*   `tflite::Interpreter::signature_keys`
       *   `tflite::Interpreter::signature_inputs`
       *   `tflite::Interpreter::signature_outputs`
       *   `tflite::Interpreter::input_tensor_by_signature`
       *   `tflite::Interpreter::output_tensor_by_signature`

    *  Similarly, the following signature runner functions in the TF Lite C API are no longer considered experimental:

       *    `TfLiteInterpreterGetSignatureCount`

		{"Or", Func, 22},
		{"Ordered", Type, 21},
	},
	"compress/bzip2": {
		{"(StructuralError).Error", Method, 0},
		{"NewReader", Func, 0},
		{"StructuralError", Type, 0},
	},
	"compress/flate": {
		{"(*ReadError).Error", Method, 0},
		{"(*WriteError).Error", Method, 0},
		{"(*Writer).Close", Method, 0},
		{"(*Writer).Flush", Method, 0},
		{"(*Writer).Reset", Method, 2},
		{"(*Writer).Write", Method, 0},

testing or for special case where a user intends to pass custom MLIR computation
through a TensorFlow graph with the intent of having custom tooling processing
it downstream (when targeting a different environment, like TensorFlow lite for
example).
The MLIR module is expected to have a main() function that will be used as an
entry point. The inputs to the operations will be passed as argument to the