matmul expreval cannot handle output stride order

[jjsjann123]

This is to follow up with #2426 's comment #2354 (comment)

import torch
from nvfuser import FusionDefinition, DataType

def fusion_func(fd: FusionDefinition):
    T0 = fd.define_tensor(shape=[-1, -1], contiguity=[True, True], dtype=DataType.Float, is_cpu=False, stride_order=[1, 0])
    T1 = fd.define_tensor(shape=[-1, -1, -1], contiguity=[True, True, True], dtype=DataType.Float, is_cpu=False, stride_order=[2, 1, 0])                                                                                                                                  
    T2 = fd.ops.linear(T1, T0)
    S3 = fd.define_scalar(1.41421, dtype=DataType.Double)
    T4 = fd.ops.mul(T2, S3)
    fd.add_output(T2, (2, 1, 0))
    fd.add_output(T4)

with FusionDefinition() as fd:
    fusion_func(fd)
                                                                                                                 
inputs = [
    torch.randn((8, 4), dtype=torch.float32, device='cuda:0'),
    torch.randn((6, 8, 4,), dtype=torch.float32, device='cuda:0')
]
fd.execute(inputs)