def METHOD_NAME(
    self,
    data_shape,
    kernel_size,
    data_layout,
    kernel_layout,
    num_filter,
    strides,
    padding,
    dilation,
    dtype,
    schedule_name,
):
    """Test a subgraph with a single conv2d_NCHWc operator."""
    ishape = data_shape
    wshape = (num_filter, data_shape[1], *kernel_size)
    weight_data = np.random.randint(low=-10, high=10, size=wshape, dtype=dtype)
    input0 = relay.var("input", relay.TensorType(ishape, dtype))
    weight0 = relay.const(weight_data)
    out0 = relay.op.nn.contrib_conv2d_nchwc(
        relay.layout_transform(input0, "NCHW", data_layout),
        relay.layout_transform(weight0, "OIHW", kernel_layout),
        kernel_size=kernel_size,
        strides=strides,
        padding=padding,
        dilation=dilation,
        data_layout=data_layout,
        kernel_layout=kernel_layout,
        channels=num_filter,
        out_dtype="",
        out_layout="",
    )
    ref_mod = tvm.IRModule.from_expr(relay.Function([input0], out0))
    input1 = relay.var("input", relay.TensorType(ishape, dtype))
    weight1 = relay.const(weight_data)
    out1 = relay.op.nn.contrib_conv2d_nchwc(
        relay.layout_transform(input1, "NCHW", data_layout),
        relay.layout_transform(weight1, "OIHW", kernel_layout),
        kernel_size=kernel_size,
        strides=strides,
        padding=padding,
        dilation=dilation,
        data_layout=data_layout,
        kernel_layout=kernel_layout,
        channels=num_filter,
        out_dtype="",
        out_layout="",
    )
    mod = tvm.IRModule.from_expr(relay.Function([input1], out1))
    inputs = {"input": np.random.randint(low=-128, high=127, size=ishape, dtype=dtype)}
    output_list = generate_ref_data(ref_mod, inputs)
    compile_and_run(
        AOTTestModel(module=mod, inputs=inputs, outputs=output_list),
        runner=AOT_CORSTONE300_RUNNER,
        interface_api="c",
        use_unpacked_api=True,
        target_opts={
            "-keys": "arm_cpu",
            "-mcpu": "cortex-m7",
        },
        schedule_name=schedule_name,
    )