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    [inference][cherrypick] Implement layer_norm op using INormalization Layer and... · 188871e6
    Zhang Jun 提交于
    [inference][cherrypick] Implement layer_norm op using INormalization Layer and conv_fusion support bias's rank equal to input's rank  (#54590)
    
    * [inference]conv_fusion support bias's rank equal to input's rank (#54477)
    
    * support bias's rank equal to input's rank
    
    * [inference][trt]layer_norm op with dynamic shape support INormalizationLayer in TRT8.6 (#54379)
    
    * layer_norm op with dynamic shape support INormalizationLayer in TRT8.6
    
    * Using trt layer to make layers_norm op in lower than trt8.6
    layer_norm op with dynamic shape support INormalizationLayer in TRT8.6
    
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    Co-authored-by: Nbukejiyu <52310069+bukejiyu@users.noreply.github.com>
    188871e6
test_trt_convert_layer_norm.py 10.1 KB