U U?h(@s@ddlmZddlZddlmZddlmZGdddeZdS) ) annotationsN) ONNXModel)FusioncspeZdZddfdd Zddddd d Zdddd d d dZdddd d ddZdddd d ddZZS) FusionGelur)modelcst|dddS)NGeluZErf)super__init__)selfr __class__^/var/www/html/venv/lib/python3.8/site-packages/onnxruntime/quantization/fusions/fusion_gelu.pyr szFusionGelu.__init__zonnx.NodeProtozdict[str, list[onnx.NodeProto]]zdict[str, onnx.NodeProto])erf_nodeinput_name_to_nodesoutput_name_to_nodecCs<||||s*||||s*||||r8|jdddS)z Interface function that tries to fuse a node sequence containing an Erf node into a single Gelu node. com.microsoftrN)fuse_1fuse_2fuse_3rZset_opset_import)r rrrrrrfuses   zFusionGelu.fusebool)rrrreturncCs |jd|krdS||jd}t|dks:|djdkr>dS|d}||dsVdS|jd|krhdS||jd}t|dks|djdkrdS|d}||dd|}|dkrdS|j|dd d dkrdS|jd}|jd|jdkrdnd} ||j| kr\||jd}t|dks2|djdkr6dS|d} || d sPdS| jd} nJ||d| |} | dkrzdS|| d sdS|| jkrdS|jd} ||||| g} || | g||sdS|j | t j j d | |g| gd } d| _|j| dS)ay This pattern is from PyTorch model Fuse Gelu with Erf into one node: Pattern 1: +-------Mul(0.5)---------------------+ | | | v [root] --> Div -----> Erf --> Add --> Mul --> (B=1.4142...) (1) Pattern 2: +------------------------------------+ | | | v [root] --> Div -----> Erf --> Add --> Mul -->Mul --> (B=1.4142...) (1) (0.5) Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine. rFrAddMulDivN -?MbP?delta?r nameinputsoutputsrToutputlenop_typehas_constant_input match_parentfind_constant_inputinputis_safe_to_fuse_nodesnodes_to_removeextendonnxhelper make_nodecreate_unique_node_namedomain nodes_to_addappend)r rrrchildren add_after_erf mul_after_erfdivsubgraph_inputZanothermul_halfZsubgraph_outputsubgraph_nodes fused_noderrrr#sd        zFusionGelu.fuse_1c Cs|jd|krdS||jd}t|dks:|djdkr>dS|d}||dsVdS|jd|krhdS||jd}t|dks|djdkrdS|d}||dsdS|jd|krdS||jd}t|dks|djdkrdS|d}||dd|}|dkrdSd} |j|d d d dkrZ||d d|} | dkrHdS|| d sZdS|jd} | |jkrtdS|||||g} | r| | || |jdg||sdS|j | t j j d|| g|jdgd} d| _|j| dS)a& This pattern is from Keras model Fuse Gelu with Erf into one node: +------------------------------------------+ | | | v [root] --> Div -----> Erf --> Add --> Mul -->Mul (B=1.4142...) (A=1) (A=0.5) Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine. rFrrrr"rNrrr ZSqrtg@r r#rT)r(r)r*r+r,r-r.r8r/r0r1r2r3r4r5r6r7) r rrrr9r:r;mulr<Z sqrt_noder=r?r@rrrrzsd          zFusionGelu.fuse_2cCs|jd|krdS||jd}t|dks:|djdkr>dS|d}||dsVdS|jd|krhdS||jd}t|dks|djdkrdS|d}||dsdS||dd|}|dkrdS|j|dd d }|dkrdSd|} |j| } |jd|kr dS||jd}t|dks6|djdkr:dS|d} | jd| ksf| jd| ksfdS||||| g} || | jdg||sdS|j | t j j d | | g| jdgd } d | _|j| dS)a? This pattern is from TensorFlow model Fuse Gelu with Erf into one node: +----------------------------------------------+ | | | v [root] --> Mul -----> Erf --> Add --> Mul -->Mul (A=0.7071067690849304) (B=1) (B=0.5) Note that constant input for Add and Mul could be first or second input: like either A=0.5 or B=0.5 is fine. rFrrrr"Ng`?rr r r#rTr')r rrrr9r:r>Z first_muliZroot_input_indexr=Zlast_mulr?r@rrrrsd        zFusionGelu.fuse_3) __name__ __module__ __qualname__r rrrr __classcell__rrr rrs WLr) __future__rr2Z onnx_modelrZfusionrrrrrrs