Source code for mars.tensor.arithmetic.hypot

#!/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
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import numpy as np

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

class TensorHypot(TensorBinOp):
    _op_type_ = OperandDef.HYPOT
    _func_name = "hypot"

[docs]@infer_dtype(np.hypot) def hypot(x1, x2, out=None, where=None, **kwargs): """ Given the "legs" of a right triangle, return its hypotenuse. Equivalent to ``sqrt(x1**2 + x2**2)``, element-wise. If `x1` or `x2` is scalar_like (i.e., unambiguously cast-able to a scalar type), it is broadcast for use with each element of the other argument. (See Examples) Parameters ---------- x1, x2 : array_like Leg of the triangle(s). 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 ------- z : Tensor The hypotenuse of the triangle(s). Examples -------- >>> import mars.tensor as mt >>> mt.hypot(3*mt.ones((3, 3)), 4*mt.ones((3, 3))).execute() array([[ 5., 5., 5.], [ 5., 5., 5.], [ 5., 5., 5.]]) Example showing broadcast of scalar_like argument: >>> mt.hypot(3*mt.ones((3, 3)), [4]).execute() array([[ 5., 5., 5.], [ 5., 5., 5.], [ 5., 5., 5.]]) """ op = TensorHypot(**kwargs) return op(x1, x2, out=out, where=where)