Method main

tests/python/relax/test_frontend_from_fx.py:69–91

(
            input_1: R.Tensor((1, 3, 10), dtype="float32"),
            w1: R.Tensor((6, 3, 7), dtype="float32"),
            w2: R.Tensor((6,), dtype="float32"),
        )

    class expected1:
        @R.function
        def main(
            input_1: R.Tensor((1, 3, 10), dtype="float32"),
            w1: R.Tensor((6, 3, 7), dtype="float32"),
            w2: R.Tensor((6,), dtype="float32"),
        ) -> R.Tensor((1, 6, 4), dtype="float32"):
            # block 0
            with R.dataflow():
                lv1: R.Tensor((1, 6, 4), dtype="float32") = R.nn.conv1d(
                    input_1,
                    w1,
                    strides=[1],
                    padding=[0, 0],
                    dilation=[1],
                    data_layout="NCW",
                    kernel_layout="OIW",
                    out_layout="NCW",
                    out_dtype="float32",
                )
                lv2: R.Tensor((1, 6, 1), dtype="float32") = R.reshape(w2, [1, 6, 1])
                lv3: R.Tensor((1, 6, 4), dtype="float32") = R.add(lv1, lv2)
                gv: R.Tensor((1, 6, 4), dtype="float32") = lv3
                R.output(gv)
            return gv

    class Conv1D2(Module):
        def __init__(self):