checks it is working with the latest onnxruntime

_unittests/ut_xrun_doc/test_check_ort_float16.py

@@ -10,6 +10,7 @@
     ExtTestCase,
     ignore_warnings,
     requires_cuda,
+    requires_onnxruntime,
 )
 
 
@@ -130,6 +131,7 @@ def common_scatter(self, opset, providers, dtype, reduction, expected_names):
 
     @requires_cuda()
     @ignore_warnings(DeprecationWarning)
+    @requires_onnxruntime("1.23")
     def test_scatterels_cuda(self):
         default_value = [
             "Cast",
@@ -143,6 +145,10 @@ def test_scatterels_cuda(self):
             (np.float16, "none"): default_value,
             (np.float32, "add"): default_value,
             (np.float16, "add"): default_value,
+            (np.float32, "min"): default_value,
+            (np.float16, "min"): default_value,
+            (np.float32, "max"): default_value,
+            (np.float16, "max"): default_value,
         }
         for opset, dtype, reduction in itertools.product(
             [16, 18], [np.float32, np.float16], ["none", "add", "min", "max"]
@@ -185,14 +191,14 @@ def test_scatternd_cuda(self):
                 )
 
     @ignore_warnings(DeprecationWarning)
+    @requires_onnxruntime("1.23")
     def test_scatterels_cpu(self):
         default_value = [
             "Cast",
             "ScatterElements",
             "Sub",
         ]
         default_value_16 = [
-            "Cast",
             "Cast",
             "ScatterElements",
             "Cast",
@@ -218,14 +224,14 @@ def test_scatterels_cpu(self):
                 )
 
     @ignore_warnings(DeprecationWarning)
+    @requires_onnxruntime("1.23")
     def test_scatternd_cpu(self):
         default_value = [
             "Cast",
             "ScatterND",
             "Sub",
         ]
         default_value_16 = [
-            "Cast",
             "Cast",
             "ScatterND",
             "Cast",

onnx_diagnostic/torch_export_patches/onnx_export_errors.py

@@ -254,6 +254,17 @@ def torch_export_patches(
     may appear ``AssertionError: Mutating module attribute _seen_tokens during export.``.
     It can be avoided by setting ``strict=False`` when call :func:`torch.export.export`.
     """
+    if verbose:
+        print(f"[torch_export_patches] patch_sympy={patch_sympy!r}")
+        print(f"                     . patch_torch={patch_torch!r}")
+        print(f"                     . patch_transformers={patch_transformers!r}")
+        print(f"                     . patch_diffusers={patch_diffusers!r}")
+        print(f"                     . catch_constraints={catch_constraints!r}")
+        print(f"                     . stop_if_static={stop_if_static!r}")
+        print(f"                     . patch={patch!r}")
+        print(f"                     . custom_patches={custom_patches!r}")
+        print(f"[torch_export_patches] dump_rewriting={dump_rewriting!r}")
+
     if rewrite:
         from .patch_module import torch_export_rewrite
 

onnx_diagnostic/torch_models/validate.py

@@ -112,6 +112,7 @@ def _make_folder_name(
     device: Optional[Union[str, torch.device]] = None,
     subfolder: Optional[str] = None,
     opset: Optional[int] = None,
+    drop_inputs: Optional[List[str]] = None,
 ) -> str:
     "Creates a filename unique based on the given options."
     els = [model_id.replace("/", "_")]
@@ -137,6 +138,9 @@ def _make_folder_name(
         els.append(sdev)
     if opset is not None:
         els.append(f"op{opset}")
+    if drop_inputs:
+        ii = "-".join(f"{s[0]}{s[-1]}" for s in drop_inputs)
+        els.append(f"I-{ii.upper()}")
     return "-".join(els)
 
 
@@ -394,12 +398,9 @@ def validate_model(
         same_as_pretrained=same_as_pretrained,
         use_pretrained=use_pretrained,
     )
+    default_patch = dict(patch_transformers=True, patch_diffusers=True, patch=True)
     if isinstance(patch, bool):
-        patch_kwargs = (
-            dict(patch_transformers=True, patch_diffusers=True, patch=True)
-            if patch
-            else dict(patch=False)
-        )
+        patch_kwargs = default_patch if patch else dict(patch=False)
     elif isinstance(patch, str):
         patch_kwargs = {"patch": True, **{p: True for p in patch.split(",")}}  # noqa: C420
     else:
@@ -408,6 +409,8 @@ def validate_model(
         if "patch" not in patch_kwargs:
             if any(patch_kwargs.values()):
                 patch_kwargs["patch"] = True
+        elif len(patch) == 1 and patch.get("patch", False):
+            patch_kwargs.update(default_patch)
 
     assert not rewrite or patch_kwargs.get("patch", False), (
         f"rewrite={rewrite}, patch={patch}, patch_kwargs={patch_kwargs} "
@@ -450,6 +453,7 @@ def validate_model(
             device=device,
             subfolder=subfolder,
             opset=opset,
+            drop_inputs=drop_inputs,
         )
         dump_folder = os.path.join(dump_folder, folder_name)
         if not os.path.exists(dump_folder):

requirements-dev.txt

@@ -7,7 +7,6 @@ huggingface_hub
 matplotlib
 onnx-array-api>=0.3.1
 onnx
-git+https://github.com/onnx/ir-py.git
 onnxscript
 openpyxl
 packaging

requirements.txt

@@ -1,6 +1,6 @@
 numpy
 onnx>=1.16.0
-onnxruntime>=1.21
+onnxruntime>=1.23
 optree
 torch>=2.8
 torch_geometric