#h*pddlmZmZmZmZmZddlZddlmZddlm Z m Z m Z m Z m Z mZmZmZmZmZmZmZmZmZmZmZmZmZmZddgZGddeZd d ed ed ed e d e d ed ze_deedeedeedeedeedeedeedeededeee fdeee fdeee fde de dedededef$d Z!deedeedeedeedeedeedeedeededeee fdeee fdeee fde de dedededef$d!Z"deedeedeedeedeedeedeedeedede de deee fde de dedededed"df&d#Z#e e!$ d(deedeedeedeedeedeed%eededed&eedeedeededede de dee efde de def(d'Z$y)))castListOptionalTupleUnionN)Tensor)_capturable_doc_default_to_fused_or_foreach_device_dtype_check_for_fused_differentiable_doc_disable_dynamo_if_unsupported _foreach_doc _fused_doc!_get_capturable_supported_devices_get_scalar_dtype _get_value _maximize_doc _params_doc_stack_if_compiling_use_grad_for_differentiable _view_as_real DeviceDictDeviceDtypeDict OptimizerParamsTAdamWadamwceZdZ ddddddddedeeefdeeeefeeeffdeded ed ed e ed ed ede effdZ fdZ dZ e ddZxZS)rFN)maximizeforeach capturabledifferentiablefusedparamslrbetaseps weight_decayamsgradr r!r"r#r$c t|tr-|r | s td|jdk7r tdd|kstd|d|kstd|d|dcxkrdksntd |dd|dcxkrdksntd |dd|kstd |t|dtrt|dts1t|dtrt|dts td t|dtr0| s |r td |djdk7r tdt|dtr0| s |r td|djdk7r tdt |||||||| | |  } t ||| | r"| r tdd|_ |r tdyy)NElr as a Tensor is not supported for capturable=False and foreach=Truer zTensor lr must be 1-elementzInvalid learning rate: zInvalid epsilon value: r?z#Invalid beta parameter at index 0: z#Invalid beta parameter at index 1: zInvalid weight_decay value: z0betas must be either both floats or both TensorszKbetas[0] as a Tensor is not supported for capturable=False and foreach=Truez!Tensor betas[0] must be 1-elementzKbetas[1] as a Tensor is not supported for capturable=False and foreach=Truez!Tensor betas[1] must be 1-element) r&r'r(r)r*r!r r"r#r$z)`fused` does not support `differentiable`Tz0`fused` and `foreach` cannot be `True` together.) isinstancer ValueErrornumelfloatdictsuper__init__ RuntimeError_step_supports_amp_scaling)selfr%r&r'r(r)r*r r!r"r#r$defaults __class__s N/var/www/html/sandstorm/venv/lib/python3.12/site-packages/torch/optim/adamw.pyr5zAdamW.__init__#s b& !z [xxzQ !>??by6rd;< <cz6se<= =eAh$$B58*MN NeAh$$B58*MN Nl";L>JK K a% (Za%-H58V,E!Hf1MOP P eAh '' aQx~~1$ !DEE eAh '' aQx~~1$ !DEE%!)   * "#NOO.2D +"#UVV ct|||jD]#}|jdd|jdd|jdd|jdd|jdd|jdd}|dD]}|jj |g}t |d k7s.tj|d rGt|d }|ds|dr,tj|t| |j ntj|t |d <&y)Nr*Fr r!r"r#r$r%rstepis_fuseddtypedevicerB) r4 __setstate__ param_groups setdefaultstategetlentorch is_tensorr2tensorrrC)r8rHgroupr$pp_statestep_valr:s r;rEzAdamW.__setstate__ms% U#&& E   Y .   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Args: closure (Callable, optional): A closure that reevaluates the model and returns the loss. Nr*r'r&r)r(r r!r"r#r$ grad_scale found_inf)r*beta1beta2r&r)r(r r!r"r#r$rirjrf) _cuda_graph_capture_health_checkrK enable_gradrFrrr2rgrgetattr)r8closurelossrNr`rarbrcrdrer*rkrlrfs r;r>z AdamW.stepsV --/  ""$ !y !&&* E-/ "$E%'H(*K,.O(*K!),GeUl 3U7^DLE5**  K     ;">2%Lz*i( .$%56Gn"4t<!$ T:') +* X _ ! !s C$$C-)gMbP?)g?g+?g:0yE>g{Gz?FN)__name__ __module__ __qualname__rrr2rrboolrr5rErgrr> __classcell__)r:s@r;rr"s$(CO"HW"& $ $HWHW %- HWU5&=)5+??@ HW  HW  HWHWHW$HWHWHW~HWT.IV":":r<a Implements AdamW algorithm. .. math:: \begin{aligned} &\rule{110mm}{0.4pt} \\ &\textbf{input} : \gamma \text{(lr)}, \: \beta_1, \beta_2 \text{(betas)}, \: \theta_0 \text{(params)}, \: f(\theta) \text{(objective)}, \: \epsilon \text{ (epsilon)} \\ &\hspace{13mm} \lambda \text{(weight decay)}, \: \textit{amsgrad}, \: \textit{maximize} \\ &\textbf{initialize} : m_0 \leftarrow 0 \text{ (first moment)}, v_0 \leftarrow 0 \text{ ( second moment)}, \: \widehat{v_0}^{max}\leftarrow 0 \\[-1.ex] &\rule{110mm}{0.4pt} \\ &\textbf{for} \: t=1 \: \textbf{to} \: \ldots \: \textbf{do} \\ &\hspace{5mm}\textbf{if} \: \textit{maximize}: \\ &\hspace{10mm}g_t \leftarrow -\nabla_{\theta} f_t (\theta_{t-1}) \\ &\hspace{5mm}\textbf{else} \\ &\hspace{10mm}g_t \leftarrow \nabla_{\theta} f_t (\theta_{t-1}) \\ &\hspace{5mm} \theta_t \leftarrow \theta_{t-1} - \gamma \lambda \theta_{t-1} \\ &\hspace{5mm}m_t \leftarrow \beta_1 m_{t-1} + (1 - \beta_1) g_t \\ &\hspace{5mm}v_t \leftarrow \beta_2 v_{t-1} + (1-\beta_2) g^2_t \\ &\hspace{5mm}\widehat{m_t} \leftarrow m_t/\big(1-\beta_1^t \big) \\ &\hspace{5mm}\widehat{v_t} \leftarrow v_t/\big(1-\beta_2^t \big) \\ &\hspace{5mm}\textbf{if} \: amsgrad \\ &\hspace{10mm}\widehat{v_t}^{max} \leftarrow \mathrm{max}(\widehat{v_{t-1}}^{max}, \widehat{v_t}) \\ &\hspace{10mm}\theta_t \leftarrow \theta_t - \gamma \widehat{m_t}/ \big(\sqrt{\widehat{v_t}^{max}} + \epsilon \big) \\ &\hspace{5mm}\textbf{else} \\ &\hspace{10mm}\theta_t \leftarrow \theta_t - \gamma \widehat{m_t}/ \big(\sqrt{\widehat{v_t}} + \epsilon \big) \\ &\rule{110mm}{0.4pt} \\[-1.ex] &\bf{return} \: \theta_t \\[-1.ex] &\rule{110mm}{0.4pt} \\[-1.ex] \end{aligned} For further details regarding the algorithm we refer to `Decoupled Weight Decay Regularization`_. z Args: a lr (float, Tensor, optional): learning rate (default: 1e-3). A tensor LR is not yet supported for all our implementations. Please use a float LR if you are not also specifying fused=True or capturable=True. betas (Tuple[float, float], optional): coefficients used for computing running averages of gradient and its square (default: (0.9, 0.999)) eps (float, optional): term added to the denominator to improve numerical stability (default: 1e-8) weight_decay (float, optional): weight decay coefficient (default: 1e-2) amsgrad (bool, optional): whether to use the AMSGrad variant of this algorithm from the paper `On the Convergence of Adam and Beyond`_ (default: False) z a8 .. 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See :class:`~torch.optim.AdamW` for details. c3PK|]}t|tj ywrr)r/rKr)rts r;rzadamw..Hs 5() 1ell#5s$&zPAPI has changed, `state_steps` argument must contain a list of singleton tensorsNF) use_fusedz6torch.jit.script not supported with foreach optimizersz4torch.jit.script not supported with fused optimizers) r*rkrlr&r)r(r r"r#rirjrf) rKrrrr6r r/rrrrrr)r%rarbrcrdrer!r"r#r$rirjrfr*rkrlr&r)r(r rfuncs r;rr*s0< >> & & (5-852 ^   }1 Ne 7 z"f-jG }599))+STT '')QRR UYY++- //1"#  ! %%r<)NFFNNNF)%typingrrrrrrKr optimizerr r r r rrrrrrrrrrrrrrr__all__r__doc__rvr2rrrrrSr<r;rs65 . G hIhX&N         %OA LPK LPK <PK6lPKf PK &\ PK f PK PKPKPK  PK  PK femPKPK PK !PK"#PK$%PK&'PKf^ L^ <^6l^f ^ &\ ^ f ^ ^^^  ^  ^ fem^^ ^ !^"#^$%^&'^B` L` <`6l`f ` &\ ` f ` ``` ` ` fem`` ` !`"#`$%`&'`( )`F 1EF#  #'"&S LS <S6lSf S &\ S f Sd^SSS D>S SSS"#S$ %S& 'S( eVm)S*+S, -S./SGSr<