o Ni44@spddlmZddlZddlZddlZddlZddlmZgdZ dde DZ dd Z d d Z d d Z ddZddZddZd r cOsdSNr )argskwargsr r r  srcCs*t|dkrtd|jj|dSdS)Nrz{}: Unexpected arguments {})lenwarningswarnformat __class____name__)solver unused_kwargsr r r _handle_unused_kwargs s rcCs |Sr)absmaxtensorr r r _linf_norms r cCs|dS)N)rpowmeansqrtrr r r _rms_normr%cCsdS)Nr rr r r _zero_normsr(cCs"t|dkrdStdd|DS)Nrr'cSsg|]}t|qSr )r%)r rr r r r !rz_mixed_norm..)rr) tensor_tupler r r _mixed_norms r*cCs4|j}|j} |j} || }|dur|||}|t||} ||| } ||| } | dks8| dkrAtjd|| d}nd| | }|}|||}||||}t|||| |}| dkr||dkr|ttjd|| d|d}ndt| |dt|d }|}td ||| S) aEmpirically select a good initial step. The algorithm is described in [1]_. References ---------- .. [1] E. Hairer, S. P. Norsett G. Wanner, "Solving Ordinary Differential Equations I: Nonstiff Problems", Sec. II.4, 2nd edition. Ngh㈵>gư>dtypedeviceg{Gz?gV瞯.)iterr_tuplerrzipr1cat)r tolshapesr r r _tuple_tolss   rmcCsPg}d}|D]}||}||d||fg||R|}qt|S)Nr.)rdappendviewrh)rlengthrl tensor_listtotalrf next_totalr r r _flat_to_shape~s &rtc$eZdZfddZddZZS) _TupleFuncctt|||_||_dSr)superrv__init__ base_funcrlselfrzrlrr r ry z_TupleFunc.__init__cCs*||t|d|j}tdd|DS)Nr cSg|]}|dqSrTreshape)r f_r r r r z&_TupleFunc.forward..)rzrtrlr1rj)r|rVyfr r r forwardsz_TupleFunc.forwardr __module__ __qualname__ryr __classcell__r r r}r rv rvcru)_TupleInputOnlyFunccrwr)rxrryrzrlr{r}r r ryr~z_TupleInputOnlyFunc.__init__cCs||t|d|jSNr )rzrtrlr|rVrr r r rr&z_TupleInputOnlyFunc.forwardrr r r}r rrrcs&eZdZdfdd ZddZZS) _ReverseFuncr.crwr)rxrryrzmul)r|rzrr}r r ryr~z_ReverseFunc.__init__cCs|j|| |Sr)rrzrr r r rsz_ReverseFunc.forward)r.rr r r}r rsrc@seZdZdZdZdZdS)Perturbrrr!N)rrrNONEPREVNEXTr r r r rsrcs,eZdZfddZejdddZZS) _PerturbFunccstt|||_dSr)rxrryrz)r|rzr}r r rys z_PerturbFunc.__init__)perturbcCstt|ts Jdt|r|j}||j}|tjur&t ||d}n|tj ur3t ||d}n | ||S)Nz-perturb argument must be of type Perturb enumr) isinstancerr1 is_complexrealr0rr,r _nextafterrrz)r|rVrrr r r rs    z_PerturbFunc.forward)rrrryrrrrr r r}r rs rc  sd|durt|dkrtdt|dt||d|}|} dt|tj } | r]t|ts2Jddd|Dtd|}td |}td d|D}t |}|dur]t |}|durdi}n| }|durnd }||vrtd |d d |d| rd|vr|dntfdd} | |d<n d|vrnt|d<td|dd} t|dkr|d|dkrd} | r| }t|dd}|durt|}z|dWn tyYn wfdd|d<t|dt|dtd|t|r|jrJdt|r|jrJd|j|jkr%td ||j}t|}t} tD]@}zt| |}Wnt yHt!||t"Yq.w|t"urg| #|| r^|ffd!d" }| rg|fd#d"}t!|||q.t$D]}zt| |}Wn t yYqqwt!|||qq| ||%}t|dkrtd$ ||||||||||| f S)%Nr!zCWe require len(t) == 2 when in event handling mode, but got len(t)=.rz+y0 must be either a torch.Tensor or a tuplecSsg|]}|jqSr )rfr y0_r r r r sz!_check_inputs..r8r9cSrrrrr r r r rdopri5z&Invalid method "{}". Must be one of {}z{"z", "z"}.r:cst|d}|Srrt)rr)r:rlr r _norms z_check_inputs.._normrVTFrg)rgrid_constructorcs|||  Srr )r4r6rV)_grid_constructorr r r!sz_check_inputs..step_tjump_tzrtol cannot require gradientzatol cannot require gradientz9t is not on the same device as y0. Coercing to y0.device.cst|d}||||Srrr5r6dt _callback)rlr r callbackFs  z_check_inputs..callbackcSs|| ||Srr rr r r rJsz)Solver '{}' does not support callbacks {})&r ValueErrorrrr1Tensorrhrmrjrvrcopyrjoinkeysr*r%_check_timelikerKeyError _flip_optionr] is_tensor requires_gradr-rrr0rset_all_callback_namesgetattrAttributeErrorsetattr_null_callbackadd_all_adjoint_callback_namesvalid_callbacks)r4r6rVr8r9methodoptionsevent_fnSOLVERS original_funcis_tupler t_is_reversedcallback_names callback_namerinvalid_callbacksr )rr:rlr _check_inputss                     rc@s$eZdZeddZeddZdS)_StitchGradientcCs|Srr )ctxx1outr r r r]sz_StitchGradient.forwardcCs|dfSrr )rgrad_outr r r backwardasz_StitchGradient.backwardN)rrr staticmethodrrr r r r r\s  rcCsVtttdrt||}nt||}Wdn1s wYt||S)N nextafter)r1no_gradhasattrr np_nextafterrapply)rx2rr r r rfs    rcCsFtd|}|}tt|| |}|S)Nztorch.nextafter is only available in PyTorch 1.7 or newer.Falling back to numpy.nextafter. Upgrade PyTorch to remove this warning.) rrdetachcpunumpyr1rnprr0)rrx1_npx2_nprr r r ros rcCst|tjs Jd|t|||dksJd||s+|jr+Jd||dd|ddk}|sG|sIJd|dSdS)Nz{} must be a torch.TensorrrXz{} cannot require gradientrTr\)rr1rrrarYrrU)r timelikecan_graddiffr r r rxs (rcCs@z||}Wn tyYdSwt|tjr| ||<dSdSr)rrr1r)r option_name option_valuer r r rs   rr)*enumrmathrrr1revent_handlingrrrrrr r%r(r*rErHrrSrWr[r]rarmrtnnModulervrrrrrautogradFunctionrrrrrr r r r sH   ,