split one test file

_unittests/ut_onnxrt/test_onnxrt_validate.py

@@ -4,7 +4,6 @@
 import os
 import unittest
 from logging import getLogger
-import numpy
 from pandas import DataFrame, read_csv
 from pyquickhelper.loghelper import fLOG
 from pyquickhelper.pycode import (
@@ -14,7 +13,6 @@
 from sklearn.utils.testing import ignore_warnings
 import skl2onnx
 from mlprodict.onnxrt.validate import enumerate_validated_operator_opsets, summary_report
-from mlprodict.onnxrt.validate.validate_problems import _modify_dimension
 
 
 class TestOnnxrtValidate(ExtTestCase):
@@ -60,37 +58,6 @@ def test_validate_summary(self):
         piv.to_excel(os.path.join(
             temp, "sklearn_opsets_summary.xlsx"), index=False)
 
-    def test_n_features_float(self):
-        X = numpy.arange(20).reshape((5, 4)).astype(numpy.float64)
-        X2 = _modify_dimension(X, 2)
-        self.assertEqualArray(X[:, :2], X2)
-        X2 = _modify_dimension(X, None)
-        self.assertEqualArray(X, X2)
-        X2 = _modify_dimension(X, 4)
-        self.assertEqualArray(X, X2)
-        X2 = _modify_dimension(X, 6)
-        self.assertEqualArray(X[:, 2:4], X2[:, 2:4])
-        self.assertNotEqualArray(X[:, :2], X2[:, :2])
-        self.assertNotEqualArray(X[:, :2], X2[:, 4:6])
-        cor = numpy.corrcoef(X2)
-        for i in range(0, 2):
-            cor = numpy.corrcoef(X[:, i], X2[:, i])
-            self.assertLess(cor[0, 1], 0.9999)
-
-    @unittest_require_at_least(skl2onnx, '1.5.9999')
-    def test_n_features_int(self):
-        X = numpy.arange(20).reshape((5, 4)).astype(numpy.int64)
-        X2 = _modify_dimension(X, 2)
-        self.assertEqualArray(X[:, :2], X2)
-        X2 = _modify_dimension(X, None)
-        self.assertEqualArray(X, X2)
-        X2 = _modify_dimension(X, 4)
-        self.assertEqualArray(X, X2)
-        X2 = _modify_dimension(X, 6)
-        self.assertEqualArray(X[:, 2:4], X2[:, 2:4])
-        self.assertNotEqualArray(X[:, :2], X2[:, :2])
-        self.assertNotEqualArray(X[:, :2], X2[:, 4:6])
-
 
 if __name__ == "__main__":
     # TestOnnxrtValidate().test_n_features_int()

_unittests/ut_onnxrt/test_onnxrt_validate_2.py

@@ -0,0 +1,49 @@
+"""
+@brief      test log(time=40s)
+"""
+import unittest
+import numpy
+from pyquickhelper.pycode import (
+    ExtTestCase, unittest_require_at_least
+)
+import skl2onnx
+from mlprodict.onnxrt.validate.validate_problems import _modify_dimension
+
+
+class TestOnnxrtValidate(ExtTestCase):
+
+    def test_n_features_float(self):
+        X = numpy.arange(20).reshape((5, 4)).astype(numpy.float64)
+        X2 = _modify_dimension(X, 2)
+        self.assertEqualArray(X[:, :2], X2)
+        X2 = _modify_dimension(X, None)
+        self.assertEqualArray(X, X2)
+        X2 = _modify_dimension(X, 4)
+        self.assertEqualArray(X, X2)
+        X2 = _modify_dimension(X, 6)
+        self.assertEqualArray(X[:, 2:4], X2[:, 2:4])
+        self.assertNotEqualArray(X[:, :2], X2[:, :2])
+        self.assertNotEqualArray(X[:, :2], X2[:, 4:6])
+        cor = numpy.corrcoef(X2)
+        for i in range(0, 2):
+            cor = numpy.corrcoef(X[:, i], X2[:, i])
+            self.assertLess(cor[0, 1], 0.9999)
+
+    @unittest_require_at_least(skl2onnx, '1.5.9999')
+    def test_n_features_int(self):
+        X = numpy.arange(20).reshape((5, 4)).astype(numpy.int64)
+        X2 = _modify_dimension(X, 2)
+        self.assertEqualArray(X[:, :2], X2)
+        X2 = _modify_dimension(X, None)
+        self.assertEqualArray(X, X2)
+        X2 = _modify_dimension(X, 4)
+        self.assertEqualArray(X, X2)
+        X2 = _modify_dimension(X, 6)
+        self.assertEqualArray(X[:, 2:4], X2[:, 2:4])
+        self.assertNotEqualArray(X[:, :2], X2[:, :2])
+        self.assertNotEqualArray(X[:, :2], X2[:, 4:6])
+
+
+if __name__ == "__main__":
+    # TestOnnxrtValidate().test_n_features_int()
+    unittest.main()