update CI with the latest version of onnx, onnxruntime (#706)

* update CI Signed-off-by: xadupre <xadupre@microsoft.com> * lint Signed-off-by: xadupre <xadupre@microsoft.com> * fix architecture Signed-off-by: xadupre <xadupre@microsoft.com> * remove architecture Signed-off-by: xadupre <xadupre@microsoft.com> * move one line * fix xgboost Signed-off-by: xadupre <xadupre@microsoft.com> * catch unable to import Signed-off-by: xadupre <xadupre@microsoft.com> * adjust import Signed-off-by: xadupre <xadupre@microsoft.com> * import Signed-off-by: xadupre <xadupre@microsoft.com> * none or Signed-off-by: xadupre <xadupre@microsoft.com> * another fix Signed-off-by: xadupre <xadupre@microsoft.com> * xgb Signed-off-by: xadupre <xadupre@microsoft.com> * fix comparison Signed-off-by: xadupre <xadupre@microsoft.com> * fix ut Signed-off-by: xadupre <xadupre@microsoft.com> * fix unittest Signed-off-by: xadupre <xadupre@microsoft.com> * atol Signed-off-by: xadupre <xadupre@microsoft.com> --------- Signed-off-by: xadupre <xadupre@microsoft.com>
onnx · Dec 23, 2024 · 4133713 · 4133713
1 parent 3ae696a
commit 4133713
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diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
@@ -9,6 +9,15 @@ jobs:
         os: [ubuntu-latest, macos-latest, windows-latest]
         python_version: ['3.12', '3.11', '3.10', '3.9']
         include:
+          - python_version: '3.12'
+            documentation: 1
+            numpy_version: '>=1.21.1'
+            scipy_version: '>=1.7.0'
+            onnx_version: 'onnx==1.17.0'
+            onnxrt_version: 'onnxruntime==1.20.1'
+            sklearn_version: '==1.6.0'
+            lgbm_version: ">=4"
+            xgboost_version: ">=2"
           - python_version: '3.12'
             documentation: 0
             numpy_version: '>=1.21.1'
@@ -19,7 +28,7 @@ jobs:
             lgbm_version: ">=4"
             xgboost_version: ">=2"
           - python_version: '3.11'
-            documentation: 1
+            documentation: 0
             numpy_version: '>=1.21.1'
             scipy_version: '>=1.7.0'
             onnx_version: 'onnx<1.16.0'
@@ -82,20 +91,19 @@ jobs:
 
       - name: versions
         run: |
-          python -c "from numpy import __version__;print('numpy', __version__)"
           python -c "from pandas import __version__;print('pandas', __version__)"
           python -c "from scipy import __version__;print('scipy', __version__)"
           python -c "from sklearn import __version__;print('sklearn', __version__)"
           python -c "from onnxruntime import __version__;print('onnxruntime', __version__)"
           python -c "from onnx import __version__;print('onnx', __version__)"
-          python -c "from xgboost import __version__;print('xgboost', __version__)"
           python -c "from catboost import __version__;print('catboost', __version__)"
           python -c "import onnx.defs;print('onnx_opset_version', onnx.defs.onnx_opset_version())"
   
       - name: versions lightgbm
         if: matrix.os != 'macos-latest'
         run: |
           python -c "from lightgbm import __version__;print('lightgbm', __version__)"
+          python -c "from xgboost import __version__;print('xgboost', __version__)"
   
       - name: Run tests baseline
         run: pytest --maxfail=10 --durations=10 tests/baseline

diff --git a/onnxmltools/convert/coreml/shape_calculators/OneHotEncoder.py b/onnxmltools/convert/coreml/shape_calculators/OneHotEncoder.py
@@ -26,7 +26,7 @@ def calculate_one_hot_encoder_output_shapes(operator):
         operator.outputs[0].type = FloatTensorType(
             [N, len(int_categories)], doc_string=operator.outputs[0].type.doc_string
         )
-    elif len(str_categories) > 0 and type(operator.inputs[0].type) == StringTensorType:
+    elif len(str_categories) > 0 and type(operator.inputs[0].type) is StringTensorType:
         operator.outputs[0].type = FloatTensorType(
             [N, len(str_categories)], doc_string=operator.outputs[0].type.doc_string
         )

diff --git a/onnxmltools/utils/tests_helper.py b/onnxmltools/utils/tests_helper.py
@@ -1,5 +1,6 @@
 # SPDX-License-Identifier: Apache-2.0
 
+import unittest
 import pickle
 import os
 import numpy
@@ -87,16 +88,22 @@ def dump_data_and_model(
     if not os.path.exists(folder):
         os.makedirs(folder)
 
-    if hasattr(model, "predict"):
+    if "LGBM" in model.__class__.__name__:
         try:
             import lightgbm
         except ImportError:
-            lightgbm = None
+            raise unittest.SkipTest("lightgbm cannot be imported.")
+    else:
+        lightgbm = None
+    if "XGB" in model.__class__.__name__ or "Booster" in model.__class__.__name__:
         try:
             import xgboost
         except ImportError:
-            xgboost = None
+            raise unittest.SkipTest("xgboost cannot be imported.")
+    else:
+        xgboost = None
 
+    if hasattr(model, "predict"):
         if lightgbm is not None and isinstance(model, lightgbm.Booster):
             # LightGBM Booster
             model_dict = model.dump_model()

diff --git a/onnxmltools/utils/utils_backend_onnxruntime.py b/onnxmltools/utils/utils_backend_onnxruntime.py
@@ -297,6 +297,30 @@ def _compare_expected(
                     (len(expected), len(output.ravel()) // len(expected))
                 )
             if len(expected) != len(output):
+                if (
+                    len(output) == 2
+                    and len(expected) == 1
+                    and output[0].dtype in (numpy.int64, numpy.int32)
+                ):
+                    # a classifier
+                    if len(expected[0].shape) == 1:
+                        expected = [
+                            numpy.hstack(
+                                [
+                                    1 - expected[0].reshape((-1, 1)),
+                                    expected[0].reshape((-1, 1)),
+                                ]
+                            )
+                        ]
+                    return _compare_expected(
+                        expected,
+                        output[1:],
+                        sess,
+                        onnx,
+                        decimal=5,
+                        onnx_shape=None,
+                        **kwargs
+                    )
                 raise OnnxRuntimeAssertionError(
                     "Unexpected number of outputs '{0}', expected={1}, got={2}".format(
                         onnx, len(expected), len(output)