- out : Tensor Element-wise `x*x`, of the same shape and dtype as `x`. Returns scalar if `x` is a scalar. See Also -------- sqrt power Examples -------- >>> import mars.tensor as mt >>> mt.square([-1j, 1]).execute() array([-1.-0.j, 1.+0.j]) """ op = TensorSquare(**kwargs) return op(x, out=out, where=where)