o ;ήc@sdddlmZddlmZddlmZddlmZddlm Z ddl m Z ee Z GdddeZd S) ) getLogger)Dict)Fusion) FusionUtils)helper) OnnxModelcs4eZdZdeffdd ZdedefddZZS) FusionQOrderedLayerNormalizationmodelcst|dddS)NQOrderedLayerNormalizationLayerNormalization)super__init__)selfr  __class__Y/tmp/pip-target-vg8gfxp4/lib/python/onnxruntime/transformers/fusion_qordered_layernorm.pyr sz)FusionQOrderedLayerNormalization.__init__input_name_to_nodesoutput_name_to_nodecCs|j||}t|dkr|djdks*t|dkr(|djdkr(|djdks*dS|d}d}t|dkr:|d}t||jsCdS|j|dgdgfg|\}}} |dkrYdS|d} t| |jsfdS|g} | |g|j| |} t| dkr| | g|j| |dur|j d|j dgn|j ||st ddS|j | t jd | jd| jd|jd|jd|jdg|j dg|jjd d d d } |dur|j||jd|j d| jt d dg| jt d dgd| _|j| |j|j| j<dS)a{ Fuse (quantized) Layer Normalization subgraph into one node QOrderedLayerNormalization: quantized input -> DQ | | (other inputs)-> LayerNormalization --> Q --> should become (quantized input + other inputs)-> QOrderedLayerNormalization --> Q --> rQuantizeLinearShapeNDequantizeLinearzs