[mpact][compiler] extract linalg module import into own method

python/mpact/mpactbackend.py

@@ -319,9 +319,8 @@ def export_and_import(f, *args, **kwargs):
     return fx_importer.module
 
 
-def mpact_jit_compile(f, *args, opt_level=2, use_sp_it=False, **kwargs):
-    """This method compiles the given callable using the MPACT backend."""
-    # Import module and lower into Linalg IR.
+def mpact_linalg(f, *args, **kwargs):
+    """Imports a function as module and lowers it into Linalg IR."""
     module = export_and_import(f, *args, **kwargs)
     run_pipeline_with_repro_report(
         module,
@@ -333,7 +332,12 @@ def mpact_jit_compile(f, *args, opt_level=2, use_sp_it=False, **kwargs):
         "Lowering TorchFX IR -> Linalg IR",
         enable_ir_printing=False,
     )
-    # Compile with MPACT backend compiler.
+    return module
+
+
+def mpact_jit_compile(f, *args, opt_level=2, use_sp_it=False, **kwargs):
+    """This method compiles the given callable using the MPACT backend."""
+    module = mpact_linalg(f, *args, **kwargs)
     backend = MpactBackendCompiler(opt_level=opt_level, use_sp_it=use_sp_it)
     compiled = backend.compile(module)
     invoker = backend.load(compiled)

test/python/mm_print.py

@@ -0,0 +1,31 @@
+# RUN: %PYTHON %s | FileCheck %s
+
+import torch
+import numpy as np
+
+from mpact.mpactbackend import mpact_linalg
+
+from mpact.models.kernels import MMNet
+
+
+net = MMNet()
+
+X = torch.arange(0, 16, dtype=torch.float32).view(4, 4)
+Y = torch.arange(16, 32, dtype=torch.float32).view(4, 4)
+
+#
+# CHECK: module {
+# CHECK:   func.func @main(%[[A0:.*]]: tensor<4x4xf32>, %[[A1:.*]]: tensor<4x4xf32>) -> tensor<4x4xf32> {
+# CHECK:    %[[C0:.*]] = arith.constant 0.000000e+00 : f32
+# CHECK:    %[[T0:.*]] = tensor.empty() : tensor<4x4xf32>
+# CHECK:    %[[T1:.*]] = linalg.fill ins(%[[C0]] : f32) outs(%[[T0]] : tensor<4x4xf32>) -> tensor<4x4xf32>
+# CHECK:    %[[T2:.*]] = linalg.matmul
+# CHECK-SAME:              ins(%[[A0]], %[[A1]] : tensor<4x4xf32>, tensor<4x4xf32>)
+# CHECK-SAME:              outs(%[[T1]] : tensor<4x4xf32>) -> tensor<4x4xf32>
+# CHECK:    return %2 : tensor<4x4xf32>
+# CHECK:   }
+# CHECK: }
+#
+
+linalg = mpact_linalg(net, X, Y)
+print(linalg)