Source code for mars.tensor.arithmetic.spacing

#!/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.
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# distributed under the License is distributed on an "AS IS" BASIS,
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import numpy as np

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

class TensorSpacing(TensorUnaryOp):
    _op_type_ = OperandDef.SPACING
    _func_name = "spacing"

[docs]@infer_dtype(np.spacing) def spacing(x, out=None, where=None, **kwargs): """ Return the distance between x and the nearest adjacent number. Parameters ---------- x : array_like Values to find the spacing of. 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 tensor 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 : array_like The spacing of values of `x1`. Notes ----- It can be considered as a generalization of EPS: ``spacing(mt.float64(1)) == mt.finfo(mt.float64).eps``, and there should not be any representable number between ``x + spacing(x)`` and x for any finite x. Spacing of +- inf and NaN is NaN. Examples -------- >>> import mars.tensor as mt >>> (mt.spacing(1) == mt.finfo(mt.float64).eps).execute() True """ op = TensorSpacing(**kwargs) return op(x, out=out, where=where)