example

sdpython · sdpython · Feb 6, 2024 · Feb 2, 2024 · Feb 2, 2024 · Feb 2, 2024
commit d1f276b67608e7d9ec413c01f8f0dcf621c37e65
diff --git a/_doc/examples/plot_onnx_diff.py b/_doc/examples/plot_onnx_diff.py
@@ -0,0 +1,68 @@
+"""
+
+.. _l-onnx-diff-example:
+
+Compares the conversions of the same model with different options
+=================================================================
+
+The script compares two onnx models obtained with the same trained
+scikit-learn models but converted with different options.
+
+A model
++++++++
+"""
+
+from sklearn.mixture import GaussianMixture
+from sklearn.datasets import load_iris
+from sklearn.model_selection import train_test_split
+from skl2onnx import to_onnx
+from onnx_array_api.reference import compare_onnx_execution
+from onnx_array_api.plotting.text_plot import onnx_simple_text_plot
+
+
+data = load_iris()
+X_train, X_test = train_test_split(data.data)
+model = GaussianMixture()
+model.fit(X_train)
+
+#################################
+# Conversion to onnx
+# ++++++++++++++++++
+
+onx = to_onnx(
+    model, X_train[:1], options={id(model): {"score_samples": True}}, target_opset=12
+)
+
+print(onnx_simple_text_plot(onx))
+
+##################################
+# Conversion to onnx without ReduceLogSumExp
+# ++++++++++++++++++++++++++++++++++++++++++
+
+onx2 = to_onnx(
+    model,
+    X_train[:1],
+    options={id(model): {"score_samples": True}},
+    black_op={"ReduceLogSumExp"},
+    target_opset=12,
+)
+
+print(onnx_simple_text_plot(onx2))
+
+
+#############################################
+# Differences
+# +++++++++++
+#
+# Function :func:`onnx_array_api.reference.compare_onnx_execution`
+# compares the intermediate results of two onnx models. Then it finds
+# the best alignmet between the two models using an edit distance.
+
+res1, res2, align, dc = compare_onnx_execution(onx, onx2, verbose=1)
+print("------------")
+text = dc.to_str(res1, res2, align)
+print(text)
+
+###############################
+# The display shows that ReduceSumSquare was replaced by Mul + ReduceSum,
+# and ReduceLogSumExp by ReduceMax + Sub + Exp + Log + Add.
diff --git a/_unittests/ut_xrun_doc/test_command_lines1.py b/_unittests/ut_xrun_doc/test_command_lines1.py
@@ -105,7 +105,7 @@ def test_command_compare(self):
 
             code = st.getvalue()
             self.assertIn("[compare_onnx_execution]", code)
-            self.assertIn("AAAA", code)
+            self.assertIn("ADFF", code)
 
 
 if __name__ == "__main__":

diff --git a/onnx_array_api/reference/evaluator_yield.py b/onnx_array_api/reference/evaluator_yield.py
@@ -62,7 +62,7 @@ def __str__(self):
             _align(str(self.dtype).replace("dtype(", "").replace(")", ""), 8),
             _align("x".join(map(str, self.shape)), 15),
             self.summary,
-            _align(self.op_type or "", 8),
+            _align(self.op_type or "", 10),
             self.name or "",
         ]
         return " ".join(els)
@@ -316,7 +316,7 @@ def to_str(
         s1: List[ResultExecution],
         s2: List[ResultExecution],
         alignment: List[Tuple[int, int]],
-        column_size: int = 50,
+        column_size: int = 60,
     ) -> str:
         """
         Prints out the alignment between two sequences into a string.
@@ -384,7 +384,7 @@ def generate_input(info: ValueInfoProto) -> np.ndarray:
         return (value.astype(np.float32) / p).astype(np.float32).reshape(new_shape)
     if elem_type == TensorProto.FLOAT16:
         return (value.astype(np.float16) / p).astype(np.float16).reshape(new_shape)
-    if elem_type == TensorProto.FLOAT64:
+    if elem_type == TensorProto.DOUBLE:
         return (value.astype(np.float64) / p).astype(np.float64).reshape(new_shape)
     raise RuntimeError(f"Unexpected element_type {elem_type} for info={info}")
 
@@ -414,6 +414,8 @@ def compare_onnx_execution(
     """
     Compares the execution of two onnx models.
     The function assumes both models takes the same inputs.
+    See :ref:`l-onnx-diff-example` to see a full example using
+    this function.
 
     :param model1: first model
     :param model2: second model

diff --git a/onnx_array_api/reference/ops/op_fused_matmul.py b/onnx_array_api/reference/ops/op_fused_matmul.py
@@ -9,7 +9,7 @@ def _run(
         self,
         A,
         B,
-        alpha: float = 0,
+        alpha: float = 1,
         transA: int = 0,
         transB: int = 0,
         transBatchA: int = 0,