U *-es@s&ddlZddlmZGdddZdS)N)Optionalc@seZdZdZdZdZdddZddejfe e ej ej ej d d d Z dejfe e ej ej ej d d dZddZddZddZddZdS) SobolEnginea The :class:`torch.quasirandom.SobolEngine` is an engine for generating (scrambled) Sobol sequences. Sobol sequences are an example of low discrepancy quasi-random sequences. This implementation of an engine for Sobol sequences is capable of sampling sequences up to a maximum dimension of 21201. It uses direction numbers from https://web.maths.unsw.edu.au/~fkuo/sobol/ obtained using the search criterion D(6) up to the dimension 21201. This is the recommended choice by the authors. References: - Art B. Owen. Scrambling Sobol and Niederreiter-Xing points. Journal of Complexity, 14(4):466-489, December 1998. - I. M. Sobol. The distribution of points in a cube and the accurate evaluation of integrals. Zh. Vychisl. Mat. i Mat. Phys., 7:784-802, 1967. Args: dimension (Int): The dimensionality of the sequence to be drawn scramble (bool, optional): Setting this to ``True`` will produce scrambled Sobol sequences. Scrambling is capable of producing better Sobol sequences. Default: ``False``. seed (Int, optional): This is the seed for the scrambling. The seed of the random number generator is set to this, if specified. Otherwise, it uses a random seed. Default: ``None`` Examples:: >>> # xdoctest: +SKIP("unseeded random state") >>> soboleng = torch.quasirandom.SobolEngine(dimension=5) >>> soboleng.draw(3) tensor([[0.0000, 0.0000, 0.0000, 0.0000, 0.0000], [0.5000, 0.5000, 0.5000, 0.5000, 0.5000], [0.7500, 0.2500, 0.2500, 0.2500, 0.7500]]) iRFNcCs||jks|dkr$td|jd||_||_||_td}tj||j|tj d|_ t |j |j|jstj|j|tj d|_ n| |j jtjd|_|jd|jdd|_d |_dS) Nz9Supported range of dimensionality for SobolEngine is [1, ]cpu)devicedtype)Z memory_formatr)MAXDIM ValueErrorseedscramble dimensiontorchrZzerosMAXBITlong sobolstateZ_sobol_engine_initialize_state_shift _scramblecloneZcontiguous_formatquasiZreshape _first_point num_generated)selfrrrrrR/var/www/html/Darija-Ai-Train/env/lib/python3.8/site-packages/torch/quasirandom.py__init__0s zSobolEngine.__init__r)noutr returncCs|jdkr^|dkr |j|}qtj|j|d|j|j|j|d\}|_tj|j|fdd}n(tj|j||j|j|jd|d\}|_|j|7_|dk r| | ||S|S)at Function to draw a sequence of :attr:`n` points from a Sobol sequence. Note that the samples are dependent on the previous samples. The size of the result is :math:`(n, dimension)`. Args: n (Int, optional): The length of sequence of points to draw. Default: 1 out (Tensor, optional): The output tensor dtype (:class:`torch.dtype`, optional): the desired data type of the returned tensor. Default: ``torch.float32`` rr)r )dimN) rrtorZ_sobol_engine_drawrrrcatZ resize_as_copy_)rrr r resultrrrdrawGs2   zSobolEngine.draw)mr r r!c CsXd|}|j|}||d@dksHtd|jd|jd|d|d |j|||d S) aR Function to draw a sequence of :attr:`2**m` points from a Sobol sequence. Note that the samples are dependent on the previous samples. The size of the result is :math:`(2**m, dimension)`. Args: m (Int): The (base2) exponent of the number of points to draw. out (Tensor, optional): The output tensor dtype (:class:`torch.dtype`, optional): the desired data type of the returned tensor. Default: ``torch.float32`` r rrzFThe balance properties of Sobol' points require n to be a power of 2. z0 points have been previously generated, then: n=z+2**=zH. If you still want to do this, please use 'SobolEngine.draw()' instead.)rr r )rr r()rr)r r rZtotal_nrrr draw_base2ks  &zSobolEngine.draw_base2cCs|j|jd|_|S)zF Function to reset the ``SobolEngine`` to base state. r)rr&rr)rrrrresetszSobolEngine.resetcCsZ|jdkr*t|j|d|j|j|jnt|j||j|j|jd|j|7_|S)a Function to fast-forward the state of the ``SobolEngine`` by :attr:`n` steps. This is equivalent to drawing :attr:`n` samples without using the samples. Args: n (Int): The number of steps to fast-forward by. rr)rrZ_sobol_engine_ff_rrr)rrrrr fast_forwards  zSobolEngine.fast_forwardc Csd}|jdk r"t}||jtd}tjd|j|jf||d}t|t dtj d|j|d|_ |j|j|jf}tjd|||d }t |j||jdS)Nrr )r generatorr)r)rr GeneratorZ manual_seedrrandintrrmvpowZarangerZtrilZ_sobol_engine_scramble_r)rgrZ shift_intsZltm_dimsZltmrrrrs   $zSobolEngine._scramblecCsTd|jg}|jr|dg7}|jdk r:|d|jg7}|jjdd|dS)Nz dimension=z scramble=Truezseed=(z, ))rrr __class____name__join)rZ fmt_stringrrr__repr__s   zSobolEngine.__repr__)FN)r7 __module__ __qualname____doc__rr rrZfloat32intrZTensorr r(r+r,r-rr9rrrrrs('   $  r)rtypingrrrrrrs