def METHOD_NAME() -> List[Tuple[str, relay.Pattern, Callable[[relay.Call], bool]]]:
    """Get the cuDNN pattern table."""
    def softmax_pattern() -> relay.Pattern:
        """Create pattern for softmax."""
        return is_op("nn.softmax")(wildcard())
    def log_softmax_pattern() -> relay.Pattern:
        """Create pattern for log_softmax."""
        return is_op("nn.log_softmax")(wildcard())
    def conv2d_pattern() -> relay.Pattern:
        """Create pattern for conv2d."""
        return is_op("nn.conv2d")(wildcard(), wildcard())
    def conv2d_bias_act_pattern() -> relay.Pattern:
        """Create pattern for fused conv2d+bias+activation."""
        conv2d = is_op("nn.conv2d")(wildcard(), wildcard())
        bias = is_op("nn.bias_add")(conv2d, wildcard())
        return bias.optional(is_op("nn.relu"))
    def check_softmax(matched: relay.Call) -> bool:
        """Check if softmax is supported by cuDNN."""
        if matched.args[0].checked_type.dtype not in ["float64", "float32", "float16"]:
            return False
        return True
    def check_log_softmax(matched: relay.Call) -> bool:
        """Check if log_softmax is supported by cuDNN."""
        if matched.args[0].checked_type.dtype not in ["float64", "float32", "float16"]:
            return False
        if len(matched.args[0].checked_type.shape) != 2:
            return False
        if matched.attrs["axis"] not in (1, -1):
            return False
        return True
    def check_conv2d(matched: relay.Call) -> bool:
        if matched.args[0].checked_type.dtype not in ["float64", "float32", "float16"]:
            return False
        if matched.attrs["data_layout"] != "NCHW" or matched.attrs["kernel_layout"] != "OIHW":
            return False
        padding = matched.attrs["padding"]
        if padding[0] != padding[2] or padding[1] != padding[3]:
            return False
        return True
    def check_conv2d_bias_act(matched: relay.Call) -> bool:
        return True
    return [
        ("cudnn.softmax", softmax_pattern(), check_softmax),
        ("cudnn.log_softmax", log_softmax_pattern(), check_log_softmax),
        ("cudnn.conv2d_bias_act", conv2d_bias_act_pattern(), check_conv2d_bias_act),
        ("cudnn.conv2d", conv2d_pattern(), check_conv2d),
    ]