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Constraints: - None or non-empty str for 'call_function', 'get_attr' - None for 'placeholder', 'output' rrNrrrzP has invalid stack_trace metadata, expected a string or None but instead found: rzA contains stack_trace metadata, expected None but instead found: )rvrrrmrWrXrYr~rrrrrZr)rurXr rrrrNrNrO_verify_stack_traceVs.   rrRc Csdd|jD}|D]9}t|tjjsq |jjD]*}|jdkrD|j |vr'q||j }t |}|j |sDt d|j d|d|qq dS)a  Performs a sanity check on the placeholder node names. - User input nodes: no restrictions, should match the original forward() signature - Params/buffers/constants/custom_obj/token nodes: should start with prefixes defined in cSsi|]}|jj|jqSrN)rrr{)rrrNrNrOrvsz-_verify_placeholder_names..rzPlaceholder node name z does not follow spec for z, name should have prefix: N) rrrmrWrXrYr~rrrrrnr)rQrR name_to_kindr r node_kindprefixrNrNrO_verify_placeholder_namesps"      repcCsd}t}|jD]9}t|tjjsq |jjD]*}|j dkr q|d7}t |j ds,Jt |j ds4J| |j j d|j jqq ||dS)Nrrzr2rFrErl)op_countop_set)rMrurrmrWrXrYr~rrr rrrFrE)rrrrrrNrNrO get_ep_statss   r _EXPORT_FLAGS_EXPORT_MODULE_HIERARCHYcstfdd}|S)Nc szLz t}|i|}t}tdd||tdt|Wn$tyE}zt|}|jd|j}td|t|td|d}~wwWdada |Sdada w)Nz export.time)r/metricsr0rlz export.error)r/rmessager0rN) timer%rrrrrFrGrZr)r|r}startrendrAt error_typefnrNrOwrappers: z$_log_export_wrapper..wrapper)rswraps)rrrNrrO_log_export_wrappersrcCs^t|tttfs |f}nt|trt|}nt|tjtfr%|dur%|f}|dur+i}||fSr)rmr8rdictrWr[)example_inputsexample_kwarg_inputsrNrNrO$_process_jit_trace_inputs_for_exports  robjccs4|j}|||j|_z dVW||_dS||_w)znHelper method to make it easier to cleanly torch.export() a method on a module that is not `forward`. N)r__get__ __class__)r new_methodoriginal_methodrNrNrO patch_forwards rc cs@tj}tjdz dVWtj|dStj|wr^)rWrh_jit_texpr_fuser_enabled_jit_set_texpr_fuser_enabled)original_staterNrNrO_temp_disable_texpr_fusers   rcs$eZdZfddZddZZS)_WrapperModulect||_dSr)super__init__r+)rr+rrNrOr  z_WrapperModule.__init__cOs|j|i|Sr)r+)rr|r}rNrNrOrsz_WrapperModule.forwardrErFrGrr __classcell__rNrNrrOrrrc Cs"tddlm}t||\}}t||tjjfr,t|||ddd WdSt|tj rkt| tjjtj j frkt| |t| ||ddd WdWdS1sewYntt|||ddd WdSWddS1swYdS)Nr)TopLevelTracedModuleFT)rLrE)rtorch.jit._tracerrrmrWrh ScriptModule_exportmodule ScriptMethodownerrrrr)traced_callabler|r}r export_args export_kwargsrNrNrO"_convert_ts_to_export_experimentalsN  "rrDoriginal_state_dict orig_in_spec_disable_forced_specializationsrEc ( Cst|||||d|dd} t| ||\} } }}| jjD]+}|jdkrEd|jvrEt| |j}t|t j j sE|dus;Jd|j |dd|jd<qi}| jjD]}|j}|j}|jdkrt| |}t|t j j r|j ddd D] \}}|||d |<ql|jddd D] \}}|||d |<q|jdkrt| |}t|t jjs|||<|jd krt|jt jjs|jD]}|jdkrt jjjD]}||vr||||j|<qqqL| j}}|dusJ|jttfvrttd|g}| jjjj}tt || j!|| j_| "t#| t|t$|}|t%| t&|| | i|||d }Wdn 1s&wY|j'}|j(} |j)}!|*D]}"|"+d d|"+ddq8|jjD]O}|jdkr|j| j,vrw| j,|j}#|#|vrw||#-D] \}$}%|%|j|$<ql|j| j.vr| j.|j}&|&|vr||&-D] \}$}%|%|j|$<qqLt/t0|1t2| | |!dt3|| }'t4|'| t5|| |!t6|| |!t7|| ||_8||_9| jd|_:|S)NF)r%r(r'r)r rzbCannot find dynamo_fake_mode. This could be due to the exported graph module have no placeholders.Tr call_module)recurserrlrz)rDrrrr)rrrrSrV);r-rr~rrrrrrmrWrrrrrrXrY_opsHigherOrderOperator _input_nodesproxy_COPY_META_FIELDS _out_specrrr8r]r0_codegen pytree_info orig_argsr-r._in_specrrrrrrQrRrSrrr^rr_rrMrqrrrrrr rTrUrV)(r r|r}r,r%rDrrr'rrErrrrdynamo_fake_moderrparams_buffers_to_node_metarr submodulerrrentryrT orig_out_specrrFaten_export_artifactrQrrSmetadata param_namerr buffer_namerrNrNrO_strict_exports                                    rc  sBdifdd} t||||| |d\} } }}}t| t|}| =t|| || &\}}}}t||||||| | d}fdd|jD|_Wdn1sUwYWdn1sdwYzt| |j|||| | dWnt t fy}zt t j t|d}~wwt||j|j|_| |_|_|S)Ncsdfdd }|S)Nc s"|pi}Gfdddtjj}||}ddD}t||||fd|i|\}}td|Wdn1s?wYtt|j |_ tt|j |_ tt|j |_ tt|j |_ tt|j |_ |jjD]} d| jvr| jd} dd tt| D| jd<qp||fS) Ncs(eZdZfddZfddZZS)z]_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrappercrr)rrrk)rr rrNrOrrzf_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrapper.__init__cs~t|jtjjr,tjjtj|jj|i|}Wdn1s&wYn|j|i|}t |\}t |Sr) rmrkrWrXrY tracebackpreserve_node_meta Interpreterrunr] tree_flattenr8)rr|r}tree_out flat_outsrTrNrOrsze_non_strict_export.._tuplify_outputs.._aot_export_non_strict..Wrapper.forwardrrNrrrOWrappers rcSsg|]}d|qS)z _export_root.rN)rrXrNrNrOrsz`_non_strict_export.._tuplify_outputs.._aot_export_non_strict..r}z%Exported program from AOTAutograd: %srcSsi|] \}}t||qSrN)rj)rrrrNrNrOrr\z`_non_strict_export.._tuplify_outputs.._aot_export_non_strict..)rWrrrlogdebugr]tree_maprgrprqr_r^rrr~rrr) r r|r}r0r wrapped_modnew_preserved_call_signaturesrQrRrr) aot_exportrVrTr%rNrO_aot_export_non_stricts<    zL_non_strict_export.._tuplify_outputs.._aot_export_non_strictrrN)rr)rVrTr%)rrO_tuplify_outputss3z,_non_strict_export.._tuplify_outputs)rEr')rDrCrEcs(i|]\}}|t|tr|n|qSrN)rmr")rrr)map_fake_to_realrNrOr0sz&_non_strict_export..)rrE)rrrrrrSrrrQr)r1r r r?rZrrRrTrUrV)r r|r}r,r%rDrrr'rrErrUrrequalities_inputsoriginal_signaturer patched_mod new_fake_argsnew_fake_kwargsnew_fake_constant_attrsrrArN)rrVrTr%rO_non_strict_exports| <      r )rLr%rDr'rrErLc Csft|tsttjdt||r|rttjdt|at} | |r'dnd| |r0dndt d| d| a |p>i}t|t j jrM||||}t||f\} } |jd d } | set|||}nd }|rktnt}|||||||| | ||| }|j}|j}|j}|j}|j}|j}||jd <d d|jjD|jd<t ddt!|j"Dt#|j"}t$|||| d}t%|||||}|rt&|||i}|D]\}}|st'|n|}t(dggd|||<qt#|dkr|st)|t*|||}|d usJ|j+}|d us Jt,|t-|| st.||t/||j0|| |t1t| ||||f|jd}|S)a Traces either an nn.Module's forward function or just a callable with PyTorch operations inside and produce a ExportedProgram. Args: f: the `nn.Module` to trace. args: example positional inputs. kwargs: optional example keyword inputs. dynamic_shapes: An optional argument where the type should either be: 1) a dict from argument names of ``f`` to their dynamic shape specifications, 2) a tuple that specifies dynamic shape specifications for each input in original order. If you are specifying dynamism on keyword args, you will need to pass them in the order that is defined in the original function signature. The dynamic shape of a tensor argument can be specified as either (1) a dict from dynamic dimension indices to :func:`Dim` types, where it is not required to include static dimension indices in this dict, but when they are, they should be mapped to None; or (2) a tuple / list of :func:`Dim` types or None, where the :func:`Dim` types correspond to dynamic dimensions, and static dimensions are denoted by None. Arguments that are dicts or tuples / lists of tensors are recursively specified by using mappings or sequences of contained specifications. preserve_module_call_signature: A list of submodule paths for which the original calling conventions are preserved as metadata. _allow_complex_guards_as_runtime_asserts: With the current dynamic shapes language for dims and derived dims, we can run into constraints that are not expressible with the language. For example, flattening a matrix and adding to a vector, both fully dynamic (i.e. x.reshape([-1]) + y) emits a guard s0 * s1 = s2, which is not expressible. By default, we either raise a constraint violation error or specialize to static values. If this flag is set to True, we avoid erroring out and instead allow complex constraints to exist as runtime assertions in the graph. The sympy interpreter (torch/utils/_sympy/interp.py) will produce the math ops required to compute and assert the value of the guard (e.g. sym_size_int, eq, _assert_scalar). Additionally, if TORCH_DYNAMO_DO_NOT_EMIT_RUNTIME_ASSERTS=1 is specified, we will allow complex constraints while not emitting runtime asserts, returning a cleaner graph with lesser guarantees around dynamic shapes. _disable_forced_specializations: Similar to _allow_complex_guards_as_runtime_asserts, but only avoids specializing to static values if set to True. For complex guards that don't specialize, this flag doesn't have any effect. Ideally this would be subsumed by _allow_complex_guards_as_runtime_asserts, but this handles one additional case: single-variable equalities where the symbol is solvable for a concrete value (e.g. Eq(s0 // 4, 400) -> s0 = 1600). If set to True, this flag will avoid specializations. Direct equalities (e.g. s0 = 4), will still specialize. Returns: An ExportedProgram containing the traced method. r1zL_disable_forced_specializations can be only be specified in non-strict mode.rL non_strictrD aot_dispatchz export.enterr.T) keep_varsNforward_arg_namescSsi|] \}}t|r||qSrN)r*rrNrNrOrs z_export..inline_constraintscss$|] \}}|jtjkr|VqdSr)r{r6 USER_INPUT)rrXsrNrNrOrs z_export..)rE)r!r"r)rr~rrrvmodule_call_graphrrSrN)2rmr8r r r9rrrrMrr%rrWrShapesCollectionr,r]rrrrr rQrRrTrSrUrVrr var_to_rangerrrvrror&rrxrgr8rrrurrrr5r~r$) r r|r}r,rLr%rDr'rrEr0r~rrr export_funcrrQrrTrSrUrV num_lifted combined_argsrvrrspecsmod_fqnrwexported_programrNrNrOrLs A         r)NNr)rKrsrloggingrrwarnings contextlibrrtypingrrrrrr r r rWrytorch.fxtorch.utils._pytreerj_pytreer]torch._dynamo.excr r torch._export.non_strict_utilsrrrrrr(torch._export.passes._node_metadata_hookrr@torch._export.passes.add_runtime_assertions_for_constraints_passr-torch._export.passes.collect_tracepoints_passr(torch._export.passes.lift_constants_passrrrtorch._export.utilsrrtorch._export.verifierrtorch._export.wrappersrtorch._functorch.aot_autogradrrxr!"torch._library.fake_class_registryr"torch._subclasses.fake_tensorr#r$torch._utils_internalr%torch.export.dynamic_shapesr&torch.export.exported_programr'torch.fx._utilsr(%torch.fx.experimental.symbolic_shapesr)r*r+r,torch.fx.graphr-r.torch.fx.passes.runtime_assertr/r0torch.utils._sympy.value_rangesr1 _safeguardr3rr4r5r6r7r8rr9r:r;r<r=r>r?r@ getLoggerrEr dataclassrArPr>criticalrerror exceptioninfowarningprintwarnrDrerjrgrxrrrrrrrrZrr[r\rrXrYr rrr$rIr-rrrrrrrrrrrJrrrrrrrrr rrNrNrNrOs (                (    $ 3  )  1 $          K  9      +!  %        /