Use onnx-weekly in CI, remove dependency on onnxconveter-common (#1179)

* Use onnx-weekly in CI

Signed-off-by: xadupre <xadupre@microsoft.com>

* remove dependency on onnxconverter-common

Signed-off-by: xadupre <xadupre@microsoft.com>

* BOOL

Signed-off-by: xadupre <xadupre@microsoft.com>

* fix wrong import

Signed-off-by: xadupre <xadupre@microsoft.com>

* fix examples

Signed-off-by: xadupre <xadupre@microsoft.com>

---------

Signed-off-by: xadupre <xadupre@microsoft.com>

Author: xadupre

.github/workflows/linux-ci.yml

@@ -13,7 +13,7 @@ jobs:
             documentation: 1
             numpy_version: '>=2.0'
             scipy_version: '>=1.7.0'
-            onnx_version: 'onnx>=1.17.0'
+            onnx_version: 'onnx-weekly'
             onnxrt_version: 'onnxruntime>=1.20.1'
             python_version: '3.12'
           - sklearn_version: '==1.5.2'
@@ -89,6 +89,9 @@ jobs:
             ${{ runner.os }}-pip-
             ${{ runner.os }}-
 
+      - name: Uninstall onnx
+        run: pip uninstall -y onnx
+
       - name: Install specific versions
         run: pip install "${{ matrix.onnx_version }}" "${{ matrix.onnxrt_version }}" "numpy${{ matrix.numpy_version }}" "scikit-learn${{ matrix.sklearn_version}}" "scipy${{ matrix.scipy_version }}"
 

CHANGELOGS.md

@@ -2,6 +2,8 @@
 
 ## 1.19.0
 
+* Removes dependency on onnxconverter-common
+  [#1179](https://github.com/onnx/sklearn-onnx/issues/1179)
 * Implements converter for QuantileTransformer
   [#1164](https://github.com/onnx/sklearn-onnx/issues/1164),
 * Refactors KNNImputer converter with local function to match

docs/examples/plot_benchmark_pipeline.py

@@ -29,7 +29,7 @@
 from timeit import timeit
 from skl2onnx.helpers import compare_objects
 import onnxruntime as rt
-from onnxconverter_common.data_types import FloatTensorType
+from skl2onnx.common.data_types import FloatTensorType
 from skl2onnx import convert_sklearn
 import numpy as np
 import pandas as pd

docs/examples/plot_custom_parser.py

@@ -34,7 +34,7 @@
 import os
 from onnx.tools.net_drawer import GetPydotGraph, GetOpNodeProducer
 import onnxruntime as rt
-from onnxconverter_common.onnx_ops import apply_identity, apply_cast, apply_greater
+from skl2onnx.common._apply_operation import apply_identity, apply_cast, apply_greater
 from skl2onnx import to_onnx, get_model_alias
 from skl2onnx.proto import onnx_proto
 from skl2onnx.common._registration import get_shape_calculator

docs/examples/plot_investigate_pipeline.py

@@ -30,7 +30,7 @@
 import pickle
 from skl2onnx.helpers import collect_intermediate_steps
 import onnxruntime as rt
-from onnxconverter_common.data_types import FloatTensorType
+from skl2onnx.common.data_types import FloatTensorType
 from skl2onnx import convert_sklearn
 import numpy as np
 import pandas as pd

docs/tests/test_documentation_examples.py

@@ -83,6 +83,12 @@ def add_test_methods(cls):
                 }:
                     reason = "unstable, xgboost not ready"
 
+                if not reason and name in {"plot_weird_pandas_and_hash.py"}:
+                    try:
+                        import onnxruntime_extensions  # noqa: F401
+                    except ImportError:
+                        reason = "onnxruntime_extensions not available"
+
                 if reason:
 
                     @unittest.skip(reason)

docs/tutorial/plot_jcustom_syntax.py

@@ -26,7 +26,7 @@
 """
 
 from skl2onnx.common.data_types import guess_proto_type
-from onnxconverter_common.onnx_ops import apply_sub
+from skl2onnx.common._apply_operation import apply_sub
 from onnxruntime import InferenceSession
 from skl2onnx import update_registered_converter
 from skl2onnx import to_onnx
@@ -128,7 +128,6 @@ def decorrelate_transformer_converter(scope, operator, container):
 
     op_name = scope.get_unique_operator_name("sub")
     sub_name = scope.get_unique_variable_name("sub")
-    # This function is defined in package onnxconverter_common.
     # Most common operators can be added to the graph with
     # these functions. It handles the case when specifications
     # changed accross opsets (a parameter becomes an input

pyproject.toml

@@ -48,13 +48,14 @@ select = [
 "**/__init__.py" = ["F401"]
 "docs/**" = ["B018", "E402"]
 "skl2onnx/algebra/onnx_ops.py" = ["F821"]
-"skl2onnx/common/_apply_operation.py" = ["F403", "F405"]
+"skl2onnx/common/_apply_operation.py" = ["F403", "F405", "RUF005"]
+"skl2onnx/common/data_types.py" = ["ISC003"]
 "tests/**" = [
     "B007", "B019", "B028", "B904",
     "C401", "C403", "C405", "C406", "C408", "C413", "C416", "C417",
     "PIE808", "PIE810",
-    "RUF005", "RUF012", "RUF010", "RUF015",
-    "SIM102", "SIM105", "SIM113", "SIM114", "SIM118", "SIM300",
+    "RUF005", "RUF012", "RUF010", "RUF015", "RUF046", "RUF051",
+    "SIM102", "SIM105", "SIM113", "SIM114", "SIM118", "SIM300", "SIM905",
     "UP015", "UP018", "UP028", "UP030", "UP031", "UP032"
 ]
 "tests_onnxmltools/**" = ["B028", "B904", "C403", "C408", "C413", "C417", "PIE808", "PIE810", "RUF010", "RUF015", "SIM102", "SIM105", "SIM118", "UP015", "UP028", "UP030", "UP031", "UP032"]

requirements.txt

@@ -1,3 +1,2 @@
 onnx>=1.2.1
 scikit-learn>=1.1
-onnxconverter-common>=1.7.0

skl2onnx/_supported_operators.py

@@ -529,7 +529,7 @@ def build_sklearn_operator_name_map():
         }
     )
     if None in res:
-        del res[None]
+        del res[None]  # noqa: RUF051
     return res