Test onnx==1.14.0 (#988)

* Test onnx==1.14.0 Signed-off-by: xadupre <xadupre@microsoft.com> * fix yml syntax Signed-off-by: xadupre <xadupre@microsoft.com> * fix requirements Signed-off-by: xadupre <xadupre@microsoft.com> * fix broken unit test Signed-off-by: xadupre <xadupre@microsoft.com> * fix ir_version Signed-off-by: xadupre <xadupre@microsoft.com> * fix misspelling Signed-off-by: xadupre <xadupre@microsoft.com> * fix error Signed-off-by: xadupre <xadupre@microsoft.com> * update to rc3 Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> * change np.float to np.float32 Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> * Test onnx==1.14.0 Signed-off-by: xadupre <xadupre@microsoft.com> * fix yml syntax Signed-off-by: xadupre <xadupre@microsoft.com> * fix requirements Signed-off-by: xadupre <xadupre@microsoft.com> * fix broken unit test Signed-off-by: xadupre <xadupre@microsoft.com> * fix ir_version Signed-off-by: xadupre <xadupre@microsoft.com> * fix misspelling Signed-off-by: xadupre <xadupre@microsoft.com> * fix error Signed-off-by: xadupre <xadupre@microsoft.com> * update to rc3 Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> Signed-off-by: xadupre <xadupre@microsoft.com> * change np.float to np.float32 Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> Signed-off-by: xadupre <xadupre@microsoft.com> * use official release Signed-off-by: xadupre <xadupre@microsoft.com> * disable documentation on one CI Signed-off-by: xadupre <xadupre@microsoft.com> * disable test for sklearn==1.0.2 Signed-off-by: xadupre <xadupre@microsoft.com> * lint Signed-off-by: xadupre <xadupre@microsoft.com> * fix issue for an old scikit-learn on windows Signed-off-by: xadupre <xadupre@microsoft.com> * update CI Signed-off-by: xadupre <xadupre@microsoft.com> * pin numpy version for old build on windows Signed-off-by: xadupre <xadupre@microsoft.com> * resolve comment Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> * update Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> --------- Signed-off-by: xadupre <xadupre@microsoft.com> Signed-off-by: xiaowuhu <xiaowuhu@microsoft.com> Co-authored-by: xiaowuhu <xiaowuhu@microsoft.com>
onnx · May 8, 2023 · 2669f0d · 2669f0d
1 parent 7e39c47
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diff --git a/.azure-pipelines/linux-conda-CI.yml b/.azure-pipelines/linux-conda-CI.yml
@@ -14,11 +14,24 @@ jobs:
   strategy:
     matrix:
 
-      Py310-Onnx130-Rt140-Skl121:
+      Py310-Onnx140-Rt140-Skl122:
         do.bench: '0'
-        python.version: '3.10'
+        python.version: '3.10'  # onnxruntime cannot support python 3.11 yet
         numpy.version: '>=1.21.1'
         scipy.version: '>=1.7.0'
+        onnx.version: 'onnx==1.14.0' # '-i https://test.pypi.org/simple/ onnx==1.14.0rc3'
+        onnx.target_opset: ''
+        onnxrt.version: 'onnxruntime==1.14.0' # -i https://test.pypi.org/simple/ ort-nightly==1.11.0.dev20220311003
+        sklearn.version: '>=1.2.2'
+        lgbm.version: ''
+        onnxcc.version: '>=1.8.1'  # git
+        run.example: '1'
+
+      Py310-Onnx130-Rt140-Skl122:
+        do.bench: '0'
+        python.version: '3.10'
+        numpy.version: '>=1.21.2'
+        scipy.version: '>=1.7.0'
         onnx.version: 'onnx==1.13.0' #'-i https://test.pypi.org/simple/ onnx==1.13.0rc1'
         onnx.target_opset: ''
         onnxrt.version: 'onnxruntime==1.14.0' # -i https://test.pypi.org/simple/ ort-nightly==1.11.0.dev20220311003
@@ -51,7 +64,7 @@ jobs:
         sklearn.version: '==1.2.0'
         lgbm.version: ''
         onnxcc.version: '>=1.8.1'  # git
-        run.example: '1'
+        run.example: '0'
       Py310-Onnx120-Rt1201-Skl11:
         do.bench: '0'
         python.version: '3.10'

diff --git a/.azure-pipelines/win32-conda-CI.yml b/.azure-pipelines/win32-conda-CI.yml
@@ -13,6 +13,15 @@ jobs:
     vmImage: 'windows-latest'
   strategy:
     matrix:
+      Py310-Onnx140-Rt140-Skl122:
+        python.version: '3.10'  # onnxruntime cannot support python 3.11 yet
+        onnx.version:  'onnx==1.14.0' # '-i https://test.pypi.org/simple/ onnx==1.14.0rc3'
+        onnx.target_opset: ''
+        numpy.version: 'numpy>=1.22.3'
+        scipy.version: 'scipy'
+        onnxrt.version: 'onnxruntime==1.14.0' # -i https://test.pypi.org/simple/ ort-nightly==1.11.0.dev20220311003
+        onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
+        sklearn.version: '>=1.2.2'
       Py310-Onnx130-Rt140-Skl121:
         python.version: '3.10'
         onnx.version:  'onnx==1.13.0' #'-i https://test.pypi.org/simple/ onnx==1.12.0rc4'
@@ -21,7 +30,7 @@ jobs:
         scipy.version: 'scipy'
         onnxrt.version: 'onnxruntime==1.14.0' # -i https://test.pypi.org/simple/ ort-nightly==1.11.0.dev20220311003
         onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
-        sklearn.version: '>=1.2.1'
+        sklearn.version: '>=1.2.2'
       Py310-Onnx130-Rt131-Skl120:
         python.version: '3.10'
         onnx.version:  'onnx==1.13.0' #'-i https://test.pypi.org/simple/ onnx==1.12.0rc4'
@@ -71,7 +80,7 @@ jobs:
         python.version: '3.9'
         onnx.version:  'onnx==1.11.0' # '-i https://test.pypi.org/simple/ onnx==1.11.0rc2'
         onnx.target_opset: ''
-        numpy.version: 'numpy>=1.22.3'
+        numpy.version: 'numpy==1.23.5'
         scipy.version: 'scipy'
         onnxrt.version: 'onnxruntime==1.11.1' # -i https://test.pypi.org/simple/ ort-nightly==1.11.0.dev20220311003
         onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
@@ -80,7 +89,7 @@ jobs:
         python.version: '3.9'
         onnx.version:  'onnx==1.11.0' # '-i https://test.pypi.org/simple/ onnx==1.11.0rc2'
         onnx.target_opset: ''
-        numpy.version: 'numpy>=1.18.1'
+        numpy.version: 'numpy==1.23.5'
         scipy.version: 'scipy'
         onnxrt.version: 'onnxruntime==1.10.0'  # -i https://test.pypi.org/simple/ ort-nightly'
         onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
@@ -89,20 +98,11 @@ jobs:
         python.version: '3.9'
         onnx.version: 'onnx==1.10.2'  # -i https://test.pypi.org/simple/ onnx'
         onnx.target_opset: ''
-        numpy.version: 'numpy>=1.18.1'
+        numpy.version: 'numpy==1.23.5'
         scipy.version: 'scipy'
         onnxrt.version: 'onnxruntime==1.10.0'  # -i https://test.pypi.org/simple/ ort-nightly'
         onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
         sklearn.version: '==1.0.2'
-      Py39-Onnx1101-Rt190-Skl10:
-        python.version: '3.9'
-        onnx.version: 'onnx==1.10.1'  # -i https://test.pypi.org/simple/ onnx'
-        onnx.target_opset: ''
-        numpy.version: 'numpy>=1.18.1'
-        scipy.version: 'scipy'
-        onnxrt.version: 'onnxruntime==1.9.0'  # -i https://test.pypi.org/simple/ ort-nightly'
-        onnxcc.version: 'onnxconverter-common>=1.8.1'  # git+https://github.com/microsoft/onnxconverter-common.git
-        sklearn.version: '==1.0.2'
 
     maxParallel: 3
 

diff --git a/.gitignore b/.gitignore
@@ -30,6 +30,7 @@ coverage.xml
 .coverage
 __dump_data/
 junit/
+tests_dump/
 skl2onnx/algebra/_cache/*.rst
 docs/auto_examples
 docs/examples/graph*.*

diff --git a/docs/requirements.txt b/docs/requirements.txt
@@ -1,7 +1,6 @@
 autopep8
 catboost
 category_encoders
-codecov
 coverage
 flake8
 furo

diff --git a/requirements-dev.txt b/requirements-dev.txt
@@ -1,5 +1,4 @@
 # tests
-codecov
 flatbuffers
 pandas
 py-cpuinfo

diff --git a/skl2onnx/common/_topology.py b/skl2onnx/common/_topology.py
@@ -40,7 +40,8 @@ def _default_OPSET_TO_IR_VERSION():
     return {
         1: 3, 2: 3, 3: 3, 4: 3, 5: 3, 6: 3,
         7: 3, 8: 4, 9: 4, 10: 5, 11: 6, 12: 7,
-        13: 7, 14: 7, 15: 8, 16: 8, 17: 8, 18: 8
+        13: 7, 14: 7, 15: 8, 16: 8, 17: 8, 18: 8,
+        19: 9
     }
 
 

diff --git a/skl2onnx/operator_converters/label_binariser.py b/skl2onnx/operator_converters/label_binariser.py
@@ -30,9 +30,9 @@ def convert_sklearn_label_binariser(scope: Scope, operator: Operator,
                            name=scope.get_unique_operator_name('identity'))
     else:
         zeros_tensor = np.full((1, len(classes)),
-                               binariser_op.neg_label, dtype=np.float)
+                               binariser_op.neg_label, dtype=np.float32)
         unit_tensor = np.full((1, len(classes)),
-                              binariser_op.pos_label, dtype=np.float)
+                              binariser_op.pos_label, dtype=np.float32)
 
         classes_tensor_name = scope.get_unique_variable_name('classes_tensor')
         equal_condition_tensor_name = scope.get_unique_variable_name(

diff --git a/skl2onnx/operator_converters/one_vs_rest_classifier.py b/skl2onnx/operator_converters/one_vs_rest_classifier.py
@@ -199,7 +199,8 @@ def convert_constant_predictor_classifier(scope: Scope, operator: Operator,
     proba_flat = OnnxTile(cst, first, op_version=op_version)
     proba_reshape = OnnxReshape(
         proba_flat, np.array([-1, 2], dtype=np.int64),
-        output_names=[operator.outputs[1].full_name])
+        output_names=[operator.outputs[1].full_name],
+        op_version=op_version)
 
     labels.add_to(scope, container)
     proba_reshape.add_to(scope, container)

diff --git a/tests/test_optimisation.py b/tests/test_optimisation.py
@@ -8,7 +8,9 @@
 from onnx import TensorProto as tp
 from skl2onnx.common.onnx_optimisation_identity import (
     onnx_remove_node_identity)
-from test_utils import TARGET_OPSET, InferenceSessionEx as InferenceSession
+from test_utils import (
+        TARGET_OPSET, TARGET_IR,
+        InferenceSessionEx as InferenceSession)
 
 
 class TestOptimisation(unittest.TestCase):
@@ -58,7 +60,8 @@ def test_coptimisation_identity_removal(self):
 
         # Create the model and check
         m = helper.make_model(
-            g, opset_imports=[helper.make_opsetid('', TARGET_OPSET)])
+            g, opset_imports=[helper.make_opsetid('', TARGET_OPSET)],
+            ir_version=TARGET_IR)
         checker.check_model(m)
 
         sess = InferenceSession(

diff --git a/tests/test_sklearn_adaboost_converter.py b/tests/test_sklearn_adaboost_converter.py
@@ -5,6 +5,7 @@
 import packaging.version as pv
 from onnx.defs import onnx_opset_version
 from onnxruntime import __version__ as ort_version
+from sklearn import __version__ as sklearn_version
 from sklearn.ensemble import AdaBoostClassifier, AdaBoostRegressor
 from sklearn.linear_model import LinearRegression, LogisticRegression
 from sklearn.tree import DecisionTreeClassifier
@@ -23,15 +24,22 @@
 
 
 ort_version = '.'.join(ort_version.split('.')[:2])
+skl_version = '.'.join(sklearn_version.split('.')[:2])
 
 
 class TestSklearnAdaBoostModels(unittest.TestCase):
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_classifier_samme_r(self):
-        model, X_test = fit_classification_model(AdaBoostClassifier(
-            n_estimators=10, algorithm="SAMME.R", random_state=42,
-            base_estimator=DecisionTreeClassifier(
-                max_depth=2, random_state=42)), 3)
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=10, algorithm="SAMME.R", random_state=42,
+                base_estimator=DecisionTreeClassifier(
+                    max_depth=2, random_state=42)), 3)
+        else:
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=10, algorithm="SAMME.R", random_state=42,
+                estimator=DecisionTreeClassifier(
+                    max_depth=2, random_state=42)), 3)
         model_onnx = convert_sklearn(
             model,
             "AdaBoost classification",
@@ -47,10 +55,16 @@ def test_ada_boost_classifier_samme_r(self):
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_classifier_samme_r_decision_function(self):
-        model, X_test = fit_classification_model(AdaBoostClassifier(
-            n_estimators=10, algorithm="SAMME.R", random_state=42,
-            base_estimator=DecisionTreeClassifier(
-                max_depth=2, random_state=42)), 4)
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=10, algorithm="SAMME.R", random_state=42,
+                base_estimator=DecisionTreeClassifier(
+                    max_depth=2, random_state=42)), 4)
+        else:
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=10, algorithm="SAMME.R", random_state=42,
+                estimator=DecisionTreeClassifier(
+                    max_depth=2, random_state=42)), 4)
         options = {id(model): {'raw_scores': True}}
         model_onnx = convert_sklearn(
             model,
@@ -69,10 +83,16 @@ def test_ada_boost_classifier_samme_r_decision_function(self):
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_classifier_samme_r_logreg(self):
-        model, X_test = fit_classification_model(AdaBoostClassifier(
-            n_estimators=5, algorithm="SAMME.R",
-            base_estimator=LogisticRegression(
-                solver='liblinear')), 4)
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME.R",
+                base_estimator=LogisticRegression(
+                    solver='liblinear')), 4)
+        else:
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME.R",
+                estimator=LogisticRegression(
+                    solver='liblinear')), 4)
         model_onnx = convert_sklearn(
             model,
             "AdaBoost classification",
@@ -88,10 +108,16 @@ def test_ada_boost_classifier_samme_r_logreg(self):
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_classifier_samme(self):
-        model, X_test = fit_classification_model(AdaBoostClassifier(
-            n_estimators=5, algorithm="SAMME", random_state=42,
-            base_estimator=DecisionTreeClassifier(
-                max_depth=6, random_state=42)), 2, n_features=7)
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME", random_state=42,
+                base_estimator=DecisionTreeClassifier(
+                    max_depth=6, random_state=42)), 2, n_features=7)
+        else:
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME", random_state=42,
+                estimator=DecisionTreeClassifier(
+                    max_depth=6, random_state=42)), 2, n_features=7)
         model_onnx = convert_sklearn(
             model,
             "AdaBoostClSamme",
@@ -107,10 +133,16 @@ def test_ada_boost_classifier_samme(self):
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_classifier_samme_decision_function(self):
-        model, X_test = fit_classification_model(AdaBoostClassifier(
-            n_estimators=5, algorithm="SAMME", random_state=42,
-            base_estimator=DecisionTreeClassifier(
-                max_depth=6, random_state=42)), 2)
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME", random_state=42,
+                base_estimator=DecisionTreeClassifier(
+                    max_depth=6, random_state=42)), 2)
+        else:
+            model, X_test = fit_classification_model(AdaBoostClassifier(
+                n_estimators=5, algorithm="SAMME", random_state=42,
+                estimator=DecisionTreeClassifier(
+                    max_depth=6, random_state=42)), 2)
         options = {id(model): {'raw_scores': True}}
         model_onnx = convert_sklearn(
             model,
@@ -174,25 +206,28 @@ def test_ada_boost_regressor(self):
             target_opset=10)
         self.assertIsNotNone(model_onnx)
         dump_data_and_model(
-            X,
-            model,
-            model_onnx,
+            X, model, model_onnx,
+            backend="onnxruntime",
             basename="SklearnAdaBoostRegressor-Dec4")
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
     def test_ada_boost_regressor_lreg(self):
-        model, X = fit_regression_model(
-            AdaBoostRegressor(n_estimators=5,
-                              base_estimator=LinearRegression()))
+        if pv.Version(skl_version) < pv.Version("1.2"):
+            model, X = fit_regression_model(
+                AdaBoostRegressor(n_estimators=5,
+                                  base_estimator=LinearRegression()))
+        else:
+            model, X = fit_regression_model(
+                AdaBoostRegressor(n_estimators=5,
+                                  estimator=LinearRegression()))
         model_onnx = convert_sklearn(
             model, "AdaBoost regression",
             [("input", FloatTensorType([None, X.shape[1]]))],
             target_opset=10)
         self.assertIsNotNone(model_onnx)
         dump_data_and_model(
-            X,
-            model,
-            model_onnx,
+            X, model, model_onnx,
+            backend="onnxruntime",
             basename="SklearnAdaBoostRegressorLReg-Dec4")
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
@@ -205,9 +240,8 @@ def test_ada_boost_regressor_int(self):
             target_opset=10)
         self.assertIsNotNone(model_onnx)
         dump_data_and_model(
-            X,
-            model,
-            model_onnx,
+            X, model, model_onnx,
+            backend="onnxruntime",
             basename="SklearnAdaBoostRegressorInt-Dec4")
 
     @unittest.skipIf(TARGET_OPSET < 11, reason="not available")
@@ -220,9 +254,8 @@ def test_ada_boost_regressor_lr10(self):
             target_opset=10)
         self.assertIsNotNone(model_onnx)
         dump_data_and_model(
-            X,
-            model,
-            model_onnx,
+            X, model, model_onnx,
+            backend="onnxruntime",
             basename="SklearnAdaBoostRegressorLR-Dec4")
 
     @unittest.skipIf((pv.Version(ort_version) <
@@ -262,9 +295,8 @@ def test_ada_boost_regressor_bool(self):
         )
         self.assertIsNotNone(model_onnx)
         dump_data_and_model(
-            X,
-            model,
-            model_onnx,
+            X, model, model_onnx,
+            backend="onnxruntime",
             basename="SklearnAdaBoostRegressorBool")
 
 

diff --git a/tests/test_sklearn_feature_hasher.py b/tests/test_sklearn_feature_hasher.py
@@ -18,7 +18,9 @@
 from skl2onnx.common.data_types import (
     StringTensorType, Int64TensorType, FloatTensorType,
     DoubleTensorType)
-from test_utils import TARGET_OPSET, InferenceSessionEx as InferenceSession
+from test_utils import (
+    TARGET_OPSET, TARGET_IR,
+    InferenceSessionEx as InferenceSession)
 
 
 class TestSklearnFeatureHasher(unittest.TestCase):
@@ -33,7 +35,8 @@ def test_ort_murmurhash3_int(self):
         graph = make_graph([node], 'hash', [X], [Y])
         onnx_model = make_model(graph, opset_imports=[
             make_opsetid('', TARGET_OPSET),
-            make_opsetid('com.microsoft', 1)])
+            make_opsetid('com.microsoft', 1)],
+            ir_version=TARGET_IR)
         check_model(onnx_model)
         sess = InferenceSession(
             onnx_model.SerializeToString(),
@@ -53,7 +56,8 @@ def test_ort_murmurhash3_string(self):
         graph = make_graph([node], 'hash', [X], [Y])
         onnx_model = make_model(graph, opset_imports=[
             make_opsetid('', TARGET_OPSET),
-            make_opsetid('com.microsoft', 1)])
+            make_opsetid('com.microsoft', 1)],
+            ir_version=TARGET_IR)
         check_model(onnx_model)
         sess = InferenceSession(
             onnx_model.SerializeToString(),