o Zh @s0UddlZddlZddlmZddlmZddlmZmZm Z m Z ddl Z ddl m Z ddlmZddlmZmZmZgdZe jje jjjhe jje jjjhe jje jjjhe jje jjje jjjhe jj e jjj!he jj"e jjj#e jjj$he j%ej%ej&d d he j'ej'ej(d d hga)e*e+e,d <ddZ-e-a.de*e+fddZ/d-ddZ0deefddZ1ddZ2de*efddZ3  d.de j4j5de*ede eege6ffd d!Z7d"e j4j5d#e j4jd$e8de9e:e jj;e j4jffd%d&ZdS)/N) OrderedDict)Sequence)AnyCallableOptionalUnion)ExportedProgram)Node)check_subgraphs_connectedget_source_partitionsSourcePartition)find_sequential_partitionsget_equivalent_typesupdate_equivalent_types_dictbfs_trace_with_node_processaddZadd_mulZmul__EQUIVALENT_TYPEScCs(i}tD] }|D]}t|||<qq|SN)rlist)Z_DICTvaluesvrU/var/www/auris/lib/python3.10/site-packages/torch/ao/quantization/pt2e/graph_utils.py_create_equivalent_types_dict%s rreturncCstSr)rrrrrr0srcCs|durtd|atadS)zHelp function for user who wants to customize the _EQUIVALENT_TYPES and _EQUIVALENT_TYPES_DICT. When customized_equivalent_types passes in, re-generate _EQUIVALENT_TYPES and _EQUIVALENT_TYPES_DICT. Nz.customized_equivalent_types should not be None) ValueErrorrr_EQUIVALENT_TYPES_DICT)Zcustomized_equivalent_typesrrrr4s r partitionscCs.d}|D]}|durt||sdS|}qdS)NFT)r )rZprev_partition partitionrrr_partitions_sequentialAs r cCs |g}|tvr|t||Sr)rextend)partition_typematching_typesrrr_get_matching_typesLsr$partition_typescCsBt}|D]}t|}t|}t||@dkrdS||O}qdS)NrFT)setr$len)r%Zpartition_types_setr"r#Zmatching_types_setrrr_valid_type_sequenceSs r(Tgm filter_fnc Cs~t|s td|dt}|D]}t|}t|j||}ttj | ||<qt| }tj |} dd| D} | S)NzInvalid partition types: z*. Each type in the sequence must be uniquecSsg|]}t|r|qSr)r ).0 candidaterrr ss z.find_sequential_partitions..) r(rrr$r graphr itertoolschain from_iterablerproduct) r)r%Zinclude_functional_equivalentr*Ztyped_partitionsr"Ztypes_to_matchrZtyped_partitions_listZfusion_candidatesZfused_partitionsrrrr ^s"   r graph_modulenode arg_indexcCsR|j|}t|tjjsJ|jdksJt|jtsJ||j}|j||fS)NZget_attr) args isinstancetorchfxr optargetstrZ get_submodule)r3r4r5Z submod_node submodulerrr_get_submodule{s   r>cCsxg}|jjD]3}|jdkrq|jtjjjur(|t ||d|t ||d|jtjjj ur9|t ||dq|S)a{ Returns a list of submodules used for control flow operations (torch.ops.higher_order.cond/map) that are in the given toplevel graph (does not look into submodules). Specifically, the returned value is a list containing a tuple of (name of the submodule that's stored in the graph module, the submodule itself, and the fx node that uses this submodule). Z call_functionr) r.nodesr:r;r8opsZ higher_orderZcondappendr>Zmap_impl)r3control_flow_submodulesr4rrr_get_control_flow_submoduless  rEmodelnode_opcCst|ttjjfsJdt|t|tr|jn|}|g}|rI|d}|jj D] }|j dvr2q*||q*ddt |D}| ||s!dSdS)z9Traverse the graph module and apply node_op to each node.z-Expected GraphModule or ExportedProgram, got r)output placeholdercSsg|]\}}}|qSrr)r+_r=rrrr-sz/bfs_trace_with_node_process..N) r7rr8r9 GraphModuletyper3popr.rAr:rEr!)rFrGr)queueZcurrent_graph_moduler4rDrrrrs$        rr)TN)?r/operator collectionsrcollections.abcrtypingrrrrr8Z torch.exportrZtorch.fxr Z*torch.fx.passes.utils.source_matcher_utilsr r r __all__nnZConv1dZ functionalZconv1dZConv2dZconv2dZAdaptiveAvgPool2dZadaptive_avg_pool2dZReLUZreluZrelu_Z BatchNorm2dZ batch_normZHardtanhZhardtanhZ hardtanh_riaddrimulrrr&__annotations__rrrrr r$r(r9rKboolr inttupler<Moduler>rErrrrrsp