o ߗi+@sdddlZddlZddlmZddlmZmZmZmZm Z m Z m Z m Z ddl Z ddlZ ddlmZddlmZgdZe e e jee jfZe e jefZee jjZe e jjZeeZhdZedd d d Zedd d eee jj fd e jjdefddZ!edd d e jjde"fddZ#edd GdddZ$edd de jj%de jj%fddZ&dS)N) dataclass)AnyDictListMappingOptionalSetTupleUnion) compatibility)_get_qualified_name)get_acc_ops_nameget_node_targetis_node_output_tensorFxNetAccFusionsFinderlegalize_graph> call_method call_module call_functionF)is_backward_compatiblecCsPt|tr|S|jrd|jvrd|jS|jdd}|r |ndd|jS)Nacc_opsacc_ops.z torch._opsz torch.ops.) isinstancestr __module____name__replace)kmoduler!Z/home/ubuntu/transcripts/venv/lib/python3.10/site-packages/torch/fx/passes/tools_common.pyr s  r submodulesnodereturncCs|jtvsJddtd|j|jdkr2t|jts!J||j}t|dt|}t|S|jdkrN|j}|j durJd|j vrJd |j St |St|jtsVJ|jS) a, Given a `node` returns its target typename. For "call_method" node, return node.target which is the name of that method being called. This could potential lead to conflict but should be okay because normally it's on a tensor. For "call_function" node, return typename of node.target. For "call_module" node, return typename of the module that node.target point to. If seeing "_VariableFunctionsClass" in the target name string, it will be replaced by "torch". e.g. _VariableFunctionsClass.relu would become torch.relu. zExpect op types of z, z , but found r_base_class_originrNrr) opCALLABLE_NODE_OPSjoinrtargetrgetattrtyper rrr )r#r$submod submod_typer*r!r!r"r*s"     rcCs"|jdd}|duot|tjS)aChecks if the node output produces a Tensor or not. NOTE: This requires to run `ShapeProp` on the containing fx graph before calling this function. This is because it works by checking the `type` metadata on the node. This metadata is produced by the `ShapeProp`. r,N)metaget issubclasstorchTensor)r$type_r!r!r"rQsrc@sxeZdZdZdejjdefddZe GdddZ dd d d e ee fd e efd dZdeejjeffddZdS)rz Finds groups of connected ACC nodes that pass non-tensor data between each other. Such groups are called fusion groups. r acc_nodescCs||_t|jj|_||_dSN)r listgraphnodesr5)selfr r5r!r!r"__init__ds zFxNetAccFusionsFinder.__init__c@s6eZdZUeed<eed<eed<eed<ddZdS)!FxNetAccFusionsFinder.FusionGroup top_node_idxr9inputsnodes_need_processcsR|jvrdSj|j|j|jfdd|jDdS)z5 Add a node to fusion group. Ncs$h|]}|jtvr|jvr|qSr!)r'r(r9).0nr:r!r" s z=FxNetAccFusionsFinder.FusionGroup.add_node..)r9r?addr>discardupdateall_input_nodes)r:r$r!rBr"add_nodews     z*FxNetAccFusionsFinder.FusionGroup.add_nodeN)rr __qualname__int__annotations__NodeSetrHr!r!r!r" FusionGroupis  rMN fusion_groupr<r>visitedcCsz|D]8}|dur||vr q|||jtvrq|j||jkr"q||jvr*dS|||j|r:||dSqdS)z Start from inputs and going reverse topological order. If any upstream node is in the fusion group, add all the nodes in this path to fusion group. NTF) rDr'r(r9indexr=recursive_add_noderGrH)r:rNr>rOargr!r!r"rQs      z(FxNetAccFusionsFinder.recursive_add_noder%cCsi}t|j}|D]}||vrq |jtvrq d|jvrq ||jvr"q |j|j||ht|j |hd}|j r|j }|j ||j tdd|jvrl|jD]}|jtvrVqN||jvr\qN|||j ||j tdqN|j D].}|jtvrwqod|jvr}qo||jvrqo||t|j|j||_|j ||j tdqo|j s7t|j|jks|j|j8_q |jD]}|j||<qq |S)N tensor_meta)r=r9r>r?)rO)r7r5r'r(r/rMr9rPsetrGr?poprQr>usersrHminr=)r:resultr5r$rNuserrRrAr!r!r"__call__sv                *  zFxNetAccFusionsFinder.__call__r6)rrrI__doc__r2fx GraphModulerLr;rrMr NodeListrrQrNoderZr!r!r!r"r]s#  &rgmcstjtjtjtjtjtjtjtjtj tj tj tj t jjjjt jjjjt jjjjt jjjjt jjjjg}t|jjdt j}|jjD]}|jD] }|d7<qIqDt}|jjD] }|dkrj| |q]it!|dkr|"}|#|fdd|<|jD]%}|d8<|dkr|j$dkr|j%|vr|&|q| |qt!|dksst!|jt!|jjkrt'dfddD|jj(|_(||_|S) a Replace the graph of the given GraphModule with one that contains the same nodes as the original, but in topologically sorted order. This is used by the merge_matmul transformation below, which disturbs the topologically sorted order of its input GraphModule, so that this order is restored before further transformation. Arguments: gm: The graph module to topologically sort. It is modified in-place. Returns: The graph module in-place sorted rcs|Sr6r!)x)envr!r".sz legalize_graph..rz&Input graph has cycles, unable to add csg|] }|dkr|qS)rr!)r@r$)indegr!r" :sz"legalize_graph..))operatorrDmulsubfloordivtruedivmodleltgegteqner2opsatensym_constrain_rangedefaultsym_constrain_range_for_size _assert_asyncmsg scalar_tensor_assert_scalardictfromkeysr8r9r\GraphrV collectionsdequeappendlenpopleft node_copyr'r* appendleft RuntimeError_codegen)r`PRIORITIZED_OPS new_graphr$rYqueuecurr!)rcrer"rs`                   r)'rrg dataclassesrtypingrrrrrrr r r2torch.fxtorch.fx._compatibilityr torch.fx.noder __all__r3TensorsTensorOrTensorsr\r_r^rLrNamesr(r nnModulerboolrrr]rr!r!r!r"s@ (       &