feat: an option to show MLIR

closes #224

hdk/hnumpy/compile.py

@@ -132,6 +132,7 @@ def compile_numpy_function(
     dataset: Iterator[Tuple[Any, ...]],
     compilation_configuration: Optional[CompilationConfiguration] = None,
     compilation_artifacts: Optional[CompilationArtifacts] = None,
+    show_mlir: bool = False,
 ) -> CompilerEngine:
     """Main API of hnumpy, to be able to compile an homomorphic program.
 
@@ -146,6 +147,8 @@ def compile_numpy_function(
             during compilation
         compilation_artifacts (Optional[CompilationArtifacts]): Artifacts object to fill
             during compilation
+        show_mlir (bool): if set, the MLIR produced by the converter and which is going
+            to be sent to the compiler backend is shown on the screen, e.g., for debugging or demo
 
     Returns:
         CompilerEngine: engine to run and debug the compiled graph
@@ -171,6 +174,9 @@ def compile_numpy_function(
     converter = MLIRConverter(V0_OPSET_CONVERSION_FUNCTIONS)
     mlir_result = converter.convert(op_graph)
 
+    if show_mlir:
+        print(f"MLIR which is going to be compiled: \n{mlir_result}")
+
     # Compile the MLIR representation
     engine = CompilerEngine()
     engine.compile_fhe(mlir_result)

tests/hnumpy/test_compile.py

@@ -236,3 +236,33 @@ def test_compile_function_with_dot(function, params, shape, ref_graph_str):
         f"\n==================\nExpected {ref_graph_str}"
         f"\n==================\n"
     )
+
+
+@pytest.mark.parametrize(
+    "function,input_ranges,list_of_arg_names",
+    [
+        pytest.param(lambda x: x + 64, ((0, 10),), ["x"]),
+        pytest.param(lambda x: x * 3, ((0, 40),), ["x"]),
+        pytest.param(lambda x: 120 - x, ((40, 80),), ["x"]),
+        pytest.param(lambda x, y: x + y + 64, ((0, 20), (0, 20)), ["x", "y"]),
+        pytest.param(lambda x, y: 100 - y + x, ((0, 20), (0, 20)), ["x", "y"]),
+        pytest.param(lambda x, y: 50 - y * 2 + x, ((0, 20), (0, 20)), ["x", "y"]),
+    ],
+)
+def test_compile_with_show_mlir(function, input_ranges, list_of_arg_names):
+    """Test show_mlir option"""
+
+    def data_gen(args):
+        for prod in itertools.product(*args):
+            yield prod
+
+    function_parameters = {
+        arg_name: EncryptedValue(Integer(64, False)) for arg_name in list_of_arg_names
+    }
+
+    compile_numpy_function(
+        function,
+        function_parameters,
+        data_gen(tuple(range(x[0], x[1] + 1) for x in input_ranges)),
+        show_mlir=True,
+    )