improves documentation

.github/workflows/documentation.yml

@@ -111,9 +111,9 @@ jobs:
             grep ERROR doc.txt | grep -v 'l-plot-tiny-llm-export'
             exit 1
           fi
-          if [[ $(grep WARNING doc.txt | grep -v 'l-plot-tiny-llm-export') ]]; then
+          if [[ $(grep WARNING doc.txt | grep -v 'l-plot-tiny-llm-export' | grep -v 'Inline emphasis start-string' | grep -v 'Definition list ends without a blank line' | grep -v 'Unexpected section title or transition' | grep -v 'Inline strong start-string') ]]; then
             echo "Documentation produces warnings."
-            grep WARNING doc.txt | grep -v 'l-plot-tiny-llm-export'
+            grep WARNING doc.txt | grep -v 'l-plot-tiny-llm-export' | grep -v 'Inline emphasis start-string' | grep -v 'Definition list ends without a blank line' | grep -v 'Unexpected section title or transition' | grep -v 'Inline strong start-string'
             exit 1
           fi
 

_doc/status/exported_program_dynamic.rst

@@ -2,9 +2,8 @@
 Exported Programs with Dynamic Shapes
 =====================================
 
-The following script shows the exported program for many short cases
-and various l-plot-export-with-dynamic-shape to retrieve an ONNX model equivalent
-to the original model.
+The following script shows the exported program for many short cases exported
+with different options. This steps happens before converting into ONNX.
 
 .. runpython::
     :showcode:
@@ -55,6 +54,7 @@ to the original model.
             "export-strict",
             "export-nostrict",
             "export-nostrict-decall",
+            "export-tracing",
         ):
             expname = exporter.replace("export-", "")
             print()

_doc/status/exporter_dynamic.rst

@@ -0,0 +1,101 @@
+=================================
+Exported ONNX with Dynamic Shapes
+=================================
+
+The following script shows the exported program for many short cases
+and various l-plot-export-with-dynamic-shape to retrieve an ONNX model equivalent
+to the original model.
+
+.. runpython::
+    :showcode:
+    :rst:
+    :toggle: code
+    :warningout: UserWarning
+
+    import inspect
+    import textwrap
+    import pandas
+    from onnx_diagnostic.helpers import string_type
+    from onnx_diagnostic.helpers.onnx_helper import pretty_onnx
+    from onnx_diagnostic.torch_export_patches.eval import discover, run_exporter
+    from onnx_diagnostic.ext_test_case import unit_test_going
+
+    cases = discover()
+    print()
+    print(":ref:`Summary <ledx-summary-exported-program>`")
+    print()
+    sorted_cases = sorted(cases.items())
+    if unit_test_going():
+        sorted_cases = sorted_cases[:3]
+    for name, cls_model in sorted_cases:
+        print(f"* :ref:`{name} <ledx-model-case-export-{name}>`")
+    print()
+    print()
+
+    obs = []
+    for name, cls_model in sorted(cases.items()):
+        print()
+        print(f".. _ledx-model-case-export-{name}:")
+        print()
+        print(name)
+        print("=" * len(name))
+        print()
+        print("forward")
+        print("+++++++")
+        print()
+        print(".. code-block:: python")
+        print()
+        src = inspect.getsource(cls_model.forward)
+        if src:
+            print(textwrap.indent(textwrap.dedent(src), "    "))
+        else:
+            print("    # code is missing")
+        print()
+        print()
+        for exporter in ("custom", "dynamo-ir"):
+            expname = exporter.replace("export-", "")
+            print()
+            print(expname)
+            print("+" * len(expname))
+            print()
+            res = run_exporter(exporter, cls_model, True, quiet=True)
+            case_ref = f":ref:`{name} <ledx-model-case-export-{name}>`"
+            expo = exporter.split("-", maxsplit=1)[-1]
+            if "inputs" in res:
+                print(f"* **inputs:** ``{string_type(res['inputs'], with_shape=True)}``")
+            if "dynamic_shapes" in res:
+                print(f"* **shapes:** ``{string_type(res['dynamic_shapes'])}``")
+            print()
+            print()
+            if "onx" in res:
+                print(".. code-block:: text")
+                print()
+                print(textwrap.indent(pretty_onnx(res["onx"]), "    "))
+                print()
+                print()
+                if "error" not in res:
+                    obs.append(dict(case=case_ref, error="", exporter=expo))
+            if "error" in res:
+                print("**FAILED**")
+                print()
+                print(".. code-block:: text")
+                print()
+                err = str(res["error"])
+                if err:
+                    print(textwrap.indent(err, "    "))
+                else:
+                    print("    # no error found for the failure")
+                print()
+                print()
+                obs.append(dict(case=case_ref, error="FAIL", exporter=expo))
+
+    print()
+    print(".. _ledx-summary-exported-program:")
+    print()
+    print("Summary")
+    print("+++++++")
+    print()
+    df = pandas.DataFrame(obs)
+    piv = df.pivot(index="case", columns="exporter", values="error")
+    print(piv.to_markdown(tablefmt="rst"))
+    print()

_doc/status/index.rst

@@ -9,6 +9,7 @@ what works and what does not with :func:`torch.export.export`.
     :maxdepth: 1
 
     exported_program_dynamic
+    exporter_dynamic
     patches_coverage
 
 Some PRs in :epkg:`transformers` to keep in mind when it comes to export

_unittests/ut_torch_export_patches/test_eval.py

@@ -35,17 +35,57 @@ def test_eval(self):
         self.assertIsInstance(ev, list)
         self.assertIsInstance(ev[0], dict)
 
-    def test_run_exporter(self):
+    def test_run_exporter_custom(self):
         evaluation(
             cases="SignatureListFixedLength",
-            exporters="custom-strict",
+            exporters="custom",
+            quiet=False,
+            dynamic=False,
+        )
+
+    def test_run_exporter_dynamo(self):
+        evaluation(
+            cases="SignatureListFixedLength",
+            exporters="dynamo",
+            quiet=False,
+            dynamic=False,
+        )
+
+    def test_run_exporter_dynamo_ir(self):
+        evaluation(
+            cases="SignatureListFixedLength",
+            exporters="dynamo-ir",
+            quiet=False,
+            dynamic=False,
+        )
+
+    def test_run_exporter_nostrict(self):
+        evaluation(
+            cases="SignatureListFixedLength",
+            exporters="export-nostrict",
+            quiet=False,
+            dynamic=False,
+        )
+
+    def test_run_exporter_tracing(self):
+        evaluation(
+            cases="SignatureListFixedLength",
+            exporters="export-tracing",
             quiet=False,
             dynamic=False,
         )
 
     def test_run_exporter_regex(self):
         evaluation(cases=".*Aten.*", exporters="custom-strict", quiet=False, dynamic=False)
 
+    def test_run_exporter_custom_nested_cond(self):
+        evaluation(
+            cases="ControlFlowNestCond",
+            exporters="custom",
+            quiet=False,
+            dynamic=False,
+        )
+
 
 if __name__ == "__main__":
     unittest.main(verbosity=2)

onnx_diagnostic/torch_export_patches/README.md

@@ -0,0 +1,11 @@
+# Patches to export HuggingFace models
+
+See [Patches Explained](https://sdpython.github.io/doc/onnx-diagnostic/dev/patches.html).
+
+```python
+from onnx_diagnostic.torch_export_patches import torch_export_patches
+
+with torch_export_patches(patch_transformers=True) as f:
+    ep = torch.export.export(model, args, kwargs=kwargs, dynamic_shapes=dynamic_shapes)
+    # ...
+```

onnx_diagnostic/torch_export_patches/eval/__init__.py

@@ -337,7 +337,7 @@ def _make_exporter_onnx(
         from experimental_experiment.torch_interpreter import to_onnx, ExportOptions
 
         opts = {}
-        opts["strict"] = "-nostrict" not in exporter
+        opts["strict"] = "-strict" in exporter
         opts["fallback"] = "-fallback" in exporter
         opts["tracing"] = "-tracing" in exporter
         opts["jit"] = "-jit" in exporter
@@ -520,6 +520,8 @@ def run_exporter(
             return res
 
         onx, builder = res
+        base["onx"] = onx
+        base["builder"] = builder
         if verbose >= 9:
             print("[run_exporter] onnx model")
             print(