a h3/@sddlZddlmZddlZddlmmZddZddZ ddZ d d Z d d Z ej d dZddZddZddZddZddZdS)N) namedtuplecstfdd}|S)Nc sdr$dj}||i|Sds8drdrFdnd}|dkrVdnd}|j}td|dd|d|d |i|S) Nautogradsave_for_backwardbackwardz We found a 'z' registration for  at z but were unable to find a 'z' registration. To use the CustomOp API to register a backward formula, please provide us both a backward function and a 'save for backward' function via `impl_backward` and `impl_save_for_backward` respectively.)Z _has_impl _get_implfunclocation RuntimeError)argskwargskernelmissingfoundlocZautograd_fallback custom_opG/var/www/auris/lib/python3.9/site-packages/torch/_custom_op/autograd.pyinners    z*autograd_kernel_indirection..inner)autograd_not_implemented)rrrrrautograd_kernel_indirectionsrcsfdd}|S)Ncs`tr$tdd||fr$tdtj|i|WdS1sR0YdS)NcSst|tjo|jSN) isinstancetorchTensorZ requires_gradxrrr6z:autograd_not_implemented..kernel..z.Autograd has not been implemented for operator)rZis_grad_enabledpytreeZtree_anyr _C_AutoDispatchBelowAutograd)r r rrrr 4s    z(autograd_not_implemented..kernelr)rr rr#rr3s rc Cs|durt|ts|f}n|}t|t|ks2Jg}tt||D]f\}\}}t|tjrl|sD||qDt|tr|sD| |qD|rDt d|d|dt |dqD|r|j |dS)NzWith output_differentiability=z . At idx z , we received an object of type za that is not a Tensor, so it cannot have be marked as differentiable in output_differentiability.) rtuplelen enumerateziprrappendlistextendr typemark_non_differentiable)ctxoutputoutput_differentiabilityZ tuple_outputZnon_differentiable_tensorsidxZdifferentiableoutrrrr,?s6     r,csfdd}|S)Ncspt|\}dfdd}fdd}tjd||}|j|}dus`Jtt|S)Ncs|dtt|}tj|}Wdn1sB0Yttt |}t|}||}t |||ft ||t |\}t |S)NT)Zset_materialize_gradsr tree_unflattenr)rr!r"namedtuple_argstree_mapr+save_pytree_for_backwardr, tree_flattenr$)r- flat_argsr r. args_infoZsave_for_backward_fn_inputsZto_save flat_output) op_overloadout_specr/save_for_backward_fnschemaspecrrforwardns  &   z9construct_autograd_kernel..apply..forwardcsfdus Jtt|}t|\}}t}t|ts>|f}||g|R}t||t||Sr) r r2r) unpack_savedobjectrr$validate_grad_inputs_dictgrad_inputs_dict_to_flat_tuple)r-Zflat_grad_outputZgradsZsavedr8Z inner_ctxgrad_inputs_dict) backward_fnrr;rrrs    z:construct_autograd_kernel..apply..backwardZ _customop)r r6gen_autograd_functionZ_opnameapplyr2r))r r7r?r generated_clsr9rErr:r/r<r=)r;r>rrGjs   z(construct_autograd_kernel..applyr)r=r/rr:r<rErGrrIrconstruct_autograd_kernelbs/rJcCs$t|tjjft|t|d}|S)N)r?r)r+rrZFunction staticmethod)namer?rrHrrrrFsrFcCs.dd|jjD}t|jd}t||}|S)NcSsg|] }|jqSr)rL.0argrrr rz'namedtuple_args_cls.._args) argumentsflat_allstrrLr)r=ZattribsrL tuple_clsrrrnamedtuple_args_clss rVcCst|tsJt|}||Sr)rr$rV)r=r rUrrrr3sr3c sfdd}t|ts(|dt|ddjjjD}|}||krb|d|d|d|D]V\}}t||}t|t rft|t t fs|d |d t|d t |t |ks|d |d t |d t |t t ||D]p\} \} } | dur qt| tjs6|d |dt| d| t| tjs|d |d| d| d|qqj|durrqjt|tjs|dt|d|dt|tjsj|d|d|d|dqjdS)Ncs*d}tdd|jd|dS)Nrz%In the backward function defined for rz using the CustomOp API, )rr r )whatr forward_oprrerrors z(validate_grad_inputs_dict..errorzBexpected the output of the backward function to be a dict but got cSsh|]}|jr|jqSr)r+Zis_tensor_likerLrMrrr s z,validate_grad_inputs_dict..z3expected the returned grad_input dict to have keys z but got z. The backward function must return a gradient (can be None) for each arg to the CustomOp that may be a Tensor or Sequence[Tensor]. Args declared to be non-Tensor-like types should not appear in the grad_input dictz for input 'zR' expected the grad_input dict to hold a list of gradients but got object of type .z1' expected the grad_input dict to hold a list of z gradients but got z\' expected the grad_input dict to hold a list of None or Tensor gradients but got object of z at index z(', got a Tensor as the gradient for the z(-th value but expected None because the z(-th value was not a Tensor (it was type zgot object of type z as the gradient for input 'z:', but expected the gradient to be either None or a Tensorz(got a Tensor as the gradient for input 'z3' but expected None as the gradient because input 'z ' was not a Tensor (it was type z).)rdictr+Z_schemarRrSkeysitemsgetattrr)r$r%r&r'rr issubclass) rDrYr8rZZ expected_keysZ actual_keysrLZgradarg_infor0ginforrXrrBs          rBcCsVg}|D]6\}}||vr8|tdd|q|||qtt|S)NcSsdSrrrrrrr rz0grad_inputs_dict_to_flat_tuple..)_asdictr_r(r r4r$Z tree_leaves)rDr8resultrLrbrrrrCsrCc Cst|\}}t|}ddt|D}ddt|D}dd|D}dd|D}||_||_|j|||_||_||_ dS)NcSs g|]\}}t|tjr|qSrrrrrNr0thingrrrrPsz,save_pytree_for_backward..cSs g|]\}}t|tjs|qSrrgrhrrrrPs cSsg|]}t|tjr|qSrrgrNrirrrrP rcSsg|]}t|tjs|qSrrgrjrrrrP!r) r r6r%r&r>num_eltsr tensor_idxssaved_non_tensorsnon_tensor_idxs) r-stuff flat_stuffr>rkrlrnZtensorsZ non_tensorsrrrr5s  r5cCs^dg|j}t|j|jD]\}}|||<qt|j|jD]\}}|||<q:t||j}|Sr) rkr'Z saved_tensorsrlrmrnr r2r>)r-rpZtensorr0Z non_tensorrorrrr@,s   r@) functools collectionsrrZtorch.utils._pytreeutilsZ_pytreer rrr,rJrF lru_cacherVr3rBrCr5r@rrrrs    #:  P