Nothing
graph(%self : __torch__.nn_linear_ydgabwknrsauujvnjgioueiy,
%3 : Float(10, 10, strides=[10, 1], requires_grad=0, device=cpu)):
%bias : Tensor = prim::GetAttr[name="bias"](%self)
%weight : Tensor = prim::GetAttr[name="weight"](%self)
%4 : Float(10, 10, strides=[10, 1], requires_grad=1, device=cpu) = aten::linear(%3, %weight, %bias)
return (%4)
graph(%self : __torch__.nn_linear_ydgabwknrsauujvnjgioueiy,
%3 : Float(10, 10, strides=[10, 1], requires_grad=0, device=cpu)):
%bias : Tensor = prim::GetAttr[name="bias"](%self)
%weight : Tensor = prim::GetAttr[name="weight"](%self)
%4 : Float(10, 10, strides=[10, 1], requires_grad=1, device=cpu) = aten::linear(%3, %weight, %bias)
return (%4)
graph(%self : __torch__.nn_linear_neebjyloatcfjjfottzlywfy,
%1 : Tensor):
%bias : Tensor = prim::GetAttr[name="bias"](%self)
%weight : Tensor = prim::GetAttr[name="weight"](%self)
%5 : Tensor = prim::profile[profiled_type=Float(10, 10, strides=[10, 1], requires_grad=0, device=cpu), seen_none=0](%1)
%6 : Tensor = prim::profile[profiled_type=Float(10, 10, strides=[10, 1], requires_grad=1, device=cpu), seen_none=0](%weight)
%7 : Tensor = prim::profile[profiled_type=Float(10, strides=[1], requires_grad=1, device=cpu), seen_none=0](%bias)
%4 : Tensor = aten::linear(%5, %6, %7)
%8 : Tensor = prim::profile[profiled_type=Float(10, 10, strides=[10, 1], requires_grad=1, device=cpu), seen_none=0](%4)
= prim::profile()
return (%8)
graph(%self : __torch__.nn_linear_neebjyloatcfjjfottzlywfy,
%1 : Tensor):
%bias : Tensor = prim::GetAttr[name="bias"](%self)
%weight : Tensor = prim::GetAttr[name="weight"](%self)
%22 : Tensor = aten::linear(%1, %weight, %bias)
return (%22)
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