[ONNX] Enables data propogation for onnx shape inference (#3280)

This small change seems to dramatically improve shape inference for
complex models, and consequently, improves onnx importer reliability.

projects/pt1/python/torch_mlir_e2e_test/configs/onnx_backend.py

@@ -27,6 +27,7 @@ from torch_mlir.ir import Context, Module
 def import_onnx(contents):
     # Import the ONNX model proto from the file contents:
     raw_model = onnx.load_from_string(contents)
+    # since it does not affect current e2e tests, data_prop is left false here
     model_proto = onnx.shape_inference.infer_shapes(raw_model)
 
     # Import the ONNX module into an MLIR module:

python/torch_mlir/tools/import_onnx/__main__.py

@@ -85,7 +85,9 @@ def load_onnx_model(args: argparse.Namespace) -> onnx.ModelProto:
     # in-memory shape inference.  If not, go ahead and do the shape inference.
     try:
         onnx.checker.check_model(raw_model)
-        inferred_model = onnx.shape_inference.infer_shapes(raw_model)
+        inferred_model = onnx.shape_inference.infer_shapes(
+            raw_model, data_prop=args.data_prop
+        )
         return inferred_model
     except ValueError:
         pass
@@ -103,7 +105,9 @@ def load_onnx_model(args: argparse.Namespace) -> onnx.ModelProto:
     # Model is too big for in-memory inference: do file-based shape inference
     # to a temp file.
     temp_inferred_file = temp_dir / "inferred.onnx"
-    onnx.shape_inference.infer_shapes_path(args.input_file, temp_inferred_file)
+    onnx.shape_inference.infer_shapes_path(
+        args.input_file, temp_inferred_file, data_prop=args.data_prop
+    )
 
     # Sanity check the shape-inferred model to be sure we have a good model
     # for the importer.  This call uses the file-based method, as the
@@ -138,6 +142,13 @@ def parse_arguments(argv=None) -> argparse.Namespace:
         action="store_true",
         help="Disable verification prior to printing",
     )
+    parser.add_argument(
+        "--data-prop",
+        dest="data_prop",
+        default=True,
+        action=argparse.BooleanOptionalAction,
+        help="Toggle data propogation for onnx shape inference",
+    )
     parser.add_argument(
         "--keep-temps", action="store_true", help="Keep intermediate files"
     )