From 5864a59de870dffa3c9bb94e503d88b5e44d10d4 Mon Sep 17 00:00:00 2001
From: klemen1999 <klemenskrlj8@gmail.com>
Date: Fri, 12 Jun 2026 15:38:51 +0200
Subject: [PATCH] ONNX modifications with no op exit early

---
 modelconverter/utils/config.py     | 15 ++++++
 modelconverter/utils/metadata.py   | 12 +++--
 modelconverter/utils/onnx_tools.py | 15 ++++--
 tests/test_utils/test_config.py    | 76 +++++++++++++++++++++---------
 4 files changed, 86 insertions(+), 32 deletions(-)

diff --git a/modelconverter/utils/config.py b/modelconverter/utils/config.py
index 06055f2f..e779f59e 100644
--- a/modelconverter/utils/config.py
+++ b/modelconverter/utils/config.py
@@ -222,6 +222,21 @@ def _parse_values(
             return [value, value, value]
         return value
 
+    def requires_onnx_input_modification(
+        self, *, reverse_only: bool = False
+    ) -> bool:
+        if self.encoding_mismatch:
+            return True
+        if reverse_only:
+            return False
+        return (
+            self.mean_values is not None
+            and any(v != 0 for v in self.mean_values)
+        ) or (
+            self.scale_values is not None
+            and any(v != 1 for v in self.scale_values)
+        )
+
 
 class TargetConfig(BaseModelExtraForbid):
     disable_calibration: bool = False
diff --git a/modelconverter/utils/metadata.py b/modelconverter/utils/metadata.py
index 3798d82f..5f8cb81b 100644
--- a/modelconverter/utils/metadata.py
+++ b/modelconverter/utils/metadata.py
@@ -45,10 +45,14 @@ def _get_metadata_dlc(path: Path) -> Metadata:
     if path.suffix == ".csv":
         csv_path = path
     else:
-        csv_path = Path("info.csv")
-        subprocess_run(
-            ["snpe-dlc-info", "-i", path, "-s", csv_path], silent=True
-        )
+        csv_path = path.with_suffix(".info.csv")
+        if (
+            not csv_path.exists()
+            or csv_path.stat().st_mtime < path.stat().st_mtime
+        ):
+            subprocess_run(
+                ["snpe-dlc-info", "-i", path, "-s", csv_path], silent=True
+            )
     content = csv_path.read_text()
 
     metadata = {}
diff --git a/modelconverter/utils/onnx_tools.py b/modelconverter/utils/onnx_tools.py
index 65b76edb..3ffa46f3 100644
--- a/modelconverter/utils/onnx_tools.py
+++ b/modelconverter/utils/onnx_tools.py
@@ -111,6 +111,15 @@ def onnx_attach_normalization_to_inputs(
     *,
     reverse_only: bool = False,
 ) -> Path:
+    if not any(
+        cfg.requires_onnx_input_modification(reverse_only=reverse_only)
+        for cfg in input_configs.values()
+    ):
+        logger.info(
+            "No ONNX input normalization changes requested; using original model."
+        )
+        return model_path
+
     model = onnx.load(str(model_path))
     if model_path.with_suffix(".onnx_data").exists():
         model_data_path = str(model_path).replace(".onnx", ".onnx_data")
@@ -136,11 +145,7 @@ def onnx_attach_normalization_to_inputs(
         if input_name not in input_configs:
             continue
         cfg = input_configs[input_name]
-        if (
-            cfg.encoding.from_ == cfg.encoding.to
-            and cfg.mean_values is None
-            and cfg.scale_values is None
-        ):
+        if not cfg.requires_onnx_input_modification(reverse_only=reverse_only):
             continue
 
         shape = cfg.shape
diff --git a/tests/test_utils/test_config.py b/tests/test_utils/test_config.py
index 28a19a99..a9b8cc7a 100644
--- a/tests/test_utils/test_config.py
+++ b/tests/test_utils/test_config.py
@@ -4,6 +4,7 @@
 import tarfile
 import tempfile
 from pathlib import Path
+from textwrap import dedent
 
 import numpy as np
 import onnx
@@ -248,29 +249,34 @@ def create_json(
 
 def create_yaml(append: str = "") -> str:
     config = (
-        f"""
-input_model: "{DATA_DIR}/dummy_model.onnx"
-mean_values: "imagenet"
-data_type: float32
-shape: [ 1, 3, 256, 256 ]
-
-calibration:
-  path: "{CALIBRATION_DATA_DIR_1}"
-  max_images: 20
-
-hailo:
-  optimization_level: 3
-  compression_level: 3
-  batch_size: 4
-
-inputs:
-  - name: "input0"
-    scale_values: [255,255,255]
-    shape: [1, 3, 64, 64]
-    layout: "NCHW"
-    calibration:
-      max_images: 100
-"""
+        dedent(
+            """
+        input_model: "{data_dir}/dummy_model.onnx"
+        mean_values: "imagenet"
+        data_type: float32
+        shape: [ 1, 3, 256, 256 ]
+
+        calibration:
+          path: "{calibration_data_dir_1}"
+          max_images: 20
+
+        hailo:
+          optimization_level: 3
+          compression_level: 3
+          batch_size: 4
+
+        inputs:
+          - name: "input0"
+            scale_values: [255,255,255]
+            shape: [1, 3, 64, 64]
+            layout: "NCHW"
+            calibration:
+              max_images: 100
+        """
+        ).format(
+            data_dir=DATA_DIR,
+            calibration_data_dir_1=CALIBRATION_DATA_DIR_1,
+        )
         + append
     )
 
@@ -834,6 +840,30 @@ def test_modified_onnx(keys: list[str], values: list[str]):
             assert input_configs[inp].scale_values is None or [1, 1, 1]
 
 
+def test_modified_onnx_noop_returns_original_model():
+    model_path = DATA_DIR / "dummy_model.onnx"
+    modified_path = DATA_DIR / "dummy_model_noop_modified.onnx"
+    config = Config.get_config(
+        None,
+        {
+            "input_model": str(model_path),
+            "encoding": "NONE",
+        },
+    )
+    input_configs = {
+        inp.name: inp for inp in next(iter(config.stages.values())).inputs
+    }
+
+    result = onnx_attach_normalization_to_inputs(
+        model_path,
+        modified_path,
+        input_configs,
+    )
+
+    assert result == model_path
+    assert not modified_path.exists()
+
+
 @pytest.mark.parametrize(
     ("keys", "values", "nn_preprocess", "expected"),
     [