import torch                                                                                                           
from nvfuser import FusionDefinition, DataType                                                                         
                                                                                                                       
def nvfuser_fusion_id9(fd : FusionDefinition) -> None :                                                                                                                                                                                       
    T0 = fd.define_tensor(shape=[1, -1, -1], contiguity=[None, True, True], dtype=DataType.Float, is_cpu=False, stride_order=[2, 1, 0])
    T1 = fd.define_tensor(shape=[-1, -1], contiguity=[True, True], dtype=DataType.Float, is_cpu=False, stride_order=[1, 0])
    T2 = fd.ops.sum(T1, axes=[1], keepdim=False, dtype=DataType.Null)                                                                                                                                                                         
    T3 = fd.ops.sum(T0, axes=[1, 0], keepdim=False, dtype=DataType.Null)                                                                                                                                                                      
    S4 = fd.define_scalar(4, dtype=DataType.Int)                                                                                                                                                                                              
    V5 = fd.define_vector([S4], dtype=DataType.Int)                                                                                                                                                                                           
    T6 = fd.ops.reshape(T2, new_shape=V5)                                                                                                                                                                                                     
    S7 = fd.define_scalar(4, dtype=DataType.Int)                                                                       
    V8 = fd.define_vector([S7], dtype=DataType.Int)                                                                                                                                                                                           
    T9 = fd.ops.reshape(T3, new_shape=V8)                                                                              
    T10 = fd.ops.mul(T6, T9)                                                                                                                                                                                                                  
    T11 = fd.ops.sum(T10, axes=[0], keepdim=False, dtype=DataType.Null)                                                
    fd.add_output(T11)                                                                                                                                                                                                                        
                                                                                                                       
with FusionDefinition() as fd:                                                                                                                                                                                                                
    nvfuser_fusion_id9(fd)                                                                                                                                                                                                                    
                                                                                                                                                                                                                                              
inputs = [                                                                                                                                                                                                                                        torch.randn((12,), dtype=torch.float32, device='cuda:0').as_strided((1, 3, 4), (12, 4, 1)),            
    torch.randn((12,), dtype=torch.float32, device='cuda:0').as_strided((4, 3), (3, 1)),                                                                                                                                                      
]                                                                                                                      
fd.execute(inputs)