def METHOD_NAME(
    in_dtype,
    kernel_dtype,
    kernel_zero_point,
):
    """Tests fully connected layer with non int8 inputs"""
    in_shape = (2, 28)
    out_channels = 2
    input_scale = 1
    input_zero_point = 24
    kernel_scale = [0.11, 0.0237]
    _, bias_dtype = get_kernel_bias_dtype(in_dtype)
    kernel_shape = [out_channels, in_shape[1]]
    conv2d_kernel_shape = [1, 1, kernel_shape[0], kernel_shape[1]]
    output_scale, output_zero_point = get_conv2d_qnn_params(
        conv2d_kernel_shape,
        input_scale,
        input_zero_point,
        kernel_scale,
        kernel_zero_point,
        in_dtype,
        kernel_dtype,
        in_dtype,
    )
    model, params = make_model(
        in_shape=in_shape,
        kernel_shape=kernel_shape,
        input_zero_point=input_zero_point,
        kernel_zero_point=kernel_zero_point,
        input_scale=input_scale,
        kernel_scale=kernel_scale,
        output_zero_point=output_zero_point,
        output_scale=output_scale,
        dtype=in_dtype,
        kernel_dtype=kernel_dtype,
        bias_dtype=bias_dtype,
        out_channels=out_channels,
        enable_bias=True,
    )
    orig_mod = make_module(model)
    cmsisnn_mod = cmsisnn.partition_for_cmsisnn(orig_mod, params)
    # validate pattern matching
    assert_no_external_function(cmsisnn_mod)