tjLUddlZddlmZddlmZddlmZmZddlZddl Zddl m Z ddl m Z ddlmZmZddlmZdd lmZerddlZd Znedzed < ddlZd Zn#e$rd ZdZYnwxYwd gZddddddZgdZddddZer!e d Gdd ZdSes!e d Gdd ZdSdS)N)chain) ModuleType)Any TYPE_CHECKING) compatibility)_parse_stack_trace) _format_arg_get_qualified_name)normalize_function)TensorMetadataTpydotF FxGraphDrawerz "AliceBlue" LemonChiffon1Yellow2 LightGrey PowderBlue) placeholder call_module get_paramget_attroutput) CadetBlue1CoralDarkOliveGreen1 DarkSeaGreen1 GhostWhiteKhaki1LavenderBlush1 LightSkyBlue MistyRose1 MistyRose2PaleTurquoise2 PeachPuff1SalmonThistle1Thistle3Wheat1r$"filled,rounded"#000000) fillcolorstyle fontcolor)is_backward_compatibleceZdZdZ d%dejjdededed ed ed edzd ed dfdZ d&dedzd e j fdZ d e j fdZ ded e j fdZd eee j ffdZdejjd eeeffdZdejjdejjd ejjfdZdejjjejjzd efdZ d'deded efdZdejjdejjd ed ed ef dZded efd Zded efd!Zd"ej d efd#Z!dejjdededed ed ed e j fd$Z"dS)(rz Visualize a torch.fx.Graph with graphviz Basic usage: g = FxGraphDrawer(symbolic_traced, "resnet18") g.get_dot_graph().write_svg("a.svg") FTN graph_modulenameignore_getattrignore_parameters_and_buffersskip_node_names_in_argsparse_stack_tracedot_graph_shapenormalize_argsreturnc ||_||nd|_||_|jtd<||||||||i|_|jjD]z} | jdkr| || } t| tj j sD|| |d| j|||||j|d| j<{dS)Nrecordshaper_)_namer5r6_WEIGHT_TEMPLATE_to_dot _dot_graphsgraphnodesop_get_leaf_node isinstancetorchfx GraphModuletarget) selfr/r0r1r2r3r4r5r6node leaf_nodes Z/var/www/html/CA-Chatbot/venv/lib/python3.11/site-packages/torch/fx/passes/graph_drawer.py__init__zFxGraphDrawer.__init__LsDJ#2#>H  #1D (,(< W %dll "1+%  D %*0  7m++ // dCC !)UX-ABB<@LL++dk++"1+% == D!8!84;!8!899   submod_namecX||S||S)aA Visualize a torch.fx.Graph with graphviz Example: >>> # xdoctest: +REQUIRES(module:pydot) >>> # xdoctest: +REQUIRES(module:ubelt) >>> # define module >>> class MyModule(torch.nn.Module): >>> def __init__(self) -> None: >>> super().__init__() >>> self.linear = torch.nn.Linear(4, 5) >>> def forward(self, x): >>> return self.linear(x).clamp(min=0.0, max=1.0) >>> module = MyModule() >>> # trace the module >>> symbolic_traced = torch.fx.symbolic_trace(module) >>> # setup output file >>> import ubelt as ub >>> dpath = ub.Path.appdir("torch/tests/FxGraphDrawer").ensuredir() >>> fpath = dpath / "linear.svg" >>> # draw the graph >>> g = FxGraphDrawer(symbolic_traced, "linear") >>> g.get_dot_graph().write_svg(fpath) )get_main_dot_graphget_submod_dot_graphrIrOs rL get_dot_graphzFxGraphDrawer.get_dot_graph{s00"..00000===rNc&|j|jSNr?r<rIs rLrQz FxGraphDrawer.get_main_dot_graphs#DJ/ /rNc0|j|jd|S)Nr;rWrSs rLrRz"FxGraphDrawer.get_submod_dot_graphs #tz$A$AK$A$AB BrNc|jSrV)r?rXs rLget_all_dot_graphsz FxGraphDrawer.get_all_dot_graphss # #rNrJc|jdddd}|jtvrt|j|d<n||j}t t j|d ddd }t|ttz|d<|S) Nz#CAFFE3r(r))r:r*r+r,r*F)usedforsecurity) r5rB _COLOR_MAP_pretty_print_targetrHinthashlibmd5encode hexdigest_HASH_COLOR_MAPlen)rIrJtemplate target_name target_hashs rL_get_node_stylezFxGraphDrawer._get_node_styles-&+& H w*$$(247(;%%#77 DD !K#**,,eikk"1"&  )8#o"6"66)%OrNmodulecN|}t|jts$tdt |j|jd}|D]G}t ||s%tt|dz|zdzt||}H|S)NzExpected str target, got .z does not have attribute !) rDrHstrAssertionErrortypesplithasattr RuntimeErrorgetattr)rIrmrJpy_objatomsatoms rLrCzFxGraphDrawer._get_leaf_nodesFdk3// V$%TdkARAR%T%TUUUK%%c**E / /vt,,&F &AADH3N!..MrNrHc t|tjjrtj|}n't|t r|}nt |}|ddddS)N{\{}\})rDrEnnModuletypenamerqr replace)rIrHrets rL _typenamezFxGraphDrawer._typenamesu&%(/22 2nV,,FC(( 2)&11 ;;sE**223>> >rNfull_file_nametruncate_to_last_nc|d}t||krd|| dS|S)N/)rtrhjoin)rIrrsplitss rL_shorten_file_namez FxGraphDrawer._shorten_file_namesP $))#..F6{{000xx(:':';'; <===! 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