i,&lddlZddlmZmZmZmZddlZddlZddl m Z m Z ddl m Z mZGdde e Zy) N)ListOptionalTupleUnion) ConfigMixinregister_to_config)SchedulerMixinSchedulerOutputc eZdZdZdZe ddedeee je e ffdZ edZedZdd efd Zdd ed eeej(ffd Z ddee ej,fdeej,defdZdee ej,fddfdZ ddej,deeej,fdej,dedeeeff dZdej,dej,fdZdZdZy)IPNDMSchedulera' A fourth-order Improved Pseudo Linear Multistep scheduler. This model inherits from [`SchedulerMixin`] and [`ConfigMixin`]. Check the superclass documentation for the generic methods the library implements for all schedulers such as loading and saving. Args: num_train_timesteps (`int`, defaults to 1000): The number of diffusion steps to train the model. trained_betas (`np.ndarray`, *optional*): Pass an array of betas directly to the constructor to bypass `beta_start` and `beta_end`. r Nnum_train_timesteps trained_betascl|j|d|_d|_g|_d|_d|_y)N?) set_timestepsinit_noise_sigma pndm_orderets _step_index _begin_index)selfrrs o/home/obispo/Crisostomo_bridge/mision_env/lib/python3.12/site-packages/diffusers/schedulers/scheduling_ipndm.py__init__zIPNDMScheduler.__init__)s? ./!$  c|jS)zg The index counter for current timestep. It will increase 1 after each scheduler step. )rrs r step_indexzIPNDMScheduler.step_index=s rc|jS)zq The index for the first timestep. It should be set from pipeline with `set_begin_index` method. rrs r begin_indexzIPNDMScheduler.begin_indexDs    rr#c||_y)z Sets the begin index for the scheduler. This function should be run from pipeline before the inference. Args: begin_index (`int`, defaults to `0`): The begin index for the scheduler. Nr")rr#s rset_begin_indexzIPNDMScheduler.set_begin_indexLs (rnum_inference_stepsdevicec||_tjdd|dzdd}tj|tjdgg}|j j ?tj|j j tj|_n1tj|tjzdz dz|_d|jdzz d z|_ tj|j|jtjz dzdd}|j||_g|_d|_d|_y) a Sets the discrete timesteps used for the diffusion chain (to be run before inference). Args: num_inference_steps (`int`): The number of diffusion steps used when generating samples with a pre-trained model. device (`str` or `torch.device`, *optional*): The device to which the timesteps should be moved to. If `None`, the timesteps are not moved. r rNg)dtyperrg?)r&torchlinspacecattensorconfigrfloat32betassinmathpialphasatan2to timestepsrrr)rr&r'stepsr8s rrzIPNDMScheduler.set_timestepsVs$7 q!%81%<=crB 5%,,u"567 ;; $ $ 0dkk&?&?u}}UDJ5477?Q#671 !;77rc|S)a? Ensures interchangeability with schedulers that need to scale the denoising model input depending on the current timestep. Args: sample (`torch.Tensor`): The input sample. Returns: `torch.Tensor`: A scaled input sample. )rrIargskwargss rscale_model_inputz IPNDMScheduler.scale_model_inputs  rc|j|}|j|}|j|}|j|}|||zz t|dz } || z||zz} | S)Ng:0yE>)r5r1max) rrIr\r]ralphasigma next_alpha next_sigmapredrXs rr[zIPNDMScheduler._get_prev_samplesp N+ >*[[!45 ZZ 34 $E4(88 4'# *:: rc.|jjSN)r/rrs r__len__zIPNDMScheduler.__len__s{{...r)iN)rrl)T) __name__ __module__ __qualname____doc__orderr intrrnpndarrayrfloatrpropertyr r#r%strr+r'rrFrCrGboolr rr^rcr[rmr`rrrrs  Eim!#&!>FuRZZY]^cYdMdGe>f!!&  !!(3(!!eCDU>V!<bf#eU\\12#HPQVQ]Q]H^# #> 1uell/B)C 1 1(! 88ll88U\\)*88 88  88 % & 88t  %,,  /rr)r3typingrrrrnumpyrtr+configuration_utilsrr scheduling_utilsr r rr`rrr~s, // A=^/^[^/r