first version of sbs

Author: xadupre

_doc/api/index.rst

@@ -11,6 +11,7 @@ API of onnx_diagnostic
     reference/index
     torch_export_patches/index
     torch_models/index
+    torch_onnx/index
 
 .. toctree::
     :maxdepth: 1

_doc/api/torch_onnx/index.rst

@@ -0,0 +1,12 @@
+onnx_diagnostic.torch_onnx
+==========================
+
+.. toctree::
+    :maxdepth: 1
+    :caption: submodules
+
+    sbs
+
+.. automodule:: onnx_diagnostic.torch_onnx
+    :members:
+    :no-undoc-members:

_doc/api/torch_onnx/sbs.rst

@@ -0,0 +1,8 @@
+
+onnx_diagnostic.torch_onnx.sbs
+==============================
+
+.. automodule:: onnx_diagnostic.torch_onnx.sbs
+    :members:
+    :no-undoc-members:
+    

_unittests/ut_torch_onnx/test_sbs.py

@@ -0,0 +1,82 @@
+import unittest
+from onnx_diagnostic.ext_test_case import ExtTestCase, hide_stdout
+from onnx_diagnostic.reference import ExtendedReferenceEvaluator
+from onnx_diagnostic.torch_onnx.sbs import run_aligned
+
+try:
+    from experimental_experiment.torch_interpreter import to_onnx
+except ImportError:
+    to_onnx = None
+
+
+class TestSideBySide(ExtTestCase):
+
+    @hide_stdout()
+    @unittest.skipIf(to_onnx is None, "to_onnx not installed")
+    def test_ep_onnx_sync_exp(self):
+        import torch
+
+        class Model(torch.nn.Module):
+            def forward(self, x):
+                ry = x.abs()
+                rz = ry.exp()
+                rw = rz + 1
+                ru = rw.log() + rw
+                return ru
+
+        x = torch.randn((5, 4))
+        Model()(x)
+        ep = torch.export.export(
+            Model(), (x,), dynamic_shapes=({0: torch.export.Dim("batch")},)
+        )
+        onx = to_onnx(ep)
+        results = list(
+            run_aligned(
+                ep,
+                onx,
+                (x,),
+                check_conversion_cls=dict(
+                    cls=ExtendedReferenceEvaluator, atol=1e-5, rtol=1e-5
+                ),
+                verbose=1,
+            ),
+        )
+        self.assertEqual(len(results), 4)
+
+    @hide_stdout()
+    @unittest.skipIf(to_onnx is None, "to_onnx not installed")
+    def test_ep_onnx_sync(self):
+        import torch
+
+        class Model(torch.nn.Module):
+            def forward(self, x):
+                ry = x.abs()
+                rz = ry.exp()
+                rw = rz + 1
+                ru = rw.log() + rw
+                return ru
+
+        x = torch.randn((5, 4))
+        Model()(x)
+        ep = torch.export.export(
+            Model(), (x,), dynamic_shapes=({0: torch.export.Dim("batch")},)
+        )
+        onx = torch.onnx.export(
+            Model(), (x,), dynamic_shapes=({0: torch.export.Dim("batch")},), dynamo=True
+        ).model_proto
+        results = list(
+            run_aligned(
+                ep,
+                onx,
+                (x,),
+                check_conversion_cls=dict(
+                    cls=ExtendedReferenceEvaluator, atol=1e-5, rtol=1e-5
+                ),
+                verbose=1,
+            ),
+        )
+        self.assertEqual(len(results), 4)
+
+
+if __name__ == "__main__":
+    unittest.main(verbosity=2)