briddlZddlZddlmZddlZddlmZdejddfdZdejfdZ dej jfdZ dej jfd Z de fd Zdd Zde fd Zd aej ddefdZdS)N) Generator)default_generator new_statereturnc.tj|dS)zSets the random number generator state. .. note:: This function only works for CPU. For CUDA, please use :func:`torch.manual_seed`, which works for both CPU and CUDA. Args: new_state (torch.ByteTensor): The desired state N)r set_state)rs d/var/www/html/bestrading.cuttalo.com/models/btc_v9/venv/lib/python3.11/site-packages/torch/random.py set_rng_stater s *****c(tjS)zReturns the random number generator state as a `torch.ByteTensor`. .. note:: The returned state is for the default generator on CPU only. See also: :func:`torch.random.fork_rng`. )r get_stater r get_rng_staters  & ( ((r c t|S)aSets the seed for generating random numbers on all devices. Returns a `torch.Generator` object. Args: seed (int): The desired seed. Value must be within the inclusive range `[-0x8000_0000_0000_0000, 0xffff_ffff_ffff_ffff]`. Otherwise, a RuntimeError is raised. Negative inputs are remapped to positive values with the formula `0xffff_ffff_ffff_ffff + seed`. )_manual_seed_impl)seeds r manual_seedr s T " ""r ct|}ddl}|js|j|ddl}|js|j|ddl}|j s|j |t|tj|S)Nr) int torch.cudacuda_is_in_bad_forkmanual_seed_all torch.mpsmpsr torch.xpuxpu_seed_custom_devicerrtorchs r rr-s t99D : % % ' ') ""4((( 9 $ $ & &$ d### 9 $ $ & &( !!$'''  ( . ..r ctj}ddl}|js|j|ddl}|js|j|ddl }|j s|j |t||S)zSets the seed for generating random numbers to a non-deterministic random number on all devices. Returns a 64 bit number used to seed the RNG. rN) rrrrrrrrrrrrrs r rrCs  ! # #D : % % ' ') ""4((( 9 $ $ & &$ d### 9 $ $ & &( !!$''' Kr ct|}tj}t t|rt t|}d}d}t ||rEt ||r5t ||st |||d Sd Sd|d}|d|d|d|dz }t j|td d Sd S) zSets the seed to generate random numbers for custom device. Args: seed (int): The desired seed. See [Note: support the custom device with privateuse1] rrzSet seed for `z0` device does not take effect, please add API's `z` and `z` to `z` device module. stacklevelN) rr _C_get_privateuse1_backend_namehasattrgetattrwarningswarn UserWarning)rcustom_backend_namecustom_device_mod_bad_fork_name_seed_all_namemessages r rr\s' t99D(@@BBu)** >#E+>??** $n 5 5 >' ~; ;  >>7,n==?? A:)>::4@@@@@ A Am':lllG m>mm.mmH[mmm mG M';1 = = = = = = > >r c(tjS)zReturns the initial seed for generating random numbers as a Python `long`. .. note:: The returned seed is for the default generator on CPU only. )r initial_seedrr r r4r4us  ) + ++r FTfork_rngdevicesrc#  K|dkrdVdStj|j}tt|d t d|ddz|sdVdS| }|dkrt s|d|d|d |d |d |d |d |d|d|d|d|d}tj |ddatt|}nt|}tj } fd|D} dVtj |t||D]\} } | | dS#tj |t||D]\} } | | wxYw)az Forks the RNG, so that when you return, the RNG is reset to the state that it was previously in. Args: devices (iterable of Device IDs): devices for which to fork the RNG. CPU RNG state is always forked. By default, :meth:`fork_rng` operates on all devices, but will emit a warning if your machine has a lot of devices, since this function will run very slowly in that case. If you explicitly specify devices, this warning will be suppressed enabled (bool): if ``False``, the RNG is not forked. This is a convenience argument for easily disabling the context manager without having to delete it and unindent your Python code under it. device_type (str): device type str, default is `cuda`. As for supported device, see details in :ref:`accelerator` metaNztorch has no module of `z`, you should register z,a module by `torch._register_device_module`.z reports that you have z& available devices, and you have used z_ without explicitly specifying which devices are being used. For safety, we initialize *every* zA device by default, which can be quite slow if you have a lot of z5s. If you know that you are only making use of a few z' devices, set the environment variable z_VISIBLE_DEVICES or the 'z' keyword argument of z with the set of devices you are actually using. For example, if you are using CPU only, set device.upper()_VISIBLE_DEVICES= or devices=[]; if you are using device 0 only, set zb_VISIBLE_DEVICES=0 or devices=[0]. To initialize all devices and suppress this warning, set the 'z#' keyword argument to `range(torch.z.device_count())`.r%Tc:g|]}|Sr)r).0device device_mods r zfork_rng..s'PPPf11&99PPPr )r r=typer* RuntimeError device_count_fork_rng_warned_alreadyupperr+r,listrangerr zip) r6enabled_caller _devices_kw device_type num_devicesr2 cpu_rng_statedevice_rng_statesr=device_rng_stater>s @r r5r5s2f ,{++0K T22J K{ K K K< =      --// ??#;?$$&& @ @{ @ @!( @ @5@5F5F5H5H @ @7B6G6G6I6I @ @)4(9(9(;(; @ @ $$&& @ @ BM @ @ el @ @#((** @ @8C @ @!, @ @ @  M'a 0 0 0 0'+ $u[))**w--'))MPPPPPPP?  M***(+G5F(G(G ? ? $F$  $ $%5v > > > > ? ? M***(+G5F(G(G ? ? $F$  $ $%5v > > > > ?s :GAH)rN)NTr5r6r) contextlibr+collections.abcrr torch._CrTensorr rr'rrrrrr4rCcontextmanagerr5rr r rUsn%%%%%% &&&&&& +U\ +d + + + +)u|)))) #+ # # # #/ux1////,c2>>>>2,c,,,,!     M?M?  M?M?M?M?M?M?r